Systems and methods for electroencephalogram monitoring

Abstract

Provided herein are systems, kits, and methods for monitoring brain activity. In some implementations, the systems include multiple wearable sensors having a housing with an extended, rounded shape, removably attached to a patient's scalp, and monitoring electroencephalogram (EEG) signals. Approaches are disclosed for prompting a user to position and activate the wearable sensors. Approaches are disclosed for facilitating collection, synchronization, and processing of EEG signals. Approaches are disclosed for handing off control of the wearable sensors between portable computing devices.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to U.S. Provisional Patent Application No. 63 / 380132, filed October 19, 2022, and is a continuation-in-part of U.S. Patent Application Nos. 18 / 067611, 18 / 067592, and 18 / 067608, filed December 16, 2022, each of which is incorporated by reference in its entirety.

[0002] STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT This invention was made with government support under Grant Nos. 4U44NS121562-03 and 5SB1NS100235-06 awarded by the Department of Health and Human Services. The U.S. Government has certain rights in this invention.

[0003] This application relates to systems and methods for monitoring brain activity using one or more wireless electroencephalogram sensors. [Background technology]

[0004] An electroencephalogram (EEG) is a diagnostic tool that measures and records a person's brain's electrical activity to assess brain function. Multiple electrodes are attached to a person's head and connected by wires to a machine. The machine amplifies the signal and records the person's brain's electrical activity. Electrical activity is generated by the summation of neural activity across multiple neurons. These neurons generate small voltage fields. The aggregate of these voltage fields produces an electrical reading that can be detected and recorded by electrodes on the person's head. The EEG is a superposition of multiple simpler signals. In normal adults, the amplitude of EEG signals typically ranges from 1 microvolt to 100 microvolts; when measured using subdural electrodes, EEG signals are approximately 10 to 20 millivolts. Monitoring the amplitude and temporal dynamics of the electrical signals provides information about underlying neural activity and a person's medical condition.

[0005] There are thousands of hospitals in the United States. Many of these hospitals are regional or local hospitals. These regional or local hospitals are traditionally part of a hospital system or network. An example of one such network includes several regional hospitals with one major tertiary hospital. Regional or regional hospitals outside of any large hospital network typically contract with large tertiary hospitals for emergency and intensive care solutions outside of the regional or local hospital's specialty.

[0006] EEG monitoring has traditionally only been available in large tertiary hospitals that support neurology departments with EEG services. Many hospitals do not offer EEG monitoring. These hospitals arrange with larger tertiary hospitals or their partners when such monitoring is necessary or desirable for a patient. This traditionally takes the form of patient referral to a tertiary hospital for specialist services. In many cases, this involves transferring or transporting the patient to the tertiary hospital for services. This creates many problems, especially for patients in rural areas. As a result, it is desirable to provide improvements in EEG monitoring systems and methods. Summary of the Invention

[0007] EEGs can be performed to diagnose epilepsy, investigate problems related to loss of consciousness or dementia, examine brain activity in people in a coma, study sleep disorders, monitor brain activity during surgery, and monitor for further physical problems.

[0008] Disclosed herein are systems and methods for monitoring brain activity using one or more wireless EEG sensors configured to be removably positioned at one or more locations on a patient's scalp. One or more computing devices can communicate with the EEG sensors to facilitate setting up the EEG sensors and receiving and processing EEG data collected by the EEG sensors. Advantageously, accurate EEG measurements can be obtained and processed to determine one or more physiological conditions of the patient, such as seizures, epilepsy, etc. Additionally, the disclosed systems and methods allow non-professionals to set up EEG monitoring, allowing a much larger patient population to benefit from monitoring.

[0009] In the following description, various implementations are described. For purposes of explanation, specific configurations and details are set forth in order to provide a thorough understanding of the implementations. However, it will also be apparent to those skilled in the art that the implementations may be practiced without the specific details. Additionally, well-known features may be omitted or simplified so as not to obscure the described implementations. [Brief explanation of the drawings]

[0010] [Figure 1A] 1A and 1B are perspective top and bottom views of an EEG recording wearable sensor. [Figure 1B] 1A-1D are various views of an EEG recording wearable sensor. [Figure 1C] 1A-1D are various views of an EEG recording wearable sensor. [Figure 1D] 1A-1D are various views of an EEG recording wearable sensor. [Figure 2A] 1 shows an exemplary attachment. [Figure 2B] 1 illustrates an exemplary attachment placed on a wearable sensor aligned over an electrode. [Figure 2C] 1 illustrates an exemplary sensor placed on a patient's scalp. [Figure 3A] FIG. [Figure 3B]FIG. [Figure 3C] FIG. [Figure 4] FIG. [Figure 5] 1 shows a kit or system for monitoring brain activity. [Figure 6] FIG. 1 is a diagram of an EEG monitoring system. [Figure 7A] 1 shows a flow diagram of a process for session setup. [Figure 7B] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 7C] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 7D] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 7E] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 7F] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 7G] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 7H] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 7I] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 7J]10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 7K] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 7L] FIG. 1 is a flow diagram of a process for sensor setup and provisioning. [Figure 8] FIG. 1 is a diagram of a sensor control forwarding environment. [Figure 9A] 10 illustrates exemplary screens related to data recording and sensor management displayed on a portable computing device. [Figure 9B] 10 illustrates exemplary screens related to data recording and sensor management displayed on a portable computing device. [Figure 9C] 10 illustrates exemplary screens related to data recording and sensor management displayed on a portable computing device. [Figure 9D] 10 illustrates exemplary screens related to data recording and sensor management displayed on a portable computing device. [Figure 9E] 10 illustrates exemplary screens related to data recording and sensor management displayed on a portable computing device. [Figure 10A] We present a method for synchronizing sensor data from multiple independent wireless EEG sensors. [Figure 10B] We present a method for synchronizing sensor data from multiple independent wireless EEG sensors. [Figure 10C] 1 illustrates another method for synchronizing sensor data from multiple independent wireless EEG sensors. [Figure 11A] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11B] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11C] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11D] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11E] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11F] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11G] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11H] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11I] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11J] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11K] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11L] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11M] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11N]10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11O] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11P] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11Q] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11R] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11S] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11T] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11U] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. [Figure 11V] 10 illustrates an exemplary screen associated with sensor activation and sensor placement displayed on a portable computing device. DETAILED DESCRIPTION OF THE INVENTION

[0011] overview Certain EEG monitoring systems can include complex, multi-component medical device systems that require technical expertise for setup and adjustment. When such systems are used outside of large or research hospitals with specialized expertise, setup and adjustment can be difficult and prone to user error. EEG monitoring systems that use multiple sensor components also require time synchronization across individual devices to combine sensor data. Achieving sensor time synchronization across multiple sensor devices can be difficult to achieve when the devices are not wired together. EEG monitoring systems can also be used for long-term use in homes or hospitals of any size or specialty, including, for example, small general hospitals in rural areas. Long-term EEG recording requires a high level of complexity in setup and adjustment, but needs to be seamless and simple for everyday use.

[0012] EEG monitoring systems and methods are described in U.S. Patent No. 11,020,035 and U.S. Patent Application Publication No. 2021 / 0307672, each of which is incorporated by reference in its entirety.

[0013] Improved systems, kits, and methods for EEG monitoring are described herein.

[0014] Wearable Sensors and EEG Monitoring Kits 1A shows perspective top and bottom views of an EEG-recording wearable sensor 101, which may be used as a seizure monitoring tool. As shown in FIG. 1A, the wearable sensor 101 is contained within a housing 102. The housing 102 may be formed from a plastic, polymer, composite material, etc. that is water-resistant, waterproof, etc.

[0015] The housing 102 can contain all of the electronics for recording EEG from at least two electrodes 104, 105. The electrodes 104, 105 are on the bottom or scalp-facing side shown on the right side of FIG. 1A. The electrodes 104, 105 can be formed from any suitable material. For example, the electrodes 104, 105 can include gold, silver, silver-silver chloride, carbon, combinations thereof, etc. One of the electrodes 104, 105 can be a reference electrode and the other can be a measurement (or metering) electrode. As mentioned above, the entire wearable sensor 101 can be contained within the waterproof housing 102. The wearable sensor 101 can be designed to be a self-contained EEG machine that is single-use and disposable per user. The wearable sensor 101 can include three or more electrodes. In some cases, the wearable sensor 101 includes three electrodes. In some implementations, the wearable sensor 101 includes four electrodes. Additional electrodes (such as a third and / or fourth electrode) may be formed of any suitable material, such as gold, silver, silver-silver chloride, carbon, combinations of the above, etc.

[0016] The wearable sensor 101 has two electrodes 104, 105 and can be used alone or in combination with other wearable sensors 101 (such as three other wearable sensors 101) as a separate tool for monitoring (and in some cases counting) seizures. It may be desirable, but not necessary, for the user to have a previous diagnosis of a seizure disorder using conventional wired EEG based on a 10-20 montage. This diagnosis provides clinical guidance regarding the optimal location for placing the wearable sensor 101 to record electrographic seizure activity in an individual user. In some cases, the spacing of the electrodes 104, 105 uses a bipolar derivation to form a single channel of EEG data.

[0017] 1B is a perspective top view of an EEG-recording wearable sensor 101 with a housing 102 having an extended (or elongated) rounded shape. Such a shape can be referred to as a jellybean shape and can facilitate accurate placement on a patient in the correct orientation as well as promote patient comfort and long-term wear.

[0018] In some cases, the EEG recording wearable sensor 101 is shaped to fit behind the ear. The EEG recording wearable sensor 101 can be shaped to fit along the hairline. The EEG recording wearable sensor 101 can be shaped to fit along the scalp. For example, as shown in FIG. 1B , the EEG recording wearable sensor 101 has an extended, rounded shape configured to fit around or complement a user's hairline, thereby facilitating discreet placement of the sensor on the user's scalp while facilitating collection of EEG signals. In some implementations, the housing 102 includes a narrow portion configured to curve around the user's hairline. The narrow portion can be concave, as shown in FIG. 1B . FIG. 1C provides a cross-sectional view, and FIG. 1D provides a perspective view of the EEG recording wearable sensor 101 of FIG. 1B . 1C-1D show that the housing 102 includes a narrow portion 110 (which may be concave). The side of the housing 102 having the narrow portion 110 can be positioned closer to the patient's ear (see FIG. 2C), which can facilitate discreet wearing and EEG signal collection. The narrow portion 110 can be thinner than other portions of the housing 102. The housing 102 can thicken (or widen) from the end including the narrow portion 110 to the opposite end 111. The opposite end 111 can be convex, as shown in FIG. 1B. Such a shape and varying thickness of the housing 102 can facilitate discreet wearing. The thickness of the housing 102 at its widest point can be approximately 10.0 mm, 9.5 mm, 9.0 mm, 8.5 mm, 8.0 mm, 7.5 mm, 7.0 mm, 6.5 mm, 6.0 mm, 5.5 mm, 5.0 mm, 4.5 mm, 4.0 mm, or within a range consisting of any of the aforementioned values.

[0019] In some implementations, the EEG recording wearable sensor 101 is shaped to mimic the appearance of a hearing aid. The EEG recording wearable sensor 101 can include an antenna.

[0020] In some cases, the EEG recording wearable sensor 101 includes a power source supported by the housing and configured to power the electronic circuitry. In some cases, the EEG recording wearable sensor 101 includes a rechargeable battery. The EEG recording wearable sensor 101 may include electrodes. The EEG recording wearable sensor 101 may include at least two electrodes positioned on the exterior surface of the housing and configured to detect EEG signals indicative of the user's brain activity when the housing is positioned on the user's scalp. The electrodes may be disposed within the housing 102 of the EEG recording wearable sensor 101. Unlike conventional wired EEG systems employing a 10-20 montage, the EEG recording wearable sensor 101 may allow for a much smaller spacing between the measurement electrode and the reference electrode, which not only makes the housing 102 more compact but also improves signal quality. The distance between the electrodes may be configured to enable EEG signal capture with less noise, thus improving signal quality. The distance between the electrodes may be reduced, especially when compared to conventional wired EEG systems employing a 10-20 montage. The distance between the electrodes can be about 25 mm or less center-to-center, about 20 mm or less center-to-center, about 18 mm or less center-to-center, about 15 mm or less center-to-center, about 10 mm or less center-to-center, or a range constructed from any of the above values. The housing 102 can be configured such that the electrodes are disposed at a distance configured to enable better EEG signal capture.

[0021] The EEG-recording wearable sensor 101 includes electronic circuitry that may be supported by a housing 102. The electronic circuitry may be configured to process EEG signals detected by at least two electrodes. In some implementations, the electronic circuitry is configured to wirelessly communicate the processed EEG signals to a remote computing device. The remote computing device may be a portable computing device as described herein.

[0022] The extended, rounded shape of the EEG recording wearable sensor 101 may enable the EEG recording wearable sensor 101 to provide (a) adequate electrode pair spacing to enable EEG signal capture, (b) a sealed housing 102 large enough to accommodate a complete electronic package including an antenna and battery to support frequent communications (such as Bluetooth or Bluetooth Low Energy (BLE)), and / or (c) a housing 102 design that complements the curvature of the scalp and / or around the hairline and / or behind the ears.

[0023] In some cases, the surface area of ​​the housing 102 is approximately 8.5 cm 2 , 8.0 cm 2 , 7.5 cm 2 , 7.0 cm 2 , 6.5 cm 2 , 6.0 cm 2 , 5.5 cm 2 , 5.0 cm 2 , 4.5 cm 2 , or within a range constructed from any of the foregoing values. The surface area of ​​the jellybean shaped housing 102 shown in FIG. 1B can be approximately 20 cm, 19.5 cm, 19.0 cm, 18.5 cm, 18.0 cm, 17.5 cm, 17.0 cm, 16.5 cm, 16.0 cm, 15.5 cm, 15.0 cm, 14.5 cm, 14.0 cm, 13.5 cm, 13.0 cm, 12.5 cm, 12.0 cm, 11.5 cm, 11.0 cm, 10.5 cm, 10.0 cm, 9.5 cm, 9.0 cm, 8.5 cm, 8.0 cm, 7.5 cm, 7.0 cm, 6.5 cm, 6.0 cm, 5.5 cm, 5.0 cm, 4.5 cm or less, or a range constructed from any of the values ​​recited above. 1B can have a volume of approximately 8.0 cm, 7.5 cm, 7.0 cm, 6.5 cm, 6.0 cm, 5.0 cm, 4.5 cm, 4.0 cm, 3.5 cm, 3.0 cm, 2.5 cm, 2.0 cm, or less, or within a range consisting of any of the aforementioned values. The wearable sensor 101 can be placed anywhere on the patient's scalp (such as behind the ear) to record EEG.

[0024] The wearable sensor 101 may be packaged such that removal from the package activates the circuitry. Implementations of the wearable sensor 101 may be similar to traditional wired It can be placed anywhere on the scalp, similar to the placement of EEG electrodes. The wearable sensor 101 can be self-adhered to the scalp through conductive adhesive, adhesive with conductive properties, and / or through mechanical means such as intradermal fixation using shape memory metal.

[0025] Once attached to the scalp (e.g., using an attachment as described below), some implementations enable the wearable sensor 101 (alone or in combination with one or more other wearable sensors 101, such as three other wearable sensors 101) to function as a seizure detection device. The wearable sensor 101 can record EEG continuously and uninterrupted for up to seven days. In some implementations, each EEG-recording wearable sensor 101 is configured to detect EEG signals independently from the other sensors. Following the recording session, the wearable sensor 101 may be mailed and returned to a service that reads the EEG to identify epileptiform activity in accordance with ACNS guidelines. In some cases, data may be retrieved from the wearable sensor 101 via an IO data retrieval port (not shown) and uploaded or otherwise transmitted to a service for reading the EEG data. The IO data retrieval port can operate with any suitable IO protocol, such as a USB protocol, a Bluetooth protocol, or the like. Epileptiform activity such as seizures and interictal spikes may be identified in a report along with EEG recording attributes and made available to a physician, such as through the user's electronic medical record.

[0026] The wearable sensor 101 may employ capacitive coupling as a means to spot-check signal quality. A handheld or other device can be brought close to the wearable sensor 101 to capacitively couple with the device as a means to interrogate the EEG or impedance signal in real time.

[0027] The wearable sensor 101 may be used to alert to seizures in real time or near real time. The wearable sensor 101 may continuously transmit to a base station (not shown), which executes seizure detection algorithm(s) in real time. The base station may sound an alarm if a seizure is detected, either at the base station itself or through communication to another device (not shown) capable of providing a visual and / or audio and / or tactile alarm. The base station may also keep EEG recordings for later review by an epileptologist. These EEGs may also be archived in an electronic medical record or otherwise stored.

[0028] The wearable sensor 101 can be used to record infrasonic events from the scalp, such as cortical spreading depression. An amplifier circuit (not shown) can be suitable for recording DC signals. Alternatively, the amplifier circuit can be suitable for recording both DC and AC signals. The wearable sensor 101 can be used as a means to monitor the presence or absence of cortical spreading depression and / or seizures or other epileptiform activity after a suspected stroke event. The wearable sensor 101 can be placed on a patient's scalp by any type of healthcare provider, such as an emergency medical technician, doctor, nurse, or the like.

[0029] In some implementations, the wearable sensor 101 may employ capacitive coupling to monitor cortical spreading depression in real time. Spreading depression can be analyzed over time and displayed as an EEG visualization. The wearable sensor 101 can store these EEGs (e.g., in storage) for later retrieval. These EEGs can also be archived in electronic medical records, etc.

[0030] FIG. 2A shows attachment 200 being peeled away from backing 201 to reveal the adhesive side. Attachment 200 may be referred to as a sticker or adhesive. The backing 201 can be made of paper, plastic, or any other suitable material. FIG. 2B shows the attachment 200 disposed on the wearable sensor 101 aligned over the electrodes 104, 105. In some cases, the attachment is shaped to substantially conform to an expanded, rounded shape and includes a first side configured to attach to the exterior surface of the housing 102 of the wearable sensor 101. In some implementations, the attachment includes a second side configured to removably position the wearable sensor 101 on the user's scalp. A layered attachment 200 can be provided to the user, where a layer (the backing 201) can be removed to expose a hydrogel-containing adhesive in wells aligned with the positioning of the electrodes (such as electrodes 104, 105). The attachment can then be placed over the sensor (sensor 101) and then on the user's skin to adhere the sensor, such as sensor 101, to the user's skin. Although the attachment 200 may be illustrated as having a rectangular shape, in any of the implementations disclosed herein, the attachment 200 may have a jelly bean shape that matches the shape of the housing 102 illustrated in FIG. 1B.

[0031] FIG. 2C shows a sensor 101 placed on a patient's scalp. The sensor 101 is reversibly attached to the scalp using an attachment 200. The sensor 101 is positioned at a suitable location on the user, for example, on the scalp below the hairline, to sense and record EEG data. The EEG data may be analyzed on-board, for example, through the application of analytics or machine learning models stored in the sensor 101, or may be analyzed by a local or remote device, or a combination of the above. By way of example, the sensor 101 can communicate to a local device using a personal area network (PAN), such as communicating data to a smartphone or tablet using a wired or wireless protocol, for example, secure Bluetooth Low Energy (BLE). Similarly, the sensor 101 can communicate with a remote device using a wide area network (WAN), such as communicating EEG data to a remote or cloud server over the internet, with or without communicating through an intermediate device such as a local device.

[0032] The hydrogel is conductive and also provides sufficient adhesion to the scalp for effective EEG recording during long wear times. Alternatively, the wearable sensor 101 may be adhered with a combination of conductive hydrogel and an adhesive structure. After use, the attachment 200 can be simply peeled off the wearable sensor 101 and discarded. Before the next use (e.g., after a wear period), a new attachment 200 can be applied to the wearable sensor 101.

[0033] Consistent EEG signal data from person to person is made possible by using an integrated, converted, conductive hydrogel and adhesive construct 200. The attachment 200 allows for reversible adhesion of the wearable sensor 101 to the scalp. The design of the attachment 200 also reduces both water penetration and water evaporation from the hydrogel during extended wear times. In some cases, the attachment 200 is fabricated by laminating several adhesive and non-adhesive layers with wells filled with hydrogel and sandwiched between release liners. In some implementations, the attachments 200 are further packaged individually in airtight and watertight pouches.

[0034] 3A shows an exploded view of attachment 200. In the example of FIG. 3A, attachment 200 includes a clear PET (polyethylene terephthalate) liner 301, a hydrogel 302, a hydrogel 303, a transfer adhesive 304, and a paper backing 201. Attachment 200 is molded to substantially conform to an expanded, rounded shape. The attachment 200 may include a first side (sensor side) configured to be attached to an exterior surface of the housing 102 of the wearable sensor 101. In some cases, the first side of the attachment 200 is configured to be attached to a bottom surface of the wearable sensor 101. The attachment 200 may include a second side configured to removably position the wearable sensor 101 on a user's scalp (skin side). In some implementations, the transparent PET liner 301 is configured to be removed before the attachment 200 is placed on the user's scalp. The hydrogels 302, 303 can facilitate repositioning the wearable sensor 101 on the user's scalp.

[0035] FIG. 3B shows an exploded view of attachment 200. In the example of FIG. 3B, attachment 200 includes layers 1101-1106. First layer 1101 can include a top liner that can be composed of a thermoplastic resin. The thermoplastic resin can be polyethylene terephthalate (PET). In some embodiments, second layer 1102 includes a cured hydrogel. Third layer 1103 can include a transfer adhesive. In some embodiments, fourth layer 1104 includes a nonwoven fabric. The nonwoven fabric can be a scrim spunlace nonwoven polyester. Fifth layer 1105 can include an adhesive. The adhesive can be a thick double-sided adhesive foam. Sixth layer 1106 can include a bottom liner that can be composed of a thermoplastic resin. The thermoplastic resin can be PET.

[0036] In some cases, two or more of the first layer 1101, the second layer 1102, the third layer 1103, the fourth layer 1104, the fifth layer 1105, and the sixth layer 1106 are stacked on top of each other such that the second layer 1102 is disposed between the first layer 1101 and the third layer 1103. In some implementations, the first layer 1101 is removable. The sixth layer 1106 may be removable. The third layer 1103 and the fifth layer 1105 can have openings formed therein. The openings may align with the electrodes of the sensor.

[0037] One or more of the third layer 1103, fourth layer 1104, and fifth layer 1105 can include a cured hydrogel. The hydrogel can be intermixed with the nonwoven fabric of the fourth layer 1104. The hydrogel can be transitioned from a liquid or semi-liquid or gel form to a solid or semi-solid form using a crosslinking process. The crosslinking process can be induced by the application of one or more of ultraviolet (UV) light and an electron beam.

[0038] Provided herein is a method for preparing an attachment 200. In some implementations, the method includes providing two or more layers, at least one of the two or more layers including an opening. Providing the two or more layers may include providing a fabric layer. The fabric may be a nonwoven fabric. The method may further include laminating the two or more layers. The method may include providing a hydrogel to the opening. Providing the hydrogel may include injecting the hydrogel into the opening. The method may further include fixing the layers. Fixing the hydrogel may include curing the hydrogel via UV light or electron beam exposure.

[0039] FIG. 3C shows an exploded view of attachment 200. In the example of FIG. 3C, attachment 200 includes a transparent PET liner 301, a hydrocolloid material 305, a hydrogel 303, double-sided tape 306, and a paper backing 201. Attachment 200 may include a first side (sensor side) shaped to substantially conform to an expanded, rounded shape and configured to attach to an exterior surface of housing 102 of wearable sensor 101. The first side of attachment 200 may be configured to attach to a bottom surface of wearable sensor 101. Attachment 200 may include a second side configured to removably position wearable sensor 101 on a user's scalp (skin side). In some cases, transparent PET liner 301 may be attached to attachment 20. The hydrocolloid material 305 may be configured to be removed before the wearable sensor 101 is placed on the user's scalp. The hydrocolloid material 305 may facilitate repositioning the wearable sensor 101 on the user's scalp.

[0040] FIG. 4 is a front perspective view of a charger 400. FIG. 4 shows the charger 400 in a closed configuration (left image) and an open configuration (right image). A system for monitoring brain activity can include a charger 400 with a charger housing 401. The charger housing 401 can be configured to receive power and simultaneously charge at least two wearable sensors 101. For example, the charger 400 can simultaneously receive power and charge two wearable sensors 101, or four sensors, or more sensors 101. In some implementations, the charger 400 includes multiple charging stations for the wearable sensors 101.

[0041] The wearable sensor 101 may be worn continuously for several days before needing to be removed, such as to charge an on-board power source such as a rechargeable battery. To allow for continuous monitoring, a user may have two (or more) sets of wearable sensors 101, using one (or more) while the other(s) are being recharged. Such a configuration allows for continuous EEG data capture and monitoring.

[0042] 5 illustrates a kit or system 500 for monitoring brain activity. In some cases, the kit or system 500 disclosed herein includes multiple sensors 101. For example, the kit or system 500 may include two sensors, three sensors, four sensors, five sensors, six sensors, seven sensors, eight sensors, nine sensors, ten sensors, or the like. The kit or system 500 may include two sets of sensors, with the first set being for use while the second set is charging. After the first set is used, the first set can be charged while the second set is being used. The kit or system 500 disclosed herein may include multiple attachments 200. For example, kit or system 500 may include two attachments, three attachments, four attachments, five attachments, six attachments, seven attachments, eight attachments, nine attachments, ten attachments, eleven attachments, twelve attachments, thirteen attachments, fourteen attachments, fifteen attachments, sixteen attachments, seventeen attachments, eighteen attachments, nineteen attachments, or twenty attachments, etc. The number of attachments in the plurality of attachments may be greater than the number of wearable sensors included in the plurality of wearable sensors. The number of attachments 200 in the plurality of attachments 200 may include the number of wearable sensors 101 in the plurality of wearable sensors 101 multiplied by the number of days the plurality of wearable sensors is configured to record the user's brain activity. For example, if there are four wearable sensors 101 configured to record a user's brain activity for seven days, the kit or system includes at least 28 attachments 200. For example, if there are four wearable sensors 101 configured to record a user's brain activity for three days, the kit or system includes at least 12 attachments 200.The kit or system may include additional attachments 200 in excess of the number of wearable sensors 101 in the plurality of wearable sensors 101 multiplied by the number of days the plurality of wearable sensors 101 is configured to record the user's brain activity.

[0043] Disclosed herein is a method for monitoring brain activity. The method can include removing at least one wearable sensor 101 of a plurality of wearable sensors 101 configured to record brain activity of a user. In some cases, each wearable sensor 101 can be configured to record brain activity of a user. The wearable sensors 101 include a housing 102 having an elongated, rounded shape. Each wearable sensor 101 can include at least two electrodes 104, 105 positioned on the exterior surface of the housing 102 and configured to detect EEG signals indicative of a user's brain activity.

[0044] The method may further include replacing a first attachment 200 of the plurality of attachments 200 with a second attachment 200 of the plurality of attachments 200. The first and second attachments 200 may include a first side shaped to substantially match the expanded, rounded shape of the housing 102. The first side may be configured to attach to an outer surface of the housing 102 of the at least one wearable sensor 101. The first and second attachments 200 may include a second side configured to removably position the at least one wearable sensor 101 on a user's scalp. In some cases, the number of attachments 200 in the plurality of attachments 200 exceeds the number of wearable sensors 101 in the plurality of wearable sensors 101.

[0045] The method may further include reattaching the at least one wearable sensor 101 to the user's scalp by adhering a second side of the second attachment 200 to the user's scalp. The method may further include resuming recording of EEG signals indicative of the user's brain activity.

[0046] EEG System Setup and Provisioning The systems and methods provided herein may include software to assist a user in setting up the system. The user may be a healthcare provider or a patient.

[0047] Figure 6 is a diagram of an EEG monitoring system 600. The system of Figure 6 includes a plurality of wearable sensors 601 configured to record a patient's brain activity. Each wearable sensor 601 can include at least two electrodes configured to detect signals indicative of the user's brain activity when the wearable sensor is positioned on the user's scalp. Each wearable sensor 601 can further include electronic circuitry configured to determine data related to the user's brain activity based on the signals detected by the at least two electrodes and wirelessly transmit the data related to the user's brain activity to one or more portable computing devices 602.

[0048] In some cases, the system further includes a non-transitory computer-readable medium storing instructions that, when executed by at least one processor of the one or more portable computing devices 602, cause the at least one processor to facilitate activation of the plurality of wearable sensors 601, instruct the user to position the plurality of wearable sensors 601 on the user's scalp using a plurality of attachments configured to removably attach the plurality of wearable sensors 601 to the user's scalp, and record data associated with the user's brain activity transmitted by the plurality of wearable sensors 601.

[0049] The portable computing device 602 may include communication capabilities, such as wireless communication capabilities. The portable computing device 602 may be configured to be worn by a user. The portable computing device 602 may include a smart watch, which may have a display. The portable computing device 602 may include a smart band, smart jewelry, etc., which may not have a display. The portable computing device 602 may include a tablet. The portable computing device 602 may include another computing device, such as a smartwatch, laptop, or medical-grade tablet. Such a portable computing device 602 may include a display larger than that of a smartwatch. The portable computing device 602 may connect to a remote server or cloud server through a connection with a phone application, or may connect directly to the remote server or cloud server (e.g., the portable computing device 602 may include a cellular communication chip that enables wireless communication with the remote server or cloud server).

[0050] Provided herein is a system for monitoring brain activity. In some implementations, the system includes a plurality of wearable sensors 601 configured to detect EEG signals indicative of a patient's brain activity. Each wearable sensor of the plurality of wearable sensors 601 may include at least two electrodes configured to monitor EEG signals when the wearable sensor is positioned on the patient's scalp. Each wearable sensor of the plurality of wearable sensors 601 may include electronic circuitry configured to process EEG signals monitored by the at least two electrodes. In some cases, the systems described herein further include a non-transitory computer-readable medium storing executable instructions that can be executed by at least one processor of the portable computing device 602.

[0051] 7A-7L provide example processes and screens (or modals) for setting up, activating, positioning, and verifying a wearable sensor 601. These may be implemented by or executed on a portable computing device 602, such as at least one processor of the portable computing device. While some illustrations may show a wearable sensor 601 having a particular shape or configuration, this is intended as an illustrative example and not limiting. For example, the processes and screens described herein may be used to guide a user through the setup, activation, positioning, and verification of a wearable sensor 601 having various configurations, such as a wearable sensor 601 having an extended, rounded shape as described herein. In some cases, through each screen, the system displays the next screen in response to user input; for example, a user can press a button (such as a button displayed on a touchscreen or a physical button on the portable computing device 602) to advance to the next screen showing the next instruction.

[0052] FIG. 7A shows a flow diagram of a process for setting up an EEG recording session. The process may include guiding the user through steps that may include starting a new session (610), entering basic settings (620), entering advanced settings (630), and entering patient information (640). The setup process may proceed to sensor identification 662 or may resume 650. During setup, a series of screens may be displayed on the portable computing device 602. In some cases, a start new session screen 610 is displayed. The user may interact with the screen, such as pressing a start button or a settings button, to begin setting up a new session or to open a settings menu. The system may verify whether IT contact information has already been entered; if so, the system bypasses the start new session screen 610 and automatically transitions to the basic settings screen 620. When the basic settings screen 620 is displayed, the user may enter basic settings, such as hospital IT contact information. In some implementations, the system stores the user input. When the preferences screen 620 is displayed, the system may verify that communications (e.g., Bluetooth) is enabled on the portable computing device 602 that the user is using to perform the session setup. If communications is not enabled, the system may The system may request the operating system of the device 602 to enable communications, or may prompt the user with a native modal informing the user that an app has requested communications be turned on. In response to user input, the system may display a new session start screen 610. User input to proceed to the new session start screen 610 may be permitted only if IT contact information is entered. Once the user enters a password, an advanced settings screen 630 may be displayed.

[0053] When the advanced settings screen 630 is displayed, the system can receive and store user input related to the advanced settings. Advanced settings may include a server URL and a server path. Advanced settings may also include toggling kiosk mode on / off, enabling patient barcode scanning, and enabling device barcode scanning. Advanced settings may also include manual entry of a patient barcode and / or a device barcode. In some cases, in response to user input, the system then displays a start new session screen 610. User input to proceed to the start screen may be permitted only if IT contact information is entered. When the patient information screen 640 is displayed, the system can receive and store user input related to patient information. The patient barcode may be scanned with the camera of the portable computing device 602, or the patient barcode may be entered manually. Patient information may also include the patient's first name and last name. In response to user input, the system can then display a sensor identification screen 660. User input to proceed to the sensor identification screen 660 may be permitted only if patient information is entered.

[0054] In response to user input, the process may then display a resume session modal 650. The screen may ask the user to confirm whether they want to resume session setup. In response to user input confirming the resume, the system may clear all patient and sensor data already stored in memory, and the process may resume at 610. In response to user input canceling the resume, the resume session modal 650 may close. In step 662, the user completes the session setup process and begins sensor identification, as further described in FIG. 7B.

[0055] The executable instructions may cause the at least one processor to provide instructions for scanning or entering identification information for the wearable sensor 601 before providing instructions for positioning the wearable sensor at a location on the user's scalp. FIG. 7B shows an example sensor identification screen 660. The sensor identification screen 660 may include a display of a camera-captured scan to allow a user to capture a barcode via the camera of the portable computing device 602. The system may automatically locate the barcode design in the image captured by the camera. The system may store information related to the sensor identification. The sensor identification screen 660 may include an indication of whether a sensor ID corresponding to each wearable sensor 601 of the multiple wearable sensors 601 has been entered. The sensor ID may be unique for each wearable sensor 601. In the example sensor identification screen 660, the circle corresponding to each wearable sensor of the multiple wearable sensors 601 is filled in when sensor identification information for that wearable sensor 601 is entered. In response to user input (e.g., selecting an already entered sensor), the system may overwrite the already entered sensor identification information for the wearable sensor 601 with the new sensor identification information. The system may receive and store the sensor identification information manually entered by the user. In response to the user input, the system may then display a resume session modal 650. The system may automatically display the next screen once the sensor identification information for each wearable sensor 601 of the multiple wearable sensors 601 has been entered / scanned.

[0056] FIG. 7C shows an exemplary sensor initialization screen. The screen may prompt the user to remove the contents of the pouch in preparation for placement of the one or more wearable sensors 601, such as one or more wearable sensors 601, one or more adhesives, and one or more alcohol wipes. The screen may also prompt the user to activate one or more wearable sensors 601. The user may activate the wearable sensor 601 by pressing a button on the wearable sensor 601. The wearable sensor 601 may be activated by removing a tab. As shown, the wearable sensor 601 may be activated before being positioned on the user's scalp. The screen may include an indication of whether each wearable sensor 601 of the multiple wearable sensors 601 has been activated. In the example of FIG. 7C, the circle corresponding to each wearable sensor 601 of the multiple wearable sensors 601 is filled in when that wearable sensor 601 is activated. In response to user input (e.g., selecting an already activated wearable sensor 601), the system can overwrite the sensor activation information for the already activated wearable sensor 601 with the new sensor activation information. In some cases, the system initiates a wireless scan (e.g., via Bluetooth) for the wearable sensor 601. The wireless scan may continue until recording is started or the sensor setup session is ended. When a wearable sensor 601 is detected by the wireless scan, if the detected wearable sensor 601 is among previously identified wearable sensors 601 (e.g., in the process described with respect to FIG. 7B ), the sensor information can be used to update the local state. The system can wirelessly connect with each activated wearable sensor 601 (e.g., via Bluetooth) to verify connection capability and verify that the wearable sensor 601 is operational.After each of the multiple wearable sensors 601 connects to the system, the system can wirelessly instruct the multiple wearable sensors 601 to enter a synchronization state, and then synchronization information (such as a synchronization time setting advertisement) is wirelessly transmitted to the multiple wearable sensors 601, as further described in connection with FIG. 10A, FIG. 10B, or FIG. 10C. Wireless connections with each wearable sensor 601 of the multiple sensors 601 can then be re-established. The system can instruct each wearable sensor 601 of the multiple sensors 601 to enter a sleep state. In the sleep state, the sensor 601 may not monitor EEG signals or transmit data. Once each wearable sensor 601 of the multiple sensors 601 is activated, the user can input input to proceed to the next step in setup, such as in FIG. 7E. In response to the user input, the system can then display a resume session modal 650. If a set amount of time (1 minute, 2 minutes, etc.) has passed since the start of the sensor activation process or since a sensor connection without a new wearable sensor 601 connecting, the system may display a connection timeout modal, such as the connection timeout modal of FIG. 7D.

[0057] FIG. 7D is an example connection timeout modal. The connection timeout modal can display error and troubleshooting information related to sensor activation. The system may allow the user to snooze the connection timeout modal (close it for a set amount of time), replace one or more wearable sensors 601, or end the session. If the user chooses to end the session, the system may display an end session modal. If the user chooses to replace one or more wearable sensors 601, a sensor replacement modal may be displayed. If the user chooses to snooze, the connection timeout modal may disappear. In some cases, the snooze interval (amount of time) is saved in a memory store. The user may enter the snooze interval. The system may display the connection timeout modal again after the snooze interval has elapsed. If the wearable sensor 601 is activated, Once the connection is established, the system can automatically exit the connection timeout mode.

[0058] FIG. 7E is an example of a sticker (or attachment) placement screen. Providing instructions for positioning the wearable sensor 601 at a location on the user's scalp can include instructing the use of multiple attachments configured to removably attach the wearable sensor 601 to the user's scalp. For example, the sticker placement screen can guide the user to open an adhesive pouch and remove the adhesive. The sticker placement screen can guide the user to remove a film (also referred to as a liner or backing) from the adhesive. The sticker placement screen can instruct the user to apply adhesive to the wearable sensor 601 (e.g., precisely aligned over the electrodes). The sticker placement screen can guide the user to remove a second film from the adhesive in preparation for sticker placement. In response to user input, the system can then display a resume session modal 650. The user can enter input to cause the system to proceed to the next step in setup, such as in FIG. 7F.

[0059] In some cases, the sticker may be pre-attached to the wearable sensor 601. In this case, the screen of FIG. 7E may be omitted.

[0060] The executable instructions cause at least one processor to position a wearable sensor 601 of the plurality of wearable sensors 601 at a location among a plurality of locations on the user's scalp, provide instructions to activate the wearable sensor 601, verify the identity of the wearable sensor 601, verify the impedance of the wearable sensor 601 in response to verifying the identity of the wearable sensor 601, and in response to verifying the impedance of the wearable sensor 601, provide instructions to position and activate another wearable sensor 601 of the plurality of wearable sensors 601, and perform identification and impedance verification of the other wearable sensor 601.

[0061] FIG. 7F shows an exemplary sensor placement and activation screen. The sensor can be placed at four locations on the scalp, such as behind the left ear (LE), behind the right ear (LE), left front of the forehead (LF), and right front of the forehead (RF). The sensor placement and activation screen may guide the user to swab a location on the user's body with an alcohol swab provided in the kit. For example, the location may be behind the ear or another location on the scalp. The screen may display a graphic to indicate to the user which location on the user's body should be swabbed. The sensor placement and activation screen may guide the user to place the wearable sensor 601 at a location on the patient's body (e.g., the scalp). In some cases, providing instructions for positioning the wearable sensor 601 includes displaying instructions on a screen of the portable computing device 602. For example, the screen may display a graphic to indicate to the user where to place the wearable sensor 601.

[0062] In some implementations, providing instructions for positioning the wearable sensor 601 includes displaying the location on a screen of the portable computing device 602 and instructions for activating the wearable sensor 601. For example, the sensor placement and activation screen may instruct the user to press a button on the wearable sensor 601 before or after placement at the indicated location to activate the wearable sensor 601. In some cases, a wireless connection (e.g., via Bluetooth) is made with a previously connected wearable sensor 601. The system verifies the identity of the activated wearable sensor 601 and activates the activated wearable sensor 601. The user can confirm that the wearable sensor 601 is the wearable sensor 601 identified by the user, e.g., scanned in the process described in connection with FIG. 7B or activated in the process described in connection with FIG. 7C. The screen may include an indication indicating whether each wearable sensor 601 of the plurality of wearable sensors 601 has been activated. In the example of FIG. 7F, the circle corresponding to each wearable sensor 601 of the plurality of wearable sensors 601 is filled in when that wearable sensor 601 is activated. The screen may include an indication indicating whether each wearable sensor 601 of the plurality of wearable sensors 601 remains wirelessly connected to the portable computing device 602, and may display a notification, graphic, and / or alert if an activated wearable sensor 601 is disconnected. In response to a user input, the system may display a resume placement modal, such as the resume placement modal of FIG. 7H.

[0063] When a wearable sensor 601 of the plurality of wearable sensors 601 is activated, the system may prompt the user to begin verifying that the sensor has been placed on the user's scalp, which may include initiating an impedance test of the wearable sensor(s) 601. The impedance test may be performed by the wearable sensor 601 (e.g., in response to a button press) or in response to a command from the portable computing device 602. In the example of FIG. 7F , the user may press a test button once the wearable sensor 601 is placed and activated. In some cases, when the user initiates the impedance test, a command is sent wirelessly (e.g., via Bluetooth) to the wearable sensor 601 to perform an impedance check. In some implementations, the system checks whether the impedance measurement from the wearable sensor 601 meets a predetermined threshold, such as 100 kΩ or greater or 500 kΩ or greater.

[0064] In some cases, alternative or additional approaches may be used to verify that the sensors are positioned on the user's scalp, for example, one or more inertial motion units (IMUs) or position sensors may be used.

[0065] In some implementations, if the impedance measurements do not meet a predetermined threshold, the system can provide instructions to the user, such as displaying an appropriate screen to indicate poor electrode contact. In some implementations, the executable instructions further cause the at least one processor to repeat one or more of providing instructions, verifying identification, and verifying impedance for the wearable sensor 601 in response to not verifying the impedance of the wearable sensor 601. In some cases, repeating includes providing instructions to reposition the wearable sensor 601 and verifying the impedance of the sensor. In some cases, in response to not verifying the impedance of the wearable sensor 601 a second time, the executable instructions cause the processor to resume providing instructions, verifying identification, and verifying impedance for the multiple wearable sensors 601. In some implementations, upon resuming, the system erases all saved sensor placement data at all locations and begins providing instructions, verifying identification, and verifying impedance for the multiple wearable sensors 601 starting with a first of the multiple wearable sensors 601. If the impedance is verified (e.g., the impedance measurement meets a predetermined threshold), the system can return to a placement screen with instructions for placing, activating, and testing the next wearable sensor 601 in the sequence of multiple sensors 601.

[0066] The executable instructions further include causing the at least one processor to detect whether at least two of the plurality of wearable sensors 601 are at the same location on the user's scalp or The executable instructions can cause the at least one processor to sequentially provide instructions to position, activate, verify the identification, and verify the impedance of each wearable sensor 601 of the plurality of wearable sensors 601. One wearable sensor 601 of the plurality of wearable sensors 601 can be positioned, activated, and tested for impedance at a location one at a time (i.e., in sequence). For example, a user may be instructed to place a first wearable sensor 601 in a first location, activate the first wearable sensor 601, and begin an impedance test of the first wearable sensor 601, then the user may be instructed to place a second wearable sensor 601 in a second location, activate the second wearable sensor 601, and begin an impedance test of the second wearable sensor 601, and so on. When the user begins the impedance test, if multiple wearable sensors 601 are activated prior to the impedance test, the system may display a multiple sensor activation alert modal, such as the multiple sensor activation alert modal of FIG.As another example, if multiple wearable sensors 601 are activated (e.g., in FIG. 7F ) before the impedance test begins, the system may display an activated alert modal. In some cases, determining whether multiple wearable sensors 601 are activated substantially simultaneously may be performed based on determining whether at least two sensors are activated within a threshold duration (e.g., 10 seconds or less, 30 seconds or less, or more).

[0067] FIG. 7G is an exemplary multiple sensor activated alert modal. In some implementations, the multiple sensor activated alert modal notifies the user that more than one wearable sensor 601 is activated for a location and instructs the user to position and activate only one wearable sensor 601 at a time. The multiple sensor activated alert modal may instruct the user to wait. When the multiple sensor activated alert modal is displayed, the system may connect to the wearable sensors 601 and command all connected wearable sensors to enter a sleep state. The user may choose to dismiss or snooze the multiple sensor activated alert mode. When the user chooses to dismiss or snooze the multiple sensor activated alert mode, the system may command any connected, improperly positioned wearable sensors 601 to enter an inactive state. When the user chooses to dismiss or snooze the multiple sensor activated alert mode, the system may again display the sensor placement and activation screen.

[0068] FIG. 7H shows an exemplary resume deployment mode. In some cases, the resume deployment modal prompts the user to confirm or cancel whether to resume the deployment process. When deployment is resumed, the system may erase all saved sensor deployment data at all locations. When deployment is resumed, the system may instruct the sensors to go to sleep. When placement is resumed, the system may display a sticker placement screen, such as the sticker placement screen of Figure 7E. When the resume is canceled, the resume placement mode may be cancelled.

[0069] FIG. 7I shows an exemplary verification session screen. This screen may be displayed after all sensors have been placed and activated. The system may display a screen to allow the user to verify that each sensor identification matches the sensor identification recorded in the system for each location (e.g., recorded in FIG. 7B). In the example of FIG. 7I, the portable computing device 602 displays a diagram of a head with squares representing sensor placement (e.g., sensor ID) and sensor status (e.g., connected). The portable computing device 602 may display a notification if there is a problem with one or more of the placements of the wearable sensors 601, such as an activation, identification, or impedance issue. For example, a graphical representation of a sensor having a problem may flash red / blue, as an alert modal appears and snoozes. In response to user input, such as clicking on the representation of the wearable sensor 601 on the screen, the system may display a sensor modal with sensor information. In response to user input (e.g., selecting cancel), the system may display an end session modal. In response to user input, the system may start a recording session on one of the portable computing devices 602. In some examples, multiple "Start Recording" options may be displayed for recording on any of multiple portable computing devices 602. For example, FIG. 7I may include an option "Start Recording on Tablet" and another option "Start Recording on Watch." A user may select one of the "Start Recording" options, and the portable computing device 602 may instruct the wearable sensor 601 to begin recording EEG signals. The portable computing device 602 may receive the EEG signals from the sensor 601 continuously or periodically via a wireless connection.

[0070] After the verification is complete, the EEG recording session can begin. As part of the subsequent verification, the wearable sensors 601 may be synchronized, as further described in connection with FIG. 10A, FIG. 10B, or FIG. 10C. FIG. 7J shows an exemplary screen informing the user that synchronization is occurring. The executable instructions may further cause the at least one processor to record processed EEG signals wirelessly transmitted by the plurality of wearable sensors 601 in response to verifying the identity and impedance of each wearable sensor 601 among the plurality of wearable sensors 601. FIG. 7K is an exemplary active recording screen. The system may store a recording start time in memory. Wireless scanning (e.g., Bluetooth scanning) may be stopped. Wireless scanning may be restarted if the wearable sensor 601 disconnects. Real-time data notifications may be enabled for all wearable sensors 601. The portable computing device 602 may display a notification if there are issues with one or more of the placements of the wearable sensors 601, such as activation, identification, or impedance issues. For example, a graphical representation of a wearable sensor 601 having a problem may flash red / blue, an alert modal appears, snooze, etc. In response to a user input, such as clicking on the representation of the wearable sensor 601 on the screen of the portable computing device 602, the system can display a sensor modal with sensor information.

[0071] The portable computing device 602 can send messages containing information about session events for started and stopped recordings to a remote or cloud server over the Internet. The start recording or stop recording messages may include patient information, wearable sensor(s) 601 information, recording start time, and The recording information may contain information such as the time and / or recording end time. The portable computing device 602 may receive messages containing real-time data / events from multiple wearable sensors 601 and communicate the messages containing real-time data / events to a remote server or cloud server via the Internet. The portable computing device 602 may display a notification on the active recording screen if there are issues with one or more of the wearable sensor 601 placements, such as activation, identification, or impedance issues. In the example of FIG. 7K , the portable computing device 602 displays a diagram of a head with squares representing the placement of the wearable sensors 601 (e.g., sensor ID) and sensor status (e.g., connected). The user may interact with the display to end the recording session. The portable computing device 602 may display diagnostic information as well as the session ID and portable computing device 602 ID.

[0072] In response to user input (such as clicking "Stop Recording"), the system may display an end recording modal. After a predetermined time (e.g., 48 hours) has elapsed since recording began, the system may automatically end the recording session and display an end session screen (not shown).

[0073] 7L shows a flow diagram of a process for guiding a user through sensor setup and provisioning. As described herein, the process may include guiding a user through the steps of sensor(s) activation 710, sensor(s) placement 720, data recording 730, and self-diagnosis 740.

[0074] In some cases, activating the sensor(s) 710 includes using an application to guide the user to scan a barcode associated with the wearable sensor 601 with the camera functionality of the portable computing device 602. Activating the sensor(s) 710 may include using the application to guide the user to manually enter the barcode associated with the wearable sensor 601 using the portable computing device 602. The application may create a passcode for each sensor based on the scanned or entered barcode. The passcode may be unique and may ensure that only the four provisioned wearable sensors 601 set up in the session can communicate with the portable computing device 602. The application may guide the user to press and / or hold a button on each wearable sensor 601 to activate the wearable sensor 601.

[0075] The application can display information related to sensor activation on the display of the portable computing device 602. The information related to sensor activation can include whether each wearable sensor 601 has been activated. FIG. 7F shows an example screen associated with sensor(s) activation 710 and sensor placement 720 displayed on the portable computing device 602. In some cases, sensor(s) placement 720 includes guiding the user, using the application, to place the wearable sensors 601 on the patient's scalp. The application can walk the user through multiple images, one for each wearable sensor 601, and show the user where they should place each sensor.

[0076] As described herein, placement of multiple wearable sensors 601 can be performed sequentially. Sequential placement of wearable sensors 601 can include activating a first sensor, providing instructions to place the first sensor at a first location on the scalp after activating the sensor, and activating a second sensor after the first sensor is placed at the first location. and verifying the placement of the first sensor. This process may then be repeated sequentially for each remaining wearable sensor 601. Because the wearable sensors 601 may be position-independent, positioning the sensors on the scalp may be prone to error. Without sequential placement, there is the potential for user error associated with inaccurate mapping between the wearable sensor's position on the scalp and its position noted in the system, resulting in misalignment or erroneous information about the sensor signal and associated position. Advantageously, sequential placement ensures that the position of each wearable sensor in the system accurately represents the sensor's actual position on the scalp, facilitating accurate monitoring of EEG signals. Using such accurate position mapping, the system can provide precise and easy-to-follow instructions for resolving any errors, replacing attachments, or the like. For example, as described herein in connection with FIG. 9B , the system can provide a graphic or image indicating the position of the wearable sensor 601 on the scalp in response to detecting an error in the operation of the wearable sensor, such as a connection error, a signal error, or the like.

[0077] 11A-11V show screens for sequential placement of wearable sensors 601. The screens show sequential placement of four wearable sensors 601: behind the left ear (LE), behind the right ear (LE), left front of the forehead (LF), and right front of the forehead (RF). In some implementations, the number of sensors and their location on the scalp can be varied.

[0078] FIG. 11A shows a screen instructing the user to select a wearable sensor 601 to be placed behind the left ear. Similar to FIG. 7C, the screen in FIG. 11B instructs the user to activate the sensor. Screen 11B can confirm that communication with the sensor has been established. For example, a sensor icon with sensor ID "801" is shown as associated with the text "left ear." The system can then display the screen in FIG. 11C , which guides the user to correctly place the sensor behind the left ear. In particular, the screen shows a representation of a person's scalp showing sensor 1106 positioned behind the left ear. In some cases, correctly orienting the sensor on the scalp can be important because incorrect orientation of the sensor on the scalp (e.g., upside down) can cause incorrect orientation of the electrodes and inaccurate or suboptimal sensing of the EEG signal. To guide the user to correctly orient the sensor, the screen shows sensor 1102 oriented for positioning behind the left ear. Guide 1104 includes an arrow indicating how indicia (e.g., multiple dots on the sensor housing) should be oriented when the sensor is placed on the scalp. The screen can guide the user to match the location of the markings on the sensor 1102 with the location of the sensor 1106, which is shown in a position behind the left ear. In some cases, the shape of the sensor housing (e.g., the jelly bean described herein) can serve as the markings.

[0079] After the sensor is positioned on the scalp, a verification can be performed that the sensor is placed on the user's scalp, as shown in the screen of FIG. 11D (showing the text "Checking..."). As described herein, the verification can include performing an impedance test. The verification can be performed automatically without user input or action. After successful completion of the verification, the screen of FIG. 11E can be shown, which confirms that the sensor is properly placed behind the left ear (showing the text "Secured").

[0080] The system may map the sensor (such as the sensor with sensor id "801") with a location behind the left ear after verification is complete, such as after a connection with the sensor is established (as described in connection with FIG. 11B), or before verification.

[0081] The system can then prompt the user to place the wearable sensor 601 at the next location on the scalp, such as the left front side of the forehead. Similar to Figures 11A and 11B, Figures 11F and 11G show screens prompting the user to select another wearable sensor 601 for placement on the left forehead and activate such sensor (e.g., the sensor with sensor id "27F" is selected).

[0082] FIG. 11H shows a screen with instructions for properly orienting the sensor on the scalp. Similar to FIG. 11C, the screen in FIG. 11H shows a representation of a person's scalp, showing the sensor 1116 positioned on the left forehead. To guide the user in properly orienting the sensor, the screen shows the sensor 1112 oriented for positioning on the left forehead. A guide 1114 includes an arrow indicating how the markings should be oriented when the sensor is placed on the scalp. The screen can guide the user to match the position of the markings on the sensor 1112 with the position of the sensor 1116 shown in the left forehead position. FIGS. 11I and 11J show verification and confirmation screens similar to FIGS. 11D and 11E.

[0083] The system can then instruct the user to place the wearable sensor 601 at a next location on the scalp, such as the front right side of the forehead. Similar to Figures 11A and 11B, Figures 11K and 11L show screens instructing the user to select another wearable sensor 601 for placement on the right frontal area and activate such sensor (e.g., the sensor with sensor id "D4F" is selected).

[0084] FIG. 11M shows a screen with instructions for properly orienting the sensor on the scalp. Similar to FIG. 11C, the screen in FIG. 11M shows a representation of a person's scalp, showing the sensor 1126 positioned on the right forehead. To guide the user in correctly orienting the sensor, the screen shows the sensor 1122 oriented for positioning on the right forehead. A guide 1114 includes an arrow indicating how the markings should be oriented when the sensor is placed on the scalp. The screen can guide the user to match the position of the markings on the sensor 1122 with the position of the sensor 1126 shown in the right forehead position. FIGS. 11N and 11O show verification and confirmation screens similar to FIGS. 11D and 11E.

[0085] The system can then instruct the user to place the wearable sensor 601 at the next location on the scalp, such as behind the right ear. Similar to Figures 11A and 11B, Figures 11P and 11Q show screens instructing the user to select another wearable sensor 601 for placement behind the right ear and activate such sensor (e.g., the sensor with sensor id "734" is selected).

[0086] FIG. 11R shows a screen with instructions for correctly orienting the sensor on the scalp. Similar to FIG. 11C, the screen in FIG. 11R shows a representation of a person's scalp, showing the sensor 1136 positioned behind the right ear. To guide the user in correctly orienting the sensor, the screen shows the sensor 1132 oriented to be positioned behind the right ear. A guide 1134 includes an arrow indicating how the markings should be oriented when the sensor is placed on the scalp. The screen can guide the user to match the position of the markings on the sensor 1132 with the position of the sensor 1136 shown in the position behind the right ear. FIGS. 11S and 11T show verification and confirmation screens similar to FIGS. 11D and 11E.

[0087] The illustrated screen guides placement of the wearable sensor 601 on the scalp along a path connecting the left ear to the right ear. This can facilitate accurate and easy-to-follow placement of the sensor on the scalp. In some cases, the system can guide placement of the wearable sensor 601 along a path connecting the right ear to the left ear.

[0088] Once the wearable sensors 601 are positioned and their location on the scalp is verified, the system can synchronize the sensors, as shown in FIG. 11U. Sensor synchronization is described in connection with FIGS. 10A-10C. The screen in FIG. 11U may be similar to the screen in FIG. 7J. After the sensors are synchronized, an EEG recording session can begin, as shown in FIG. 11V. The screen in FIG. 11V may be similar to the screens in FIGS. 7J-7K.

[0089] The placement of multiple wearable sensors 601 can follow a pattern, such as from left to right. The display can provide graphical instructions such as those shown in FIG. 7F. Emergency care screening may be performed on a patient using four wearable sensors 601, two on the forehead and two behind the ears. With this four-sensor placement, a desired montage can be created by subtracting the EEG signal from one sensor relative to another to create a 10-channel longitudinal-lateral montage, as described, for example, in U.S. Pat. No. 11,020,035 and U.S. Patent Publication No. 2021 / 0307672 (each of which is incorporated by reference in its entirety). The instructions can further cause the processor to activate the wearable sensors 601 and perform verification (such as an impedance test) to ensure the wearable sensors 601 are attached to the skin and have proper electrode contact. The impedance test can include pushing a current and measuring a voltage.

[0090] Recording data 730 may include recording EEG data. Recording data 730 may be initiated in response to a user input (such as a button press) on an application running on portable computing device 602. The application on portable computing device 602 may display a screen indicating that a recording session is in progress, such as the recording screen of FIG.

[0091] In some cases, recording data 730 includes determining the state of the wearable sensor 601. The state can include a standby state (on but not recording), a recording state, a charging state, a communication state, etc. The state information can include whether and when the sensor's internal clock was set, the number of records / pages of records, the battery charge state (fully charged, partially charged, etc.).

[0092] In some implementations, the instructions further cause the at least one processor to display a push notification on a display of the portable computing device 602. The push notification may be based on state information. The push notification may be based on a change in state.

[0093] The instructions may further cause the at least one processor to perform self-diagnostics 740 on a system including multiple wearable sensors 601. The self-diagnostics 740 may include identifying problems related to one or more wearable sensors 601, sensor data, and / or communication between the wearable sensors 601. The self-diagnostics 740 may include diagnosing the problem. In some cases, the problem includes a system problem. The system problem may include a battery problem, the wearable sensor 601 being disconnected, a connection timeout, poor electrode contact, a cellular signal error, a Bluetooth error, a portable computing device 602 Wi-Fi failure, a remote server or cloud server problem, or recording not starting. The problem may include a sensor / data problem. The sensor / data problem may include in-phase cancellation of electrographic activity (due to close spacing of electrodes), muscle artifact, or saturation.

[0094] Provided herein is a method for monitoring a patient's brain activity, the method comprising: receiving, by at least one processor of a portable computing device 602, a user's The method may include providing instructions for positioning a plurality of wearable sensors 601 at a plurality of locations on the scalp. The plurality of wearable sensors 601 may be configured to detect EEG signals indicative of a patient's brain activity, each wearable sensor 601 including at least two electrodes configured to monitor EEG signals when the wearable sensor 601 is positioned on the user's scalp and electronic circuitry configured to process the EEG signals monitored by the at least two electrodes. The method may further include providing an alert in response to detecting that the at least two wearable sensors 601 are positioned at particular locations among the plurality of locations on the user's scalp. The method may further include recording the processed EEG signals wirelessly transmitted by the plurality of wearable sensors 601 in response to verifying that the plurality of wearable sensors 601 are correctly positioned at the plurality of locations on the user's scalp.

[0095] Advantageously, guiding a user using the portable computing device 602 can enable EEG setup and monitoring by non-experts, such as clinicians in local or regional hospitals who are unfamiliar with EEG monitoring.

[0096] Handoff Control It may be advantageous to hand off control of the EEG sensor between computing devices, which may be portable. For example, the EEG sensor setup may be performed on a first portable computing device (e.g., a tablet) and then transferred to a second portable computing device (e.g., a watch, a smart band, smart jewelry, etc.). The second computing device (which may be referred to as the second portable computing device) may be a wearable computing device without a screen or with a screen smaller than that of the first computing device (which may be referred to as the first portable computing device). Generally, the second computing device may be smaller than the first computing device. The first portable computing device may be configured to facilitate activation and positioning of the EEG sensor on the patient's scalp, and the second portable computing device may be configured to facilitate monitoring of the patient's brain activity and detection of one or more disorders. Transferring control to the second portable computing device may advantageously enable EEG monitoring using smaller and less expensive user-worn computing devices.

[0097] Advantageously, handoff can facilitate EEG monitoring outside of a hospital or clinic, such as at home. This mode of operation can be referred to as an ambulatory mode. The second portable computing device can operate in a day mode when the user is active and in a night mode when the user is inactive. In the dark mode, notifications can be reduced or turned off (e.g., the display can be kept dark).

[0098] In some cases, the second portable computing device can include a display and can be configured to provide at least a portion of the instructions for activating and positioning the EEG sensor on the scalp. In some implementations, the second portable computing device may not include a display. The second portable computing device can function as a relay to forward EEG data received from the sensor to another computing device. For example, the second portable computing device can be a base station, a pack, etc. When the second portable computing device functions as a relay and instructions need to be provided to the user (e.g., for activating or positioning the sensor), such instructions can be provided on another device, such as via a companion application or app. In some cases, the second portable computing device may be omitted and the sensor may transmit data directly to another computing device.

[0099] In an ambulatory mode in which a second portable computing device (or any other computing device) is configured to receive EEG data from the sensor and relay the data to another computing device, care may need to be taken to conserve the power capacity of the second portable computing device. As described herein, the second portable computing device may be a small, wearable device, which may have limited power capacity. To preserve power capacity and facilitate continuous EEG monitoring, the second portable computing device may disconnect from the sensor and periodically reconnect to the sensor to retrieve recorded EEG data, which may be relayed to another computing device. For example, the periodic connection may be every 30 minutes or less, every hour or less, every two hours or less, etc. As described herein, after an EEG recording session is initiated, the sensor may continue to record EEG data regardless of the state of its connection to the second portable computing device (or any other computing device) until the EEG recording session ends (or one of the sensors runs out of power or memory space). When the connection with the second portable computing device is restored (after being lost), the second portable computing device can restore the state of the session and backfill gaps in the EEG data as described herein.

[0100] When the power source of the second portable computing device is being charged (e.g., by being connected to a charger), the second portable computing device can maintain an uninterrupted connection with the sensor to facilitate real-time or substantially real-time EEG monitoring.

[0101] The second portable computing device and the one or more EEG sensors can communicate directly or through another computing device, such as a telephone. The second portable computing device can communicate with a remote server or cloud server through another computing device or directly (such as with a cellular communication chip).

[0102] The first portable computing device can have prescription functionality to train, prescribe, provision, or otherwise determine how the EEG system is to be used when ambulatory worn. This can include parental controls, duration and location of wear, and other prescription functionality. The second portable computing device can have unique functionality, and its interaction with the patient will vary depending on the prescription and provisioning by the first portable computing device.

[0103] 8 is a diagram of an EEG sensor control and transfer environment 800. The sensor control and transfer environment 800 includes a plurality of wearable sensors 802 (which may be similar to sensors 101), a first portable computing device 832, and a second portable computing device 834 that may be configured to be worn by a patient. In the example of FIG. 8, the plurality of wearable sensors 802 and the first portable computing device 832 communicate to facilitate setup 810 of the plurality of wearable sensors 802. The first portable computing device 832 and the second portable computing device 834 communicate to facilitate handoff 810 of control of the plurality of sensors 802 from the first portable computing device 832 to the second portable computing device 834. 20. After handoff 820, the second portable computing device 834 communicates with the plurality of wearable sensors 802 to send and receive data 830. The data 830 may include sensor data, such as EEG measurements or sensor status, and may also include commands from the second portable computing device 834 to the plurality of sensors 802, such as to start or stop recording EEG data.

[0104] Provided herein is a method for monitoring brain activity. In some cases, the method includes activating (e.g., setting up 810) a plurality of wearable sensors 802 configured to detect EEG signals indicative of the patient's brain activity and positioned at a plurality of locations on the patient's scalp. Each wearable sensor 802 may have at least two electrodes configured to monitor EEG signals when the wearable sensor 802 is positioned on the patient's scalp, and electronic circuitry configured to process the EEG signals monitored by the at least two electrodes and wirelessly transmit the processed EEG signals to a first portable computing device 832. The activating may include following instructions displayed on a display of the first portable computing device 832 (e.g., setting up 810).

[0105] The method may further include transferring control (e.g., handoff 820) of the plurality of wearable sensors 802 to a second portable computing device 834 following activation of the plurality of wearable sensors 802. The second portable computing device 834 may be configured to be worn by the patient to enable the second portable computing device 834 to wirelessly receive the processed EEG signals (e.g., data 830). The second portable computing device may not include a display or may include a display that is smaller than the display of the first portable computing device 832.

[0106] The first portable computing device 832 can be configured to facilitate activation and positioning (e.g., setup 810) of the multiple wearable sensors 802 on the patient's scalp, and the second portable computing device 834 is configured to facilitate monitoring the patient's brain activity (e.g., receiving data 830) and detecting one or more disorders. Transferring control can cause the first portable computing device 832 to cease wirelessly receiving the processed EEG signals. The first portable computing device 832 can be a tablet, and the second portable computing device 834 can be a smartwatch.

[0107] The method may further include authenticating the second portable computing device 834 before transferring control to the second portable computing device 834. Authenticating the second portable computing device 834 may include scanning a QR code of the second portable computing device 834. For example, the first portable computing device 832 may prompt the user to use a camera of the first portable computing device 832 to scan a QR code displayed on the second portable computing device 834. The first portable computing device 832 may prompt the user to manually enter a code associated with the second portable computing device 834 (e.g., a code displayed on the second portable computing device 834).

[0108] The method further comprises: displaying a second portable computing device 834 displaying the ... In response to the indicated alert, the method may further include causing the second portable computing device 834 to display instructions for resolving the alert and following the instructions for resolving the alert.

[0109] FIG. 9A illustrates a process for data recording and sensor management that may be performed by the second portable computing device 834. The process is shown as a sequence of screens that may be displayed on the second portable computing device 834 (or played in other ways, e.g., audibly played by the second portable computing device). Through each screen, the system may display the next screen automatically or in response to user input; for example, the user may press a button (e.g., an on-screen virtual control or a physical button on the second portable computing device 834) to advance to the next screen showing the next instruction. The user may be the patient. The second portable computing device 834 may display a screen 916 indicating that a session of EEG data recording by the wearable sensor is in progress. The second portable computing device 834 may display an alert, e.g., an action required screen 910. The action required screen 910 may indicate that one or more actions are required, e.g., due to one or more detected problems. If multiple actions are required, the action required screen 910 may display a number representing the number of actions required based on the number of detected alerts. In some cases, auditory, visual, or tactile feedback by the second portable computing device 834 alerts the user that action is required. Auditory, visual, or tactile feedback on one or more wearable sensors 802 can alert the user that action is required.

[0110] An application display on the second portable computing device 834 may display specific information regarding one or more detected alerts. The specific information regarding the alerts may be displayed on the action request screen 910 automatically or in response to a user input (e.g., a tap). For example, the display may indicate that a signal emission has been detected (e.g., signal emission alert 912) or that a sensor has been disconnected (e.g., sensor disconnection alert 914). The signal emission alert 912 may indicate that insufficient electrode contact by one or more wearable sensors has been detected, which may be determined based on impedance, as described herein. The number of signal check attempts may be tracked (e.g., stored in memory), and an alert is generated in response to the number reaching a threshold (e.g., one, two, three, four, five, or more). The signal emission alert 912 may indicate which wearable sensor(s) 802 have a signal emission. The sensor disconnection alert 914 may indicate that one or more wearable sensor(s) 802 have stopped wireless communication with the second portable computing device 834. The system can wirelessly scan (e.g., using Bluetooth) the wearable sensor 802. The current sensor state and disconnection count can be tracked (e.g., stored in memory), and an alert is generated in response to the number reaching a threshold (e.g., 1, 2, 3, 4, 5, or more).

[0111] In response to user input (or automatically), the system may display instructions on how to troubleshoot or reconnect one or more wearable sensors 802. In response to user input (or automatically), a screen may be displayed that may instruct the user to verify whether the wearable sensors 802 are attached. In response to user input (or automatically), the signaling alert 912 or sensor disconnection alert 914 may be snoozed or dismissed. Dismissing or snoozing the signaling alert 912 or sensor disconnection alert 914 may be disabled. After a predetermined time has elapsed , the signal issuance alert 912 or sensor disconnection alert 914 can be automatically timed out and dismissed. In response to user input (or automatically), a replace attachment screen 918 can be displayed to provide instructions for troubleshooting the signal issuance alert 912 and sensor disconnection alert 914, as described further herein. After detecting an alert, the second portable computing device 834 can pause recording of EEG data when the alert is detected.

[0112] The instructions may further cause the at least one processor to display instructions corresponding to the self-diagnosed problem on a display of the first computing device 832 or the second portable computing device 834. For example, the instructions may include moving the wearable sensor 802, replacing an attachment (e.g., a screen 918 instructing the user to replace an attachment), charging a battery of the wearable sensor 802, charging a battery of the first portable computing device 832 or the second portable computing device 834, restarting the wearable sensor 802 or the first or second portable computing device 832, 834, etc.

[0113] Once the user completes the instructed steps, the alert can be dismissed and EEG data recording can resume. The second portable computing device 834 can display an in-session recording screen 916 once the alert is resolved. The recorded EEG data can be transmitted to a remote or cloud server. The remote or cloud server can combine and / or process the recorded data to determine the presence of one or more physiological conditions, such as seizures, heart rate, respiration, sweating, etc.

[0114] The instructions can be associated with replacing an attachment configured to removably attach a wearable sensor 802 of the plurality of wearable sensors 802 to a user's scalp. FIG. 9B is an example screen showing a process for instructing a user to replace an attachment. Through each screen, the system can display the next screen automatically or in response to user input; for example, the user may press a button (as described in connection with FIG. 9A) to advance to the next screen showing the next instruction. An alert screen 918 can instruct the user that the attachment should be replaced. In the event of a sensor malfunction, the system can display screen 922 instructing the user to remove the wearable sensor 802 from its position on the scalp.

[0115] The second portable computing device 834 may display a screen 920 prompting the user to confirm whether to proceed with the attachment change. The user may confirm by pressing a button (as described in connection with FIG. 9A ). In response to a user input canceling the attachment change (such as selecting a cancel user interface option) or in response to the passage of a predetermined time, the screen 920 may close. Automatically, or in response to a user input confirming the change proceeds, the system may display a screen 922 and instruct the user to remove the wearable sensor 802 from its position on the scalp. The second portable computing device 834 may instruct the wearable sensor 802 to enter a sleep state.

[0116] In response to the instruction to replace the attachment, the user can remove the wearable sensor 802, replace the attachment with another attachment, and reposition the wearable sensor 802 on the user's scalp. The second portable computing device 834 can instruct the user to remove the wearable sensor 802 from its position on the scalp. On the screen 922, for example, the second portable computing device The screen of the training device 834 displays a graphical representation of the location of the wearable sensor. The system can use known sensor locations (determined during setup, as described herein) to configure the screen to show a specific location. For example, as shown in screen 922, the system has detected a problem with the sensor positioned behind the left ear, and this location is displayed. Sensor location information can be stored in memory.

[0117] The second portable computing device 834 can instruct the user to clean the area at the indicated location on the scalp, for example, by displaying screen 924. The second portable computing device 834 can instruct the user to place a new attachment on the wearable sensor 802, for example, by displaying screen 926. The second portable computing device 834 can instruct the user to place the wearable sensor 802 at a location on the scalp, for example, by displaying screen 928. Screen 928 can include instructions for removing the second liner to expose the second adhesive surface of the attachment. The system can use known sensors / locations from memory to populate the screen showing the specific location. The second portable computing device 834 can instruct the user to activate or connect the placed wearable sensor 802, for example, by pressing a button on the placed wearable sensor 802, for example, by displaying screen 930. The second portable computing device 834 may instruct the user to wait, for example, by displaying screen 932 while the placement of the wearable sensor 802 on the scalp is verified. This may be done by testing for impedance, such as using the impedance test described herein. In some cases, the impedance is verified and the memory is updated with the impedance level. If the impedance test fails on the first attempt or a subsequent attempt (e.g., a second attempt), a poor electrode contact alert screen (not shown) may be displayed. If the impedance test fails on yet another subsequent attempt (e.g., a third attempt), a sensor failed - no retry screen (not shown) may be displayed. If the impedance is verified (the impedance test was successful), the process may be repeated if replacement of the additional wearable sensor 802 attachment is required.When the attachment change is complete for one or more wearable sensors 802, the second portable computing device 834 may notify the user that the change is complete, for example, by displaying screen 934. The screens shown in Figure 9B (or Figures 9C or 9D) may be displayed sequentially to address the issue of user error that may occur when one or more attachments are being changed.

[0118] Attachments may need to be replaced periodically, as described herein. The second portable computing device 834 can periodically instruct the user to replace one or more attachments, which can be done by displaying instructions. FIG. 9C is an illustration of a process for guiding a user through replacing one or more attachments. In some cases, through each screen, the system displays the next screen automatically or in response to user input; for example, the user can press a button (on the screen display or on a physical button on the second portable computing device 834) to advance to the next screen showing the next instruction. In some examples, an application running on the second portable computing device 834 alerts the user to replace one or more attachments. Alerts may be provided periodically, such as every 6 hours or less, 12 hours, 18 hours, 24 hours, 30 hours, 36 hours, 42 hours, 48 ​​hours, 54 hours, 60 hours, 66 hours, or 72 hours, 4 days, 5 days, 6 days, or 7 days or more, or any value therebetween, or any range constructed from any of the above values ​​or any value therebetween. The process may be initiated by a user desiring to replace one or more attachments. In step 941, the user changes (replaces) one or more attachments (e.g., including all attachments). The application may display several screens on the second portable computing device 834 to guide the user through the attachment replacement. The application may request user input regarding whether one or all attachments are to be replaced. In some implementations, an option may be provided to replace two or more but fewer than all attachments. In some cases, in response to user input (or automatically), a process is initiated to indicate the replacement of only one attachment. In screen 942, a diagram of the locations of the wearable sensors 802 may be displayed, allowing the user to input a selection of which wearable sensors 802 attachments should be replaced. Only some wearable sensors 802, e.g., only wearable sensors 802 that are currently active (or connected) and / or in use, may be displayed or enabled for selection by the user. A display (not shown) may prompt the user to confirm the selection of the wearable sensor 802 whose attachment is being replaced. The second portable computing device 834 may command the selected wearable sensor 802 to enter a sleep state.

[0119] In screen 944, the user is instructed to remove the selected wearable sensor 802 from its position on the scalp. In the example of screen 944, the screen of the second portable computing device 834 displays a graphical representation of the position of the wearable sensor 802. In screen 924, the user is instructed to clean the area where the sticker was placed on the scalp. In screen 926, the user is instructed to place a new attachment (adhesive sticker) on the wearable sensor 802. Additional screens described in connection with FIG. 9B can then be displayed. The process may be repeated in sequence to replace attachments for one or more additional wearable sensors 802. For example, the process can be repeated through screens 942, 944, 924, 926, etc. for each additional wearable sensor 802. As another example, the user can select attachments for multiple wearable sensors 802 for replacement in screen 942, and the process can be repeated through screens 944, 924, 926, etc. for each selected wearable sensor. In some cases, the user cannot select the next sensor until the current sensor has been swapped out.

[0120] In some cases, before instructing the user to remove the selected wearable sensor 802 (or any other EEG sensor described herein) from the scalp, the wearable sensor 802 may be powered down or placed into sleep mode to prevent damage to the wearable sensor 802 (e.g., due to electrostatic discharge) during sticker replacement. This may be accomplished by sending a command to the wearable sensor 802. The command may instruct the wearable sensor 802 to stop recording EEG data and enter sleep mode. As described herein, in ambulatory mode, the second portable computing device 834 may disconnect from the sensor and periodically reconnect to the sensor. In such an example, the second portable computing device 834 may need to reconnect to the selected wearable sensor 802 following selection of the sensor on screen 942. There may be an additional screen (not shown) between screens 942 and 944 indicating that a connection has been established (e.g., "Waiting to Reconnect"). A similar additional screen may be displayed before screen 950 of FIG. 9D .

[0121] FIG. 9D is a diagram of a process for guiding a user through changing all attachments. In some cases, all attachments refer to all adhesive attachments for all wearable sensors 802 currently in use. In some examples, the process of FIG. 9D can be performed automatically. An application running on the second portable computing device 834 can alert the user to replace all of the attachments. Attachments may have a limited wear time, and alerts can be provided periodically, such as every 6 hours or less, 12 hours, 18 hours, 24 hours, 30 hours, 36 hours, 42 hours, 48 ​​hours, 54 hours, 60 hours, 66 hours, or 72 hours, 4 days, 5 days, 6 days, or 7 days or more, or any value therebetween, or a range constructed from any of the above values ​​or any value therebetween. In some cases, because replacing all attachments may take time, the process can display a screen (e.g., "Are you ready to replace all attachments?") for the user to confirm they are ready to replace all attachments. On display 950, the user may be instructed to remove each of the plurality of wearable sensors 802 from its respective location on the scalp. On display 952, the user may be instructed to remove all attachments from each of the plurality of wearable sensors 802. On display 954, the user may be instructed to clean all areas on the scalp for placement of each of the plurality of wearable sensors 802. On display 956, the user may be instructed to place a new attachment on each of the plurality of wearable sensors 802. Additional screens similar to those described in connection with FIG. 9B may then be displayed (e.g., screens 928, 930, 932, 934). These screens may be displayed sequentially to address possible user error issues. In some cases, the user may not be able to select the next sensor until the current sensor's attachment change is complete.

[0122] Following replacement of all wearable sensor 802 attachments, the sensors can be synchronized as described herein, which can remove any clock misalignment or drift, as described herein.

[0123] In certain implementations, a user can create a custom workflow for replacing one or more attachments.

[0124] Provided herein is a system for monitoring brain activity. The system may include a plurality of wearable sensors 802 configured to detect EEG signals indicative of a user's brain activity. Each wearable sensor 802 may include at least two electrodes configured to monitor the EEG signals when the wearable sensor 802 is positioned on the user's scalp, and electronic circuitry configured to process the EEG signals monitored by the at least two electrodes and wirelessly transmit the processed EEG signals to a first portable computing device 832.

[0125] The system may further include a first non-transitory computer-readable medium storing executable instructions that, when executed by at least one processor of the first portable computing device 832, cause the at least one processor of the first portable computing device 832 to facilitate activation of the plurality of wearable sensors 802 by displaying instructions on a display of the first portable computing device 832. The executable instructions may further cause the at least one processor of the first portable computing device 832, following activation of the plurality of wearable sensors 802, to transfer control of the plurality of wearable sensors 802 to a second portable computing device 834, the second portable computing device 834 being configured to be worn by a user, to transfer the processed EEG signals The second portable computing device 834 may be configured to facilitate activating and positioning the plurality of wearable sensors 802 on the user's scalp, and the second portable computing device 834 may be configured to facilitate monitoring the user's brain activity and detecting one or more disorders. The second portable computing device 834 may not include a display or may include a display that is smaller than the display of the first portable computing device 834. The first portable computing device 834 may be configured to facilitate activating and positioning the plurality of wearable sensors 802 on the user's scalp, and the second portable computing device 834 is configured to facilitate monitoring the user's brain activity and detecting one or more disorders.

[0126] The first portable computing device 832 may be a tablet, and the second portable computing device 834 may be a smartwatch. The executable instructions may further cause at least one processor of the first portable computing device 832 to authenticate the second portable computing device 834 before transferring control to the second portable computing device 834. Authenticating the second portable computing device 834 may include scanning a QR code of the second portable computing device 834.

[0127] The system may further include a second non-transitory computer-readable medium storing executable instructions that, when executed by the at least one processor of the second portable computing device 834, cause the at least one processor of the second portable computing device 834 to display an alert on a display of the second portable computing device 834. The executable instructions may further cause the at least one processor of the second portable computing device 834 to display instructions for resolving the alert on a display of the second portable computing device 834. The executable instructions may further cause the at least one processor of the second portable computing device 834 to pause collection of processed EEG signals.

[0128] The executable instructions may cause at least one processor of the second portable computing device 834 to detect and display an alert in response to determining that the impedance of at least one wearable sensor of the plurality of wearable sensors does not meet an impedance threshold. For example, signaling alert 912 in FIG. 9A is a display of an alert on a display of the second portable computing device 834 related to an impedance issue. The instructions may be associated with replacing an attachment configured to removably attach at least one wearable sensor 802 to a user's scalp. The instructions may include removing the at least one wearable sensor 802, replacing the attachment with another attachment, and repositioning the at least one wearable sensor 802 on the user's scalp. The executable instructions may further cause the at least one processor of the second portable computing device 834 to resume collecting processed EEG signals in response to verifying the impedance of the at least one wearable sensor 802 after it has been repositioned on the user's scalp. Verifying the impedance of the at least one wearable sensor 802 may include determining that the impedance of the at least one wearable sensor 802 meets an impedance threshold. Execution of the executable instructions may facilitate selecting at least one wearable sensor 802 from the plurality of wearable sensors 802. For example, execution of the executable instructions may cause a location of the at least one wearable sensor 802 on the user's scalp to be displayed.

[0129] The executable instructions may be stored in at least one of the second portable computing device 834. The processor may be caused to display an alert in response to the passage of a duration since replacement of a plurality of attachments configured to removably attach the plurality of wearable sensors 802 to the user's scalp, where the duration may be 6 hours or less, 12 hours, 18 hours, 24 hours, 30 hours, 36 hours, 42 hours, 48 ​​hours, 54 hours, 60 hours, 66 hours, or 72 hours, 4 days, 5 days, 6 days, or 7 days or more, or any value therebetween, or a range constructed from any of the foregoing values ​​or any values ​​therebetween.

[0130] The system may further include a second non-transitory computer-readable medium storing executable instructions that, when executed by at least one processor of the second portable computing device 834, cause the at least one processor of the second portable computing device 834 to display instructions for confirming the occurrence of a seizure in response to detecting a possible seizure.

[0131] As described herein, the wearable sensor 802 can monitor EEG signals for detection of one or more physiological conditions, such as seizures. The EEG data can be processed by one or more recognition techniques, such as machine learning techniques, to detect seizures. To improve detection (e.g., to train the one or more recognition techniques), it may be advantageous to have a user confirm the occurrence of a possible seizure if it was correctly detected. FIG. 9E displays a process for confirming the occurrence of a seizure to a user. An in-session recording screen 916 indicates that an EEG recording is in session.

[0132] Automatically, or in response to user input (such as pressing a button as described in connection with FIG. 9A ), the second portable computing device 834 may display a log events screen 960. The second portable computing device 834 may display a screen (such as the log events screen 960) that prompts the user to indicate whether a seizure has just occurred. The user may select yes or no (a seizure has or has not just occurred) by, for example, pressing a button (as described in connection with FIG. 9A ).

[0133] If the user inputs that a seizure occurred, the second portable computing device 834 may add a record of the event to its memory. If the user inputs that a seizure did not occur, the second portable computing device 834 may not add a record of the event to its memory. If the user inputs that a seizure occurred, the second portable computing device 834 may display a confirm event screen 962. The second portable computing device 834 may automatically display the confirm event screen 962 after a predetermined time (e.g., 30 seconds) has elapsed since the log event screen 960 was opened. The confirm event screen 962 may indicate to the user that an event indicating the occurrence of a seizure has been recorded. The in-session record screen 916 may be displayed again in response to a user input or after another predetermined time has elapsed since the confirm event screen 962 was displayed.

[0134] In some cases, wireless scanning (e.g., Bluetooth scanning) is stopped during a recording session. Wireless scanning can be restarted if a wearable sensor 802 disconnects. Real-time data notification can be enabled for all wearable sensors 802. When an EEG recording session is in progress, the second portable computing device 834 can receive messages containing real-time data / events from multiple wearable sensors 802 and communicate the messages containing the real-time data / events to a remote server or cloud server via the Internet. A session end message can be communicated to the remote server or cloud server. In response to user input (or automatically), the second portable computing device The operating device 834 may display an options screen (not shown) or a parent lockout screen (not shown).

[0135] Once an EEG recording session is initiated, any of the wearable sensors 802 can record EEG data until instructed to stop recording (such as with a stop command sent by the portable computing device 832 or 834) or until the wearable sensor 802 runs out of power or memory space. As described herein, the wearable sensor 802 can transmit EEG data to the first portable computing device 832 or the second portable computing device 834. If connection with the portable computing device 832 or 834 is lost (e.g., due to connection issues or loss of power by the portable computing device), any of the wearable sensors 802 continues to record EEG data as described herein. After connection is restored, the portable computing device 832 or 834 can restore the state of the session and backfill any gaps in the EEG data. Such backfilling can be performed as a result of requesting and receiving EEG data recorded by any of the wearable sensors 802 while connection was lost. Backfilling can be facilitated by time-stamping of the EEG data, as described herein. Similar functionality can be implemented if the connection between the portable computing device 832 or 834 and the remote server or cloud device is lost.

[0136] Synchronization of independent wireless EEG sensors Each EEG sensor of the multiple EEG sensors can independently monitor and collect EEG signals without communicating with the other EEG sensors. The collected EEG signals can be wirelessly transmitted to one or more portable computing devices for processing, which can include collating (or integrating, aligning, or synchronizing) and analyzing the EEG signals to determine the occurrence of one or more physiological conditions. At least a portion of the processing can be performed by a remote computing device. To ensure proper processing, it can be advantageous to synchronize one or more of the collection or transmission of EEG signals by the multiple sensors.

[0137] Provided herein are methods and systems for synchronized monitoring of brain activity by multiple independent EEG sensors configured to detect EEG signals indicative of brain activity of a user (e.g., a patient). Each sensor can be configured to detect EEG signals independently of the other sensors and may not be in communication with the other sensors.

[0138] Each EEG sensor may include at least two electrodes configured to monitor EEG signals when the EEG sensor is positioned on a user's scalp. Each EEG sensor may further include electronic circuitry configured to process the EEG signals monitored by the at least two electrodes based on the signals detected by the at least two electrodes and wirelessly transmit data related to the user's brain activity to one or more portable computing devices.

[0139] The system may further include a non-transitory computer-readable medium storing executable instructions that, when executed by at least one processor of the one or more portable computing devices, cause the at least one processor to wirelessly transmit a first message to the plurality of EEG sensors to listen for a second message. The executable instructions may cause the at least one processor to, subsequent to transmitting the first message, wirelessly transmit a second message to the plurality of EEG sensors, the second message including timing information. Transmission of the second message may be performed by transmitting a second message to the electronic circuit of each EEG sensor. The circuit can have an internal clock set to substantially coincide with the internal clocks of the other EEG sensors, the internal clock being used to timestamp recorded signals indicative of the user's brain activity. Data determined by each EEG wearable sensor can be correlated with data determined by the EEG wearable sensor within a range of about 10 ms or less, 20 ms, 30 ms, 40 ms, 50 ms or more, etc., or within a range consisting of any of the above values.

[0140] In some cases, none of the EEG sensors communicate with another EEG sensor. The executable instructions may further cause the at least one processor to verify that the EEG sensor has set its internal clock following wirelessly transmitting the second message. The executable instructions may further cause the at least one processor to verify that the processed EEG signals received from each EEG sensor correlate with the processed EEG signals determined by the other EEG sensors of the plurality of wearable sensors (e.g., within a range of approximately 10 ms or less, 20 ms, 30 ms, 40 ms, 50 ms or more, etc., or within a range consisting of any of the aforementioned values). The executable instructions may further cause the at least one processor to transmit the processed EEG signals received from the plurality of EEG sensors to a remote computing device in response to the verification.

[0141] The executable instructions may further cause the at least one processor to poll the plurality of EEG sensors for their internal clocks. The executable instructions may further cause the at least one processor to repeat wireless transmission of the first and second messages to set the internal clock of the electronic circuitry of the at least one EEG sensor in response to detecting that a difference between the internal clock of the at least one EEG sensor and an expected internal clock satisfies a threshold. The threshold may be equal to or less than approximately 10 ms, 20 ms, 50 ms, 75 ms, 90 ms, 100 ms, or 200 ms, or within a range constructed from any of the above values, and may depend on clock synchronization specifications. For example, a threshold having a higher value is used to monitor physiological signals that change less frequently. Monitoring such signals may be performed even when the internal clocks are not synchronized very precisely. As another example, a threshold having a lower value is used to monitor physiological signals that change more frequently. Monitoring such signals may require greater precision in synchronization of the internal clocks.

[0142] Provided herein is a method for synchronous monitoring of brain activity. The method can include wirelessly transmitting a first message to a plurality of EEG sensors configured to detect EEG signals indicative of brain activity of a user (e.g., a patient). Each EEG sensor can include at least two electrodes configured to monitor the EEG signals when the EEG sensor is positioned on the user's scalp. Each EEG sensor can include electronic circuitry configured to determine data related to the user's brain activity based on signals detected by the at least two electrodes.

[0143] The method may further include, following the first message, wirelessly transmitting a second message to the plurality of EEG sensors. The second message may include timing information. The transmission of the second message may cause the electronic circuitry of each EEG sensor to set an internal clock to substantially match the internal clocks of the other EEG sensors in the set of activated sensors for the sensor session, for example. The internal clock may be used to timestamp recorded signals indicative of the user's brain activity.

[0144] The method includes wirelessly receiving processed EEG signals from a plurality of EEG sensors, and determining whether the processed EEG signals received from each EEG sensor are consistent with the other EEG sensors. It may further include verifying that it correlates with the processed EEG signal (e.g., within a range of about 10 ms or less, 20 ms, 30 ms, 40 ms, 50 ms or more, etc., or within a range constructed from any of the above values).

[0145] The method may further include, in response to the verification, transmitting the processed EEG signals received from the EEG sensors to a remote computing device. The remote computing device may be a portable computing device as described herein. In some cases, none of the EEG sensors communicates with another EEG sensor. The method may include verifying that the processed EEG signals received from each EEG sensor correlate with the processed EEG signals determined by the other EEG sensors (e.g., within a range of about 10 ms or less, 20 ms, 30 ms, 40 ms, 50 ms or more, etc., or within a range constructed from any of the above values).

[0146] The method may further include verifying that the plurality of EEG sensors have set their internal clocks. The method may further include polling the plurality of EEG sensors for their internal clocks. In response to detecting a difference between the internal clock of at least one EEG sensor and an expected internal clock, or the difference meeting a threshold, the method may further include repeating the wireless transmission of the first and second messages to cause the electronic circuitry of the at least one EEG sensor to set its internal clock. As described herein, the expected internal clock may correspond to clock value information or values ​​provided by the portable computing device. In this manner, any unacceptable clock misalignment or drift can be detected and corrected.

[0147] FIG. 10A illustrates a method for synchronizing sensor data from multiple independent EEG sensors. The method can be performed by a portable computing device, such as any of the portable computing devices 602. In step 1010, a first message is sent to each EEG sensor to cause the EEG sensor to listen (or transition to a listening state). The first message can be a command sent from the portable computing device. The first message can be a directed message sent individually to each EEG sensor. In some cases, listening is a state of scanning and waiting for a second command (or second message) that includes clock information or a value (such as a timestamp) for synchronizing the EEG sensor's internal clock. The second message can be sent as an advertising (or advertisement) message using, for example, the BLE protocol. BLE mesh capabilities can be used. The second message can be a single message broadcast to all EEG sensors (as compared to a first message sent directly to each EEG sensor). The reason for sending the first and second messages may be that the first message causes the EEG sensor to enter a listening state and look for a broadcast message to be received by the EEG sensor at the same time.

[0148] In some cases, different wireless communication protocols can be used, such as WiFi, NFC, RFID, etc. For protocols that support direct broadcasting to EEG sensors (such as WiFi, which supports direct broadcasting to all devices on a subnet), it is sufficient to send a single broadcast message to all EEG devices. The broadcast message can include clock information, which can be a timestamp.

[0149] In step 1020, a second message may be sent to each EEG sensor to synchronize the internal clocks of the EEG sensors. The second message may be a command to set a clock to the clock (or some other clock value) of the portable device. Thus, the second message may include clock information or a value. As described herein, each of the multiple individual sensors may simultaneously receive the second message. In this manner, the internal clocks of the EEG sensors are set to approximately the same clock value (which may be the clock value included in the second message), and as described herein, the EEG data may be transmitted by the EEG sensors with synchronized internal clock values, resulting in synchronized processing of the EEG data received from the EEG sensors.

[0150] After all EEG sensors receive and process the second message, each EEG sensor can set its internal clock to the same time setting (specified by the clock information in the second message) within a desired tolerance (e.g., approximately 10 ms or less, 20 ms, 30 ms, 40 ms, 50 ms or more, etc., or within a range consisting of any of the above values). Each individual EEG sensor can record EEG data with a timestamp derived from its internal clock. EEG data packets from the EEG sensors can be transmitted independently, possibly at different times, to the portable computing device. The portable computing device can combine data from multiple EEG sensors based on the timestamps from the individual EEG sensors.

[0151] In some cases, if the EEG sensor does not receive the first command or the second command and does not set its internal clock (as described herein), when the EEG sensor attempts to reconnect with the portable computing device, the portable computing device will recognize that the sensor has not synchronized its internal clock. The portable computing device can then resume (or repeat) the synchronization process of FIG. 10A .

[0152] In some implementations, the synchronization process of FIG. 10A can be resumed (or repeated) in response to the portable computing device detecting that the internal clock of at least one EEG sensor differs from an expected internal clock, which may correspond to clock value information or values ​​provided by the portable computing device. The portable computing device can repeat transmitting clock information or values ​​to all EEG sensors or to only at least one EEG sensor. For example, in response to receiving the second message, each of the EEG sensors can set its internal clock to the clock value transmitted in the second message or time out and set its internal clock to a default (or known) invalid clock value. Each of the EEG sensors can then report its internal clock value to the portable computing device. If the portable computing device determines that any of the EEG sensors failed to set their internal clock to a clock value (instead, set their internal clock to an invalid clock value), the synchronization process of FIG. 10A can be resumed or repeated. As a result, for example, in an environment with electromagnetic interference, it may take several retries to synchronize the internal clocks of the EEG sensors.

[0153] The synchronization process of FIG. 10A can be repeated periodically to resynchronize the internal clocks of the EEG sensors.

[0154] In some implementations, synchronization of the internal clock of the EEG sensor (such as the process of FIG. 10A) can be implemented by transmitting multiple second messages. Referring to FIG. 10B, following transmitting the first message in step 1010, a series of second messages 1022, 1024, and 1026 are transmitted to the EEG sensor. Although three second messages are shown being transmitted, the number of second messages in the series of second messages can generally be two or more second messages. The second messages can be transmitted periodically with a specific fixed delay (or one or more variable delays) between adjacent second messages. The first second message 1022 in the series of second messages can include clock information or values, as described above. Subsequent second messages in the series (such as second messages 1024 and 1026) can include clock information or values ​​adjusted by the delay from the transmission of the first second message 1022. For example, assume the first second message includes a clock value of 10 time units and the fixed delay between second messages is 5 time units. The clock value included in second message 1024 is 15, and the clock value included in second message 1026 is 20.

[0155] Under this approach, any particular EEG sensor has multiple opportunities to receive and process at least one second message in the series of second messages and synchronize its internal clock value based on the clock value included in the at least one second message. Automatically transmitting the series of second messages 1022, 1024, and 1026 can increase the likelihood that all EEG sensors will synchronize their internal clocks, even in environments with electromagnetic interference. Advantageously, as described herein, the need to restart or repeat the process of FIG. 10A can be avoided.

[0156] In some examples, the process of FIG. 10B can be repeated periodically to resynchronize the internal clocks of the EEG sensors. In some implementations, synchronizing the internal clocks of the EEG sensors can be performed as follows: Each EEG sensor can process electrical stimuli generated by another EEG sensor and sensed by at least two electrodes and record the electrical stimuli along with data related to the user's brain activity. Recording the electrical stimuli facilitates combining and processing data related to the user's brain activity collected by multiple EEG sensors. As shown in FIG. 10C , in step 1030, the EEG sensor can stimulate the skin by applying an electrical signal using the electrodes. For example, the EEG sensor can send a signal (such as rail power through one of the electrodes) that stimulates the skin and creates an electrical tap. In step 1040, the other EEG sensor can sense the tap through the skin to synchronize the sensors. Rather than synchronizing clocks, the EEG data can be synchronized by including information in the data indicating that the tap was applied (for the EEG sensor applying the tap) and sensed (for the other EEG sensors). Thus, EEG data from different EEG sensors can be combined and aligned by using information related to the taps. Synchronization can be initiated by the portable computing device receiving the data packets containing the tap information.

[0157] In some cases, synchronization can be performed as follows: A recordable event (such as a ping or an instruction to generate a stimulus) can be provided to one of the EEG sensors via a portable computing device. The recordable event can be relayed by the EEG sensor to the other EEG sensors and recorded by each of the EEG sensors. The data can later be synchronized using techniques described in connection with FIG. 10C.

[0158] Although specific examples have been described in the context of timestamps, other techniques for time ordering may be used, for example, sequence numbers may be used instead of timestamps.

[0159] Additional Examples Example 1: A system for monitoring brain activity, comprising: a plurality of wearable sensors configured to record brain activity of a user, each wearable sensor comprising: a housing; at least two electrodes positioned on an exterior surface of the housing and configured to detect electroencephalogram (EEG) signals indicative of brain activity of the user when the wearable sensor is positioned on the user's scalp; an electronic circuit supported by the housing and configured to process the EEG signals detected by the at least two electrodes; and a power source supported by the housing and configured to provide power to the electronic circuit, wherein the housing has an extended, rounded shape; a plurality of attachments, each attachment shaped to substantially conform to the expanded, rounded shape and including a first side configured to be attached to an outer surface of a housing of the wearable sensor, and a second side configured to removably position the wearable sensor on a user's scalp, wherein the number of attachments in the plurality of attachments exceeds the number of wearable sensors in the plurality of wearable sensors.

[0160] Example 2: The system of any one of the preceding examples, further comprising a charger comprising a charger housing configured to receive a power source and simultaneously charge at least two wearable sensors of the plurality of wearable sensors.

[0161] Example 3: The system of any one of the preceding examples, wherein the extended, rounded shape of the housing is configured to fit around the user's hair, thereby facilitating unobtrusive placement of the wearable sensor on the user's scalp while facilitating collection of EEG signals.

[0162] Example 4: The system of example 3, wherein the housing includes a first portion having a first thickness and a second portion having a second thickness greater than the first thickness.

[0163] Example 5: The system of any one of the preceding examples, wherein the surface area of ​​the housing is between 16.0 cm and 10 cm.

[0164] Example 6: The system of any one of the preceding examples, wherein the volume of the housing is between 5.0 cm3 and 3.0 cm3.

[0165] Example 7: The system of any one of the preceding examples, wherein the number of attachments among the plurality of attachments includes the number of wearable sensors among the plurality of wearable sensors multiplied by the number of days the plurality of wearable sensors are configured to record the user's brain activity.

[0166] Example 8: The system of any one of the preceding examples, wherein the first side of each attachment is configured to attach to a bottom surface of the housing.

[0167] Example 9: The system of any one of the preceding examples, wherein each attachment of the plurality of attachments comprises a hydrocolloid material on a second side of the attachment, the hydrocolloid material facilitating repositioning of the wearable sensor on the user's scalp.

[0168] Example 10: Each attachment is a first layer comprising a thermoplastic resin; a second layer comprising a cured hydrogel; a third layer containing an adhesive; a fourth layer comprising a nonwoven fabric; a fifth layer comprising an adhesive; or A sixth layer containing a thermoplastic resin 10. The system of any one of the preceding embodiments, comprising a plurality of layers including one or more of:

[0169] Example 11: The system of Example 10, wherein the thermoplastic resin comprises PET.

[0170] Example 12: The system of any one of Examples 10-11, wherein two or more of the first, second, third, fourth, fifth, or sixth layers are laminated to one another such that the cured hydrogel is disposed between the first layer and the third layer.

[0171] Example 13: The system of any one of Examples 10-12, wherein the third and fifth layers form an opening, and one or more of the third layer, fourth layer, or fifth layer comprises a hardened hydrogel.

[0172] Example 14: The system of example 13, wherein the opening is aligned with at least two electrodes of the wearable sensor.

[0173] Example 15: An integrated wireless wearable sensor configured to monitor brain activity, comprising: a housing having an enlarged, rounded shape configured to fit around a user's hairline; at least two electrodes positioned on an exterior surface of the housing and configured to detect electroencephalogram (EEG) signals indicative of the user's brain activity when the housing is positioned on the user's scalp; an electronic circuit supported by the housing and configured to process EEG signals detected by the at least two electrodes and wirelessly communicate the processed EEG signals to a remote computing device; The extended, rounded shape of the housing facilitates unobtrusive wearing of the housing on the user's scalp while facilitating the collection of EEG signals from the sensor.

[0174] Example 16: The sensor of Example 15, wherein the housing comprises a first portion having a first thickness and a second portion having a second thickness greater than the first thickness.

[0175] Example 17: The sensor according to any one of Examples 15 to 16, wherein the surface area of ​​the housing is 16.0 cm 2 to 10 cm 2 .

[0176] Example 18: The sensor according to any one of Examples 15 to 17, wherein the volume of the housing is 5.0 cm 3 to 3.0 cm 3 .

[0177] Example 19: A kit comprising a plurality of sensors of any of Examples 15-18, wherein each sensor is configured to detect electroencephalogram (EEG) signals independently of the other sensors.

[0178] Example 20: A method of using a sensor in a wearable device, further comprising a plurality of attachments, each attachment shaped to substantially conform to the expanded rounded shape and including a first side configured to be attached to an outer surface of a housing of a sensor of the plurality of sensors, and a second side configured to removably position the sensor on a scalp of a user, wherein the number of attachments of the plurality of attachments exceeds the number of sensors of the plurality of sensors. The kit described in Example 19.

[0179] Example 21: The kit of Example 20, wherein the number of attachments of the plurality of attachments comprises the number of sensors of the plurality of sensors multiplied by the number of days the plurality of sensors is configured to record the user's brain activity.

[0180] Example 22: A system for monitoring brain activity, comprising: 1. A plurality of integrated wireless wearable sensors configured to record brain activity of a user, each sensor comprising: a housing having an enlarged, rounded shape configured to fit around a user's hairline; at least two electrodes positioned on an exterior surface of the housing and configured to detect electroencephalogram (EEG) signals indicative of the user's brain activity when the housing is placed on the user's scalp; an electronic circuit supported by the housing and configured to process EEG signals detected by the at least two electrodes and wirelessly communicate the processed EEG signals to a remote computing device; The extended, rounded shape of the housing facilitates discreet wearing of the housing on the user's scalp while facilitating the collection of EEG signals, and a plurality of attachments, each attachment shaped to substantially conform to the expanded, rounded shape and including a first side configured to be attached to an exterior surface of a housing of the sensor and a second side configured to removably position the sensor on a user's scalp, wherein the number of attachments in the plurality of attachments exceeds the number of sensors in the plurality of sensors.

[0181] Example 23: A method for monitoring brain activity, comprising: removing at least one wearable sensor of a plurality of wearable sensors configured to record brain activity of a user, each wearable sensor comprising: a housing having an enlarged, rounded shape; and at least two electrodes positioned on an exterior surface of the housing and configured to detect electroencephalogram (EEG) signals indicative of brain activity of the user; attaching a first attachment of the plurality of attachments to a second attachment of the plurality of attachments, the first and second attachments being shaped to substantially conform to the expanded rounded shape and including a first side configured to be attached to an outer surface of a housing of the at least one wearable sensor and a second side configured to removably position the at least one wearable sensor on a scalp of a user, wherein the number of attachments of the plurality of attachments exceeds the number of wearable sensors of the plurality of wearable sensors; reattaching the at least one sensor to the user's scalp by adhering a second side of the second attachment to the user's scalp; and resuming recording of EEG signals indicative of the user's brain activity.

[0182] Example 24: A system for monitoring brain activity, comprising: a plurality of wearable sensors configured to detect electroencephalogram (EEG) signals indicative of a user's brain activity, each wearable sensor comprising at least two electrodes configured to monitor EEG signals when the wearable sensor is positioned on the user's scalp, and electronic circuitry configured to process the EEG signals monitored by the at least two electrodes; a non-transitory computer-readable medium storing executable instructions that, when executed by at least one processor of the portable computing device, cause the at least one processor to: positioning a wearable sensor of the plurality of wearable sensors at a location of the plurality of locations on the scalp of the user and providing instructions to activate the wearable sensor; Verify the identity of the wearable sensor; In response to verifying the identity of the wearable sensor, verifying the impedance of the wearable sensor; In response to verifying the impedance of the wearable sensor, the system provides instructions for locating and activating another wearable sensor of the plurality of wearable sensors to perform identification and impedance verification of the other wearable sensor.

[0183] Example 25: The system described in Example 24, wherein the executable instructions further cause at least one processor to sequentially provide instructions for positioning and activating, verifying identity, and verifying impedance of each wearable sensor of the plurality of wearable sensors.

[0184] Example 26: The system described in Example 25, wherein the executable instructions further cause at least one processor to record processed EEG signals wirelessly transmitted by the plurality of wearable sensors in response to verifying the identification and impedance of each wearable sensor of the plurality of wearable sensors.

[0185] Example 27: The system described in any one of Examples 24 to 26, wherein the executable instructions further cause at least one processor to repeat providing instructions, verifying identification, and verifying impedance of the wearable sensor in response to not verifying that the impedance of the wearable sensor meets the impedance threshold.

[0186] Example 28: The system described in Example 27, wherein the executable instructions further cause at least one processor to resume providing instructions, verifying identification, and verifying impedance of the wearable sensor in response to not verifying the impedance of the wearable sensor a second time.

[0187] Example 29: The system described in any one of Examples 24 to 28, wherein the executable instructions further cause at least one processor to provide an alert in response to detecting that at least two wearable sensors of the plurality of wearable sensors have been activated to position at a location among a plurality of locations on the user's scalp.

[0188] Example 30: The system described in Example 29, wherein the executable instructions further cause the processor to resume providing instructions, verifying identification, and verifying impedance for the plurality of wearable sensors in response to detecting that at least two wearable sensors of the plurality of wearable sensors have been activated for positioning at specific locations of the plurality of locations on the user's scalp.

[0189] Example 31: The system described in Example 30, wherein detecting that at least two wearable sensors have been activated to position at a particular location includes detecting that multiple sensors have been activated substantially simultaneously.

[0190] Example 32: A system described in any one of Examples 24 to 31, wherein providing instructions for positioning the wearable sensor includes displaying the instructions on a screen of the portable computing device.

[0191] Example 33: The system described in Example 32, wherein providing instructions for positioning the wearable sensor includes displaying the location on a screen of the portable computing device and instructions for activating the wearable sensor.

[0192] Example 34: A system described in any one of Examples 24 to 33, wherein the executable instructions further cause at least one processor to provide instructions for scanning or inputting identification for the wearable sensor before providing instructions for positioning the wearable sensor at a location on the user's scalp.

[0193] Example 35: A system described in any one of Examples 24 to 34, wherein providing instructions for positioning the wearable sensor at a location on the user's scalp includes instructing the use of multiple attachments configured to removably attach the wearable sensor to the user's scalp.

[0194] Example 36: A method for monitoring brain activity, comprising: by at least one processor of the portable computing device, positioning one wearable sensor of a plurality of wearable sensors at one of a plurality of locations on a scalp of a user and providing instructions to activate the wearable sensor, the plurality of wearable sensors being configured to detect electroencephalogram (EEG) signals indicative of brain activity of the user, each wearable sensor comprising at least two electrodes configured to monitor the EEG signals when the wearable sensor is positioned on the scalp of the user, and electronic circuitry configured to process the EEG signals monitored by the at least two electrodes; Verifying the identity of the wearable sensor; verifying an impedance of the wearable sensor in response to verifying the identity of the wearable sensor; and providing instructions to, in response to verifying the impedance of the wearable sensor, position and activate another wearable sensor of the plurality of wearable sensors and perform identification and impedance verification of the other wearable sensor.

[0195] Example 37: The method of Example 36, further comprising sequentially providing instructions to position, activate, verify identity, and verify impedance of each wearable sensor of the plurality of wearable sensors.

[0196] Example 38: The method described in Example 37, further comprising recording processed EEG signals wirelessly transmitted by the plurality of wearable sensors in response to verifying the identity and impedance of each wearable sensor of the plurality of wearable sensors.

[0197] Example 39: A method described in any one of Examples 36 to 37, further comprising, in response to not verifying that the impedance of the wearable sensor meets the impedance threshold, repeating providing instructions, verifying the identification, and verifying the impedance of the wearable sensor.

[0198] Example 40: The method described in Example 39, further comprising, in response to not verifying the impedance of the wearable sensor a second time, providing instructions, verifying the identification, and resuming verifying the impedance of the wearable sensor.

[0199] Example 41: At least two wearable sensors of the plurality of wearable sensors The method of any one of Examples 36 to 40, further comprising providing an alert in response to detecting that the device has been activated for positioning at a location among a plurality of locations on the user's scalp.

[0200] Example 42: The method described in Example 41, further comprising, in response to detecting that at least two wearable sensors of the plurality of wearable sensors have been activated for positioning at a particular location among a plurality of locations on the user's scalp, resuming providing instructions, verifying identification, and verifying impedance for the plurality of wearable sensors.

[0201] Example 43: The method described in Example 42, wherein detecting that at least two wearable sensors have been activated to position at a particular location includes detecting that the multiple sensors have been activated substantially simultaneously.

[0202] Example 44: A method according to any one of Examples 36 to 43, wherein providing instructions for positioning the wearable sensor includes displaying the instructions on a screen of the portable computing device.

[0203] Example 45: The method described in Example 44, wherein providing instructions for positioning the wearable sensor includes displaying the position on a screen of the portable computing device and instructions for activating the wearable sensor.

[0204] Example 46: A method described in any one of Examples 36 to 45, further comprising providing instructions to scan or input an identification of the wearable sensor before providing instructions to position the wearable sensor at a location on the user's scalp.

[0205] Example 47: A method described in any one of Examples 36 to 46, wherein providing instructions for positioning the wearable sensor at a location on the user's scalp includes instructing the use of a plurality of attachments configured to removably attach the wearable sensor to the user's scalp.

[0206] Example 48: A method for monitoring brain activity, comprising: activating a plurality of wearable sensors positioned at a plurality of locations on the user's scalp, the wearable sensors configured to detect electroencephalogram (EEG) signals indicative of the user's brain activity, each wearable sensor comprising at least two electrodes configured to monitor EEG signals when the wearable sensor is positioned on the user's scalp, and an electronic circuit configured to process the EEG signals monitored by the at least two electrodes and wirelessly transmit the processed EEG signals to a first portable computing device, wherein the activating includes following instructions displayed on a display of the first portable computing device; following activation of the plurality of wearable sensors, transferring control of the plurality of wearable sensors to a second portable computing device configured to be worn by a user to enable the second portable computing device to wirelessly receive the processed EEG signals, wherein the second portable computing device does not include a display or includes a display that is smaller than the display of the first portable computing device; A method, wherein a first portable computing device is configured to facilitate activation and positioning of a plurality of wearable sensors on a user's scalp, and a second portable computing device is configured to facilitate monitoring of the user's brain activity and detection of one or more disorders.

[0207] Example 49: The method of Example 48, wherein transferring control causes the first portable computing device to cease wirelessly receiving the processed EEG signals.

[0208] Example 50: The method of any one of Examples 48 to 49, wherein the first portable computing device includes a tablet and the second portable computing device includes a smartwatch.

[0209] Example 51: The method of any one of Examples 48 to 50, further comprising authenticating the second portable computing device before transferring control to the second portable computing device.

[0210] Example 52: The method of Example 51, wherein authenticating the second portable computing device includes scanning a QR code of the second portable computing device.

[0211] Example 53: A method described in any one of Examples 48 to 52, further comprising, in response to an alert displayed on a display of the second portable computing device, causing the second portable computing device to display instructions for resolving the alert and following the instructions for resolving the alert.

[0212] Example 54: The method described in Example 53, wherein the instructions are associated with replacing an attachment configured to removably attach a wearable sensor of the plurality of wearable sensors to the user's scalp, and the method further includes, in response to the instructions, removing the wearable sensor, replacing the attachment with another attachment, and repositioning the wearable sensor on the user's scalp.

[0213] Example 55: A method according to any one of Examples 53 to 54, wherein the instructions are associated with replacing a plurality of attachments configured to removably attach the plurality of wearable sensors to the user's scalp, and the method further includes, in response to the instructions, removing the plurality of wearable sensors, replacing the plurality of attachments with another plurality of attachments, and repositioning the plurality of wearable sensors on the user's scalp.

[0214] Example 56: A system for monitoring brain activity, comprising: a plurality of wearable sensors configured to detect electroencephalogram (EEG) signals indicative of a user's brain activity, each wearable sensor comprising: at least two electrodes configured to monitor EEG signals when the wearable sensor is positioned on the user's scalp; and electronic circuitry configured to process the EEG signals monitored by the at least two electrodes and wirelessly transmit the processed EEG signals to a first portable computing device; a first non-transitory computer-readable medium storing executable instructions that, when executed by at least one processor of the first portable computing device, cause the at least one processor of the first portable computing device to: displaying instructions on a display of the first portable computing device to facilitate activation of the plurality of wearable sensors; Following activation of the plurality of wearable sensors, transfer control of the plurality of wearable sensors to a second portable computing device, where the second portable computing device is configured to be worn by a user, and enable the second portable computing device to wirelessly receive the processed EEG signals, does not include a display or includes a display that is smaller than the display of the first portable computing device; A system, wherein a first portable computing device is configured to facilitate activation and positioning of a plurality of wearable sensors on a user's scalp, and a second portable computing device is configured to facilitate monitoring of the user's brain activity and detection of one or more disorders.

[0215] Example 57: The system described in Example 56, wherein the first portable computing device includes a tablet and the second portable computing device includes a smartwatch.

[0216] Example 58: A system described in any one of Examples 56 to 57, wherein the executable instructions further cause at least one processor of the first portable computing device to authenticate the second portable computing device before transferring control to the second portable computing device.

[0217] Example 59: The system described in Example 58, wherein authenticating the second portable computing device includes scanning a QR code of the second portable computing device.

[0218] Example 60: A method further comprising: a second non-transitory computer-readable medium storing executable instructions, the executable instructions, when executed by at least one processor of the second portable computing device, causing the at least one processor of the second portable computing device to: displaying an alert on a display of the second portable computing device; displaying user instructions for resolving the alert on a display of the second portable computing device; A system described in any one of Examples 56 to 59, which pauses collection of processed EEG signals.

[0219] Example 61: The system described in Example 60, wherein the executable instructions cause at least one processor of the second portable computing device to detect an alert in response to determining that the impedance of at least one wearable sensor among the plurality of wearable sensors does not meet an impedance threshold.

[0220] Example 62: User instructions for resolving the alert are associated with replacing an attachment configured to removably attach at least one wearable sensor to the user's scalp, the user instructions including removing the at least one wearable sensor, replacing the attachment with another attachment, and repositioning the at least one wearable sensor on the user's scalp; The executable instructions further cause at least one processor of the second portable computing device to resume collecting processed EEG signals in response to verifying the impedance of at least one wearable sensor after being repositioned on the user's scalp.

[0221] Example 63: The system described in Example 62, wherein verifying the impedance of at least one wearable sensor includes determining that the impedance of the at least one wearable sensor meets an impedance threshold.

[0222] Example 64: A system described in Example 62 or 63, wherein the executable instructions facilitate selection of at least one wearable sensor from a plurality of wearable sensors, and the executable instructions further cause at least one processor of a second portable computing device to display the position of the at least one wearable sensor on the user's scalp.

[0223] Example 65: A system described in any one of Examples 60 to 64, wherein the executable instructions cause at least one processor of a second portable computing device to cause the display of an alert in response to the passage of a duration of time since replacing a plurality of attachments configured to removably attach a plurality of wearable sensors to a user's scalp.

[0224] Example 66: The system of Example 65, wherein the duration comprises 24 hours.

[0225] Example 67: When executed by at least one processor of a second portable computing device, the method causes the at least one processor of the second portable computing device to: A system described in any one of Examples 56 to 66, further comprising a second non-transitory computer-readable medium storing executable instructions that, in response to detecting a possible seizure, cause the display of instructions for confirming the occurrence of a seizure.

[0226] Example 68: A system described in any one of Examples 56 to 67, wherein the second portable computing device is configured to transmit the processed EEG signal to another computing device, such as a server.

[0227] Example 69: The second portable computing device is smaller than the first portable computing device; The system described in any one of Examples 56 to 68, further comprising a second non-transitory computer-readable medium storing executable instructions that, when executed by at least one processor of the second portable computing device, cause the at least one processor of the second portable computing device to output instructions on a display for placing multiple wearable sensors on the user's scalp.

[0228] Example 70: The second portable computing device is smaller than the first portable computing device; the second portable computing device does not include a display; The system described in any one of Examples 56 to 68, further comprising a second non-transitory computer-readable medium storing executable instructions that, when executed by at least one processor of another computing device, cause the at least one processor of the other computing device to output instructions on a display for placing multiple wearable sensors on the user's scalp.

[0229] Example 71: A system for synchronized monitoring of brain activity, comprising: a plurality of wearable sensors configured to detect electroencephalogram (EEG) signals indicative of a user's brain activity, each wearable sensor comprising: at least two electrodes configured to monitor EEG signals when the wearable sensor is positioned on the user's scalp; and electronic circuitry configured to process the EEG signals monitored by the at least two electrodes and wirelessly transmit the processed EEG signals to a portable computing device; a non-transitory computer-readable medium storing executable instructions, the executable instructions being executed by at least one processor of the portable computing device. At least one processor wirelessly transmitting messages including clock information to a plurality of wearable sensors; The system further includes causing an electronic circuit of each wearable sensor of the plurality of wearable sensors to set an internal clock to the clock information such that the internal clock substantially coincides with the internal clocks of other wearable sensors of the plurality of wearable sensors, the internal clock being used to timestamp recorded signals indicative of the user's brain activity, and data determined by each wearable sensor of the plurality of wearable sensors correlates to data determined by other wearable sensors of the plurality of wearable sensors within 200 ms or less.

[0230] Example 72: The system described in Example 71, wherein none of the wearable sensors of the plurality of wearable sensors communicates with another wearable sensor of the plurality of wearable sensors.

[0231] Example 73: A system described in any one of Examples 71 to 72, wherein data determined by each wearable sensor of the plurality of wearable sensors correlates with data determined by other wearable sensors of the plurality of wearable sensors within 50 ms or less.

[0232] Example 74: A system described in any one of Examples 66, 67, and 71, wherein the executable instructions further cause at least one processor to confirm that the multiple wearable sensors have set their internal clocks following wirelessly transmitting a message.

[0233] Example 75: A system described in any one of Examples 71 to 74, wherein the executable instructions further cause at least one processor to verify that the processed EEG signals received from each wearable sensor of the plurality of wearable sensors correlate with the processed EEG signals determined by other wearable sensors of the plurality of wearable sensors within 200 ms or less.

[0234] Example 76: The system described in Example 75, wherein the executable instructions further cause at least one processor to transmit processed EEG signals received from the multiple wearable sensors to a remote computing device in response to verification.

[0235] Example 77: The executable instructions further include: polling a plurality of wearable sensors about their internal clocks; A system described in any one of Examples 71 to 76, wherein in response to detecting that the difference between the internal clock of at least one wearable sensor among a plurality of wearable sensors and the expected internal clock meets a threshold, the system repeatedly wirelessly transmits a message to cause the electronic circuitry of at least one wearable sensor to set the internal clock.

[0236] Example 78: The executable instructions may include instructions to at least one processor: causing each wearable sensor of the plurality of wearable sensors to wirelessly transmit a first message and causing electronic circuitry of the plurality of wearable sensors to listen for a second message; A system described in any one of Examples 71 to 77, wherein the system transmits a message wirelessly by wirelessly broadcasting a second message to multiple wearable sensors following transmission of a first message, the second message including clock information.

[0237] Example 79: The system described in Example 78, wherein the first and second messages are transmitted using a Bluetooth Low Energy (BLE) protocol.

[0238] Example 80: A method for synchronized monitoring of brain activity, comprising: wirelessly transmitting a message including clock information to a plurality of wearable sensors configured to detect electroencephalogram (EEG) signals indicative of a user's brain activity, each wearable sensor comprising at least two electrodes configured to monitor the EEG signals when the wearable sensor is positioned on the user's scalp, and electronic circuitry configured to process the EEG signals monitored by the at least two electrodes and wirelessly transmit the processed EEG signals to a portable computing device; causing electronic circuitry of each wearable sensor of the plurality of wearable sensors to set an internal clock to the clock information such that the internal clock substantially coincides with internal clocks of other wearable sensors of the plurality of wearable sensors, the internal clock being used to timestamp recorded signals indicative of the user's brain activity; wirelessly receiving processed EEG signals from the plurality of wearable sensors and verifying that the processed EEG signal received from each wearable sensor of the plurality of wearable sensors correlates with processed EEG signals determined by other wearable sensors of the plurality of wearable sensors within 200 ms or less; and in response to verifying, transmitting the processed EEG signals received from the plurality of wearable sensors to a remote computing device.

[0239] Example 81: The method described in Example 80, wherein none of the wearable sensors of the plurality of wearable sensors communicates with another wearable sensor of the plurality of wearable sensors.

[0240] Example 82: A method described in any one of Examples 80 to 81, wherein verifying includes verifying that the processed EEG signals received from each wearable sensor of the plurality of wearable sensors correlate with the processed EEG signals determined by other wearable sensors of the plurality of wearable sensors within 50 ms or less.

[0241] Example 83: A method described in any one of Examples 80 to 82, further comprising verifying that multiple wearable sensors have set their internal clocks.

[0242] Example 84: Polling a plurality of wearable sensors about their internal clocks; The method of example 83, further comprising: in response to detecting that a difference between the internal clock of at least one wearable sensor among the plurality of wearable sensors and an expected internal clock satisfies a threshold, repeating wireless transmission of a message to cause an electronic circuit of at least one wearable sensor to set its internal clock.

[0243] Example 85: Wirelessly transmitting a message includes: wirelessly transmitting a first message to each wearable sensor of the plurality of wearable sensors and causing electronic circuitry of the plurality of wearable sensors to listen for a second message; A method described in any one of Examples 80 to 84, comprising: following sending the first message, wirelessly broadcasting a second message to a plurality of wearable sensors, wherein the second message includes clock information.

[0244] Example 86: The method described in Example 85, wherein the first message and the second message are transmitted using a Bluetooth Low Energy (BLE) protocol.

[0245] Example 87: A system for synchronized monitoring of brain activity, comprising: A plurality of wearable sensors configured to record brain activity of a user, each of the sensors comprising: a plurality of wearable sensors, each comprising at least two electrodes configured to detect signals indicative of a user's brain activity when the wearable sensors are positioned on the user's scalp; and an electronic circuit configured to determine data associated with the user's brain activity based on the signals detected by the at least two electrodes; a non-transitory computer-readable medium storing instructions that, when executed by at least one processor of an electronic circuit of a wearable sensor of the plurality of wearable sensors, cause the at least one processor to: applying an electrical stimulus to two electrodes of at least one of the wearable sensors configured to be sensed by other wearable sensors of the plurality of wearable sensors; The system causes electronic circuitry of each wearable sensor among the other wearable sensors to process electrical stimuli sensed by at least two electrodes and record the electrical stimuli along with data associated with the user's brain activity, the recording of the electrical stimuli facilitating combining and processing the data associated with the user's brain activity collected by the multiple wearable sensors.

[0246] Example 88: A system for monitoring brain activity, comprising: a plurality of wearable sensors configured to detect electroencephalogram (EEG) signals indicative of a user's brain activity, each wearable sensor comprising at least two electrodes configured to monitor EEG signals when the wearable sensor is positioned on the user's scalp, and electronic circuitry configured to process the EEG signals monitored by the at least two electrodes and wirelessly transmit the processed EEG signals to a first portable computing device, each wearable sensor associated with a unique sensor identifier; and a non-transitory computer-readable medium storing executable instructions that, when executed by the at least one processor, cause the at least one processor to: providing instructions for activating and positioning a plurality of wearable sensors on the user's scalp, the positioning including attaching the plurality of wearable sensors to the user's scalp with a plurality of attachments; For each wearable sensor of the plurality of wearable sensors, recording an association between a unique sensor identifier of the wearable sensor and a location of the wearable sensor on the user's scalp; and providing instructions for replacing a wearable sensor attachment, including the location of the wearable sensor on the user's scalp.

[0247] Example 89: The system described in Example 88, wherein instructions for replacing the attachment are provided in response to detecting a malfunction of the wearable sensor.

[0248] Example 90: A system described in any one of Examples 88 to 89, wherein instructions regarding replacement of attachments and positioning of wearable sensors are provided on a display.

[0249] Example 91: A system described in any one of Examples 88 to 90, wherein the plurality of wearable sensors includes four wearable sensors configured to be positioned behind the user's left ear, behind the user's right ear, on the left side of the user's forehead, and on the right side of the user's forehead.

[0250] Example 92: A system for monitoring brain activity, comprising: A plurality of wearable sensors configured to record brain activity of a user, each wearable sensor comprising: a housing; at least two electrodes positioned on an exterior surface of the housing and configured to detect electroencephalogram (EEG) signals indicative of the user's brain activity when the wearable sensor is positioned on the user's scalp; and an electronic circuit supported by the housing and configured to process the EEG signals detected by the at least two electrodes. a power source supported by the housing and configured to provide power to the electronic circuitry, the housing having an elongated rounded shape with a concave first side and a convex second side disposed opposite the concave first side, the concave first side and the convex second side configured to protrude from the user's scalp when the housing is positioned on the user's scalp, and a thickness of the housing increasing from the concave first side to the convex second side; a plurality of attachments, each attachment shaped to substantially conform to an elongated, rounded shape of a housing of one of the plurality of wearable sensors, the attachment including a first side configured to be attached to an outer surface of the housing, and a second side configured to removably position the one of the plurality of wearable sensors on a user's scalp, wherein the number of attachments in the plurality of attachments exceeds the number of wearable sensors in the plurality of wearable sensors.

[0251] Example 93: The system described in Example 92, further comprising a charger including a charger housing configured to receive power sources and simultaneously charge at least two of the plurality of wearable sensors.

[0252] Example 94: A system described in any one of Examples 92 to 93, wherein the elongated, rounded shape of the housing of one of the plurality of wearable sensors is configured to fit around the user's hairline so that the elongated, rounded shape of the housing facilitates inconspicuous placement of the wearable sensor on the user's scalp while facilitating collection of EEG signals.

[0253] Example 95: A system described in any one of Examples 92 to 94, wherein the surface area of ​​the housing of one of the plurality of wearable sensors is between 16.0 cm2 and 10 cm2.

[0254] Example 96: A system described in any one of Examples 92 to 95, wherein the volume of the housing of one of the plurality of wearable sensors is between 5.0 cm3 and 3.0 cm3.

[0255] Example 97: A system described in any one of Examples 92 to 96, wherein the number of attachments among the plurality of attachments includes the number of wearable sensors among the plurality of wearable sensors multiplied by the number of days the plurality of wearable sensors are configured to record the user's brain activity.

[0256] Example 98: A system described in any one of Examples 92 to 97, wherein the first side of each attachment is configured to be attached to the bottom surface of the housing of a wearable sensor among the plurality of wearable sensors.

[0257] Example 99: A system described in any one of Examples 92 to 98, wherein each attachment of the plurality of attachments comprises a hydrocolloid material on a second side of the attachment, the hydrocolloid material facilitating repositioning of a wearable sensor of the plurality of wearable sensors on the user's scalp.

[0258] Example 100: Each attachment is a first layer comprising a thermoplastic resin; a second layer comprising a cured hydrogel; a third layer containing an adhesive; a fourth layer comprising a nonwoven fabric; a fifth layer comprising an adhesive; and A sixth layer containing a thermoplastic resin 99. The system of any one of Examples 92-99, comprising a plurality of layers comprising:

[0259] Example 101: The system described in Example 100, wherein the thermoplastic resin comprises polyethylene terephthalate (PET).

[0260] Example 102: A system described in any one of Examples 100-101, wherein the first and third layers are laminated to one another such that the second layer comprising the cured hydrogel is disposed between the first and third layers.

[0261] Example 103: A system described in any one of Examples 100 to 102, wherein the third and fifth layers form an opening, and one or more of the third layer, fourth layer, or fifth layer comprises a hardened hydrogel.

[0262] Example 104: A system described in Example 103, wherein the opening is aligned with at least two electrodes of one of the plurality of wearable sensors.

[0263] Example 105: An integrated wireless wearable sensor configured to monitor brain activity, comprising: a housing having an elongated, rounded shape configured to fit around a user's hair, the housing comprising a concave first side and a convex second side positioned opposite the concave first side, the concave first side and the convex second side configured to protrude from the user's scalp when the housing is positioned on the user's scalp, and a thickness of the housing increasing from the concave first side to the convex second side; at least two electrodes positioned on an exterior surface of the housing and configured to detect electroencephalogram (EEG) signals indicative of the user's brain activity when the housing is positioned on the user's scalp; an electronic circuit supported by the housing and configured to process EEG signals detected by the at least two electrodes and wirelessly communicate the processed EEG signals to a remote computing device; An integrated wireless wearable sensor, the elongated, rounded shape of the housing facilitates unobtrusive wearing of the housing on the user's scalp while facilitating the collection of EEG signals.

[0264] Example 106: The system of Example 105, wherein the surface area of ​​the housing is 16.0 cm2 to 10 cm2.

[0265] Example 107: A system described in any one of Examples 105 to 106, wherein the volume of the housing is 5.0 cm3 to 3.0 cm3.

[0266] Example 108: A kit comprising a plurality of sensors according to any one of Examples 105 to 107, wherein each sensor is configured to detect electroencephalogram (EEG) signals independently of the other sensors.

[0267] Example 109: A device further comprising a plurality of attachments, each attachment shaped to substantially conform to the elongated, rounded shape of a housing of one of the plurality of sensors, the attachment including a first side configured to be attached to an exterior surface of the housing, and a second side configured to removably position the sensor on a user's scalp; The kit of Example 108, wherein the number of attachments in the plurality of attachments exceeds the number of sensors in the plurality of sensors.

[0268] Example 110: The kit of Example 109, wherein the number of attachments among the plurality of attachments includes the number of sensors among the plurality of sensors multiplied by the number of days the plurality of sensors are configured to record the user's brain activity.

[0269] Example 111: A system for monitoring brain activity, comprising: 1. A plurality of integrated wireless wearable sensors configured to record brain activity of a user, each sensor comprising: a housing having an elongated, rounded shape configured to fit around a user's hair, the housing comprising a concave first side and a convex second side positioned opposite the concave first side, the concave first side and the convex second side configured to protrude from the user's scalp when the housing is positioned on the user's scalp, and a thickness of the housing increasing from the concave first side to the convex second side; at least two electrodes positioned on an exterior surface of the housing and configured to detect electroencephalogram (EEG) signals indicative of the user's brain activity when the housing is placed on the user's scalp; an electronic circuit supported by the housing and configured to process EEG signals detected by the at least two electrodes and wirelessly communicate the processed EEG signals to a remote computing device; The elongated, rounded shape of the housing facilitates unobtrusive placement of the housing on the user's scalp while facilitating collection of EEG signals. a plurality of attachments, each attachment shaped to substantially conform to the elongated, rounded shape of a housing of a sensor of the plurality of integrated wireless wearable sensors, the plurality of attachments including a first side configured to be attached to an exterior surface of the housing and a second side configured to removably position the sensor on a user's scalp, wherein the number of attachments in the plurality of attachments exceeds the number of sensors in the plurality of integrated wireless wearable sensors.

[0270] Example 112: The system described in Example 111, wherein the number of attachments in the plurality of attachments includes the number of sensors in the plurality of integrated wireless wearable sensors multiplied by the number of days the plurality of integrated wireless wearable sensors are configured to record the user's brain activity.

[0271] Example 113: A system described in any one of Examples 111 to 112, wherein the surface area of ​​the housing of one of the multiple integrated wireless wearable sensors is 16.0 cm2 to 10 cm2 and the volume of the housing is 5.0 cm3 to 3.0 cm3.

[0272] Example 114: A system for synchronized monitoring of brain activity, comprising: a plurality of wearable sensors configured to detect electroencephalogram (EEG) signals indicative of a user's brain activity, each wearable sensor comprising at least two electrodes configured to monitor EEG signals when the wearable sensor is positioned on the user's scalp, and electronic circuitry configured to process the EEG signals monitored by the at least two electrodes and wirelessly transmit the processed EEG signals to a computing device; and a non-transitory computer-readable medium storing executable instructions, the executable instructions, when executed by at least one processor of a computing device, At least one processor wirelessly transmitting a message including clock information to a plurality of wearable sensors; causing electronic circuitry of each wearable sensor of the plurality of wearable sensors to set its internal clock value to the clock information such that the internal clock value substantially matches internal clock values ​​of other wearable sensors of the plurality of wearable sensors, the internal clock value being used to timestamp recorded EEG signals indicative of the user's brain activity, and the recorded EEG signals determined by each wearable sensor of the plurality of wearable sensors correlate to within 200 ms or less with recorded EEG signals determined by other wearable sensors of the plurality of wearable sensors; checking a plurality of wearable sensors for their internal clock values; repeating wireless transmission of the message in response to detecting that an internal clock value of at least one first wearable sensor of the plurality of wearable sensors differs from an expected first internal clock value associated with the clock information to cause an electronic circuit of the at least one first wearable sensor to set its internal clock value so that the internal clock value substantially matches the internal clock values ​​of other wearable sensors of the plurality of wearable sensors; A system that allows the following to be performed.

[0273] Example 115: The system described in Example 114, wherein none of the wearable sensors of the plurality of wearable sensors communicates with another wearable sensor of the plurality of wearable sensors.

[0274] Example 116: A system described in any one of Examples 114 to 115, wherein the recorded EEG signals determined by each wearable sensor of the plurality of wearable sensors correlate with the recorded EEG signals determined by other wearable sensors of the plurality of wearable sensors within a range of 50 ms or less.

[0275] Example 117: A system described in any one of Examples 114 to 116, wherein the executable instructions further cause at least one processor to confirm that the multiple wearable sensors have set their internal clock values ​​following wirelessly transmitting a message.

[0276] Example 118: A system described in any one of Examples 114 to 117, wherein the executable instructions further cause at least one processor to verify that the processed EEG signals received from each wearable sensor of the plurality of wearable sensors correlate to processed EEG signals determined by other wearable sensors of the plurality of wearable sensors within a range of 200 ms or less.

[0277] Example 119: The system described in Example 118, wherein the executable instructions further cause at least one processor to transmit processed EEG signals received from the multiple wearable sensors to a remote computing device in response to verification.

[0278] Example 120: The executable instructions further include: polling a plurality of wearable sensors for their internal clock values; A system described in any one of Examples 114 to 119, wherein in response to detecting that the difference between the internal clock value of at least one second wearable sensor among the plurality of wearable sensors and the expected second internal clock value satisfies a threshold, the system repeats wireless transmission of a message to cause the electronic circuit of the at least one second wearable sensor to set the internal clock value.

[0279] Example 121: The executable instructions include instructions for causing at least one processor to: causing each wearable sensor of the plurality of wearable sensors to wirelessly transmit a first message and causing electronic circuitry of the plurality of wearable sensors to listen for a second message; A system described in any one of Examples 114 to 120, wherein the message is transmitted wirelessly by wirelessly broadcasting a second message to multiple wearable sensors following transmission of a first message, the second message including clock information.

[0280] Example 122: The system described in Example 121, wherein the first and second messages are transmitted using the Bluetooth Low Energy (BLE) protocol.

[0281] Example 123: A method for synchronized monitoring of brain activity, comprising: wirelessly transmitting a message including clock information to a plurality of wearable sensors configured to detect electroencephalogram (EEG) signals indicative of a user's brain activity, each wearable sensor comprising at least two electrodes configured to monitor the EEG signals when the wearable sensor is positioned on the user's scalp, and electronic circuitry configured to process the EEG signals monitored by the at least two electrodes and wirelessly transmit the processed EEG signals to a computing device; causing electronic circuitry of each wearable sensor of the plurality of wearable sensors to set its internal clock value in the clock information such that the internal clock value substantially matches internal clock values ​​of other wearable sensors of the plurality of wearable sensors, the internal clock value being used to timestamp recorded EEG signals indicative of the user's brain activity; wirelessly receiving processed EEG signals from the plurality of wearable sensors and verifying that the processed EEG signal received from each wearable sensor of the plurality of wearable sensors correlates to within 200 ms or less with processed EEG signals determined by other wearable sensors of the plurality of wearable sensors; In response to verifying, transmitting the processed EEG signals received from the plurality of wearable sensors to a remote computing device; and in response to failure to verify, repeating wireless transmission of the message to cause an electronic circuit of at least one first wearable sensor whose internal clock value differs from the expected first internal clock value associated with the clock information to set its internal clock value so that its internal clock value substantially matches the internal clock values ​​of other wearable sensors of the plurality of wearable sensors.

[0282] Example 124: The method described in Example 123, wherein none of the wearable sensors of the plurality of wearable sensors communicates with another wearable sensor of the plurality of wearable sensors.

[0283] Example 125: A method described in any one of Examples 123 to 124, wherein verifying includes verifying that the processed EEG signal received from each wearable sensor of the plurality of wearable sensors correlates with the processed EEG signal determined by other wearable sensors of the plurality of wearable sensors within a range of 50 ms or less.

[0284] Example 126: A method described in any one of Examples 123 to 125, further comprising verifying that multiple wearable sensors have set their internal clock values.

[0285] Example 127: Polling a plurality of wearable sensors for their internal clock values; an interior of at least one second wearable sensor of the plurality of wearable sensors; A method described in any one of Examples 123 to 126, further comprising, in response to detecting that the difference between the clock value and the expected second internal clock value meets a threshold, repeating the wireless transmission of the message to cause the electronic circuit of at least one second wearable sensor to set the internal clock value.

[0286] Example 128: Wirelessly transmitting a message includes: wirelessly transmitting a first message to each wearable sensor of the plurality of wearable sensors and causing electronic circuitry of the plurality of wearable sensors to listen for a second message; A method described in any one of Examples 123 to 127, comprising: following sending the first message, wirelessly broadcasting a second message to multiple wearable sensors, wherein the second message includes clock information.

[0287] Example 129: The method described in Example 128, wherein the first message and the second message are transmitted using a Bluetooth Low Energy (BLE) protocol.

[0288] Example 130: A system for synchronized monitoring of brain activity, comprising: a plurality of wearable sensors configured to detect electroencephalogram (EEG) signals indicative of a user's brain activity, each wearable sensor comprising at least two electrodes configured to monitor EEG signals when the wearable sensor is positioned on the user's scalp, and electronic circuitry configured to process the EEG signals monitored by the at least two electrodes and wirelessly transmit the processed EEG signals to a computing device; a non-transitory computer-readable medium storing executable instructions that, when executed by at least one processor of a computing device, cause the at least one processor to: wirelessly transmitting a message including clock information to a plurality of wearable sensors; causing an electronic circuit of each wearable sensor of the plurality of wearable sensors to set an internal clock in the clock information such that the internal clock substantially coincides with internal clocks of other wearable sensors of the plurality of wearable sensors, the internal clock being used to timestamp recorded EEG signals indicative of the user's brain activity, and the recorded EEG signals determined by each wearable sensor of the plurality of wearable sensors correlate to within 200 ms or less with recorded EEG signals determined by other wearable sensors of the plurality of wearable sensors; The executable instructions further include instructions to at least one processor: polling a plurality of wearable sensors about their internal clocks; and in response to detecting that a difference between an internal clock of at least one wearable sensor among a plurality of wearable sensors and an expected internal clock satisfies a threshold, repeatedly wirelessly transmitting a message to cause an electronic circuit of the at least one wearable sensor to set its internal clock.

[0289] Example 131: The method described in Example 130, wherein none of the wearable sensors of the plurality of wearable sensors communicates with another wearable sensor of the plurality of wearable sensors.

[0290] Example 132: A method for synchronized monitoring of brain activity, comprising: and wirelessly transmitting a message including clock information to a plurality of wearable sensors, the plurality of wearable sensors configured to detect electroencephalogram (EEG) signals indicative of brain activity of a user, each wearable sensor including at least two electrodes configured to monitor the EEG signals when the wearable sensor is positioned on the scalp of the user; an electronic circuit configured to process EEG signals monitored by the at least two electrodes and wirelessly transmit the processed EEG signals to a computing device; causing electronic circuitry of each wearable sensor of the plurality of wearable sensors to set an internal clock to the clock information such that the internal clock substantially coincides with internal clocks of other wearable sensors of the plurality of wearable sensors, the internal clock being used to timestamp recorded EEG signals indicative of the user's brain activity; wirelessly receiving processed EEG signals from the plurality of wearable sensors and verifying that the processed EEG signal received from each wearable sensor of the plurality of wearable sensors correlates to within 200 ms or less with processed EEG signals determined by other wearable sensors of the plurality of wearable sensors; In response to verifying, transmitting the processed EEG signals received from the plurality of wearable sensors to a remote computing device; polling a plurality of wearable sensors about their internal clocks; and in response to detecting that a difference between an internal clock of at least one wearable sensor among a plurality of wearable sensors and an expected internal clock satisfies a threshold, repeating wireless transmission of a message to cause an electronic circuit of the at least one wearable sensor to set its internal clock.

[0291] Example 133: The method described in Example 132, wherein none of the wearable sensors of the plurality of wearable sensors communicates with another wearable sensor of the plurality of wearable sensors.

[0292] One or more features of any one of the above examples may be used with one or more features of any other example.

[0293] Other variations The general principles described herein can be extended to other scenarios, for example, for intensive care in children and adults, two sensors, four sensors, eight sensors, or various combinations of sensors may be used.

[0294] Various other configurations may also be used, and particular elements shown as implemented in hardware may instead be implemented in software, firmware, or a combination thereof. Those skilled in the art will recognize various alternatives to the specific embodiments described herein.

[0295] The specification and drawings depict specific embodiments that are provided to facilitate explanation and illustration and are not intended to be limiting. The embodiments can be implemented for use in various environments without departing from the spirit and scope of the disclosure.

[0296] In operation using a programmable processor governed by instructions stored in memory, at least some elements of the device of the present application can be controlled and at least some steps of the method of the present invention can be performed. The memory can be random access memory (RAM), read only memory (ROM), flash memory, or any other memory, or combination thereof, suitable for storing control software or other instructions and data. Those skilled in the art will also understand that the instructions or programs defining the functionality of the present invention can be stored permanently on a non-writable storage medium (e.g., a read-only memory device within a computer such as a ROM, or a device readable by a computer I / O attachment such as a CD-ROM or DVD disk), on a writable storage medium, or on a computer readable medium. It should be readily understood that information may be delivered to a processor in many forms, including, but not limited to, information mutably stored on a hard disk (e.g., floppy disk, removable flash memory, and hard drive) or transmitted to a computer via a communications medium, including a wired or wireless computer network. Additionally, while the present invention may be embodied in software, the functionality required to implement the present invention may optionally or alternatively be embodied partially or entirely using firmware and / or hardware components, such as combinational logic, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other hardware, or some combination of hardware, software, and / or firmware components.

[0297] In various embodiments, input may be requested from a user. Examples of methods for receiving user input, such as receiving a button press from a user, are illustrative and not limiting. Alternative methods of receiving user input may be used, including receiving a button press on a touchscreen, a physical button press on a device, a swipe, a tap, any other touch gesture, verbal (audio) input, etc.

[0298] Various modifications to the implementations described in this disclosure will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other implementations without departing from the spirit or scope of the disclosure. Thus, the scope of the claims is not intended to be limited to the implementations shown herein, but is to be accorded the widest scope consistent with this disclosure, the principles and novel features disclosed herein.

[0299] Certain features that are described herein in the context of separate implementations may also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation may also be implemented in multiple implementations separately or in any suitable subcombination. Furthermore, while features may be described above as acting in a particular combination and may even initially be claimed as such, one or more features from a claimed combination may in some cases be deleted from that combination, and the claimed combination may be directed to a subcombination or a variation of the subcombination.

[0300] Depending on the embodiment, certain operations, events, or functions of any of the processes or algorithms described herein may be performed in a different order, added, merged, or omitted entirely. Furthermore, in certain embodiments, operations or events may be performed simultaneously rather than sequentially, for example, through multithreading, interrupt processing, or multiple processors or processor cores, or on other parallel architectures.

[0301] The various illustrative logic blocks, modules, routines, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or as a combination of electronic hardware and executable software. To clearly illustrate this interchangeability, the various illustrative components, blocks, modules, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or as software running on hardware depends on the particular application and design constraints imposed on the overall system. The described functionality may be implemented in various ways for each particular application, and such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

[0302] Additionally, various example logic blocks and modules described with respect to the embodiments disclosed herein may include machine learning service servers, digital signal processors (DSPs), application specific The machine learning service server may be implemented or performed by a machine, such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. The machine learning service server may be or include a microprocessor, but alternatively, the machine learning service server may be or include a controller, microcontroller, or state machine, combinations thereof, or the like, configured to generate and publish machine learning services supported by machine learning models. The machine learning service server may include electrical circuitry configured to process computer-executable instructions. Although described herein primarily with respect to digital technology, the machine learning service server may also include primarily analog components. For example, some or all of the modeling, simulation, or service algorithms described herein may be implemented in analog circuitry or mixed analog and digital circuitry. The computing environment may include any type of computer system, including, but not limited to, computer systems based on microprocessors, mainframe computers, digital signal processors, portable computing devices, device controllers, or computational engines within appliances, to name a few.

[0303] Elements of the methods, processes, routines, or algorithms described in connection with the embodiments disclosed herein may be embodied directly in hardware, in software modules executed by a machine learning service server, or in a combination of the two. The software modules may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of non-transitory computer-readable storage medium. An exemplary storage medium may be coupled to the machine learning service server such that the machine learning service server can read information from and write information to the storage medium. Alternatively, the storage medium may be integral with the machine learning service server. The machine learning service server and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. Alternatively, the machine learning service server and the storage medium may reside as separate components in a user terminal (e.g., an access device or a network service client device).

[0304] As used herein, conditional language, particularly "can," "could," "might," "may," "for example," and the like, is intended to generally convey that certain embodiments include certain features, elements, and / or steps, while other embodiments do not, unless otherwise specified or understood within the context in which it is used. Thus, such conditional language is not generally intended to imply that features, elements, and / or steps are somehow required for one or more embodiments, or that one or more embodiments necessarily include logic for determining whether those features, elements, and / or steps are included or should be performed in any particular embodiment, with or without other input or prompting. Terms such as "comprising," "including," and "having" are synonymous and used inclusively, without limitation, and do not exclude additional elements, features, acts, operations, etc. Also, the term "or" is used in its inclusive sense (rather than its exclusive sense), so, for example, when used to connect a list of elements, the term "or" means one, some, or all of the elements in the list.

[0305] Disjunctive language, such as the phrase "at least one of X, Y, or Z," means that an item, term, etc. may be X, Y, or Z, or any combination thereof, unless otherwise specified. It is understood otherwise with the context as it is generally used to indicate that any combination (e.g., X, Y, and / or Z) may be present. Thus, such disjunctive language is generally not intended to, and should not, imply that a particular embodiment requires that at least one of X, at least one of Y, or at least one of Z, respectively, be present.

[0306] Unless otherwise specified, articles such as "a" or "an" should generally be construed to include one or more listed items. Thus, phrases such as "a device configured to" are intended to include one or more listed devices. Such one or more listed devices may also be collectively configured to perform the stated enumeration. For example, "a processor configured to perform statements A, B, and C" may include a first processor configured to perform statement A working in conjunction with a second processor configured to perform statements B and C.

[0307] While the above detailed description illustrates, describes, and points out novel features as applied to various embodiments, it will be understood that various omissions, substitutions, and changes in the form and details of the illustrated devices or algorithms may be made without departing from the spirit of the present disclosure. As will be recognized, specific embodiments described herein may be embodied in forms that do not provide all of the features and benefits described herein, since some features may be used or practiced separately from others. The scope of the specific embodiments disclosed herein is indicated by the appended claims, rather than the foregoing description. All changes that come within the meaning and range of equivalency of the claims are to be embraced within their scope.

Claims

1. 1. A system for monitoring brain activity, comprising: a plurality of wearable sensors configured to detect electroencephalogram (EEG) signals indicative of a user's brain activity, each wearable sensor comprising: at least two electrodes configured to monitor the EEG signals when the wearable sensor is positioned on the user's scalp; and electronic circuitry configured to process the EEG signals monitored by the at least two electrodes and wirelessly transmit the processed EEG signals to a first portable computing device; a first non-transitory computer-readable medium storing executable instructions that, when executed by at least one processor of the first portable computing device, cause the at least one processor of the first portable computing device to: displaying instructions on a display of the first portable computing device to facilitate activation of the plurality of wearable sensors; following the activation of the plurality of wearable sensors, transferring control of the plurality of wearable sensors to a second portable computing device, enabling the second portable computing device configured to be worn by the user to wirelessly receive processed EEG signals, the second portable computing device not including a display or including a display smaller than the display of the first portable computing device; The system, wherein the first portable computing device is configured to facilitate activation and positioning of the plurality of wearable sensors on the scalp of the user, and the second portable computing device is configured to facilitate monitoring the brain activity of the user and detecting one or more disorders.

2. The system of claim 1 , wherein the first portable computing device comprises a tablet and the second portable computing device comprises a smartwatch.

3. 2. The system of claim 1, wherein the executable instructions further cause the at least one processor of the first portable computing device to authenticate the second portable computing device before transferring control to the second portable computing device.

4. The system of claim 3 , wherein authenticating the second portable computing device includes scanning a QR code on the second portable computing device.

5. and a second non-transitory computer-readable medium storing executable instructions that, when executed by at least one processor of the second portable computing device, cause the at least one processor of the second portable computing device to: displaying an alert on the display of the second portable computing device; displaying user instructions for resolving the alert on the display of the second portable computing device; The system of claim 1 , further comprising: pausing acquisition of the processed EEG signals.

6. The executable instructions are for executing the at least one program on the second portable computing device.

6. The system of claim 5, further comprising: causing one processor to detect the alert in response to determining that the impedance of at least one wearable sensor of the plurality of wearable sensors does not meet an impedance threshold.

7. the user instructions for resolving the alert are associated with replacing an attachment configured to removably attach the at least one wearable sensor to the scalp of the user, the user instructions including removing the at least one wearable sensor, replacing the attachment with another attachment, and repositioning the at least one wearable sensor on the scalp of the user; The executable instructions further cause the at least one processor of the second portable computing device to: verifying the impedance of the at least one wearable sensor after the at least one wearable sensor is repositioned on the scalp of the user; resuming collection of the processed EEG signals in response to verifying the impedance of the at least one wearable sensor after the at least one wearable sensor is repositioned on the scalp of the user. The system of claim 6.

8. The system of claim 7 , wherein verifying the impedance of the at least one wearable sensor comprises determining that the impedance of the at least one wearable sensor meets the impedance threshold.

9. 8. The system of claim 7, wherein the executable instructions further cause the at least one processor of the second portable computing device to display a position of the at least one wearable sensor on the scalp of the user.

10. 6. The system of claim 5, wherein the executable instructions cause the at least one processor of the second portable computing device to display the alert in response to a lapse of a duration since a replacement of a plurality of attachments configured to removably attach the plurality of wearable sensors to the scalp of the user.

11. The system of claim 10 , wherein the duration comprises 24 hours.

12. and a second non-transitory computer-readable medium storing executable instructions that, when executed by at least one processor of the second portable computing device, cause the at least one processor of the second portable computing device to: Detecting possible seizures and in response to detecting the possible seizure, displaying instructions for confirming the occurrence of a seizure. The system of claim 1 .

13. The system of claim 1 , wherein the second portable computing device is configured to transmit the processed EEG signals to another computing device.

14. The system of claim 1 , wherein the other computing device comprises a server.

15. the second portable computing device is smaller than the first portable computing device; The system further comprises a second non-transitory computer-readable medium storing executable instructions that, when executed by at least one processor of the second portable computing device, cause the at least one processor of the second portable computing device to output instructions on the display for placing the plurality of wearable sensors on the scalp of the user. The system of claim 1 .

16. the second portable computing device is smaller than the first portable computing device; the second portable computing device does not include the display; The system further comprises a second non-transitory computer-readable medium storing executable instructions that, when executed by at least one processor of another computing device, cause the at least one processor of the other computing device to output instructions on the display for positioning the plurality of wearable sensors on the scalp of the user. The system of claim 1 .

17. The system of claim 1 , wherein the executable instructions cause the at least one processor of the first portable computing device to facilitate sequential activation of the plurality of wearable sensors.

18. 10. A method of monitoring brain activity comprising operating the system of claim 1.

19. SYSTEMS AND / OR METHODS AS ILLUSTRATED AND / OR DESCRIBED.

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