Wireless bioelectric device

Abstract

Methods and / or systems configured for receiving an electroencephalogram (EEG) signal with an electrode; transmitting the EEG signal to a processor or application on a device; and computing a sleep report from the EEG signal. The methods and / or systems may be further be configured for processing the EEG signal into a digital signal with an analog-to-digital converter disposed on the signal acquisition circuit board, wherein computing the sleep report comprises an algorithm disposed on a processor or application on a device.

Description

Attorney Docket No. 1910-00402Wireless Bioelectric DeviceBACKGROUND

[0001] Current sleep monitoring technologies and studies, particularly Polysomnography (PSG), remain the gold standard for diagnosing sleep disorders, yet they come with substantial technical and practical shortcomings that hinder their effectiveness. While PSG is capable of providing detailed, multi-channel data on brain activity, eye movement, muscle tone, heart rate, and respiration, the process is far from seamless. Preparing the patient for monitoring — including attaching multiple electrodes to the scalp, face, chest, and legs — takes an average of 1.5 hours. This lengthy setup can significantly disrupt the patient's sleep cycle even before the monitoring begins. The presence of cumbersome wires and sensors can further prevent the patient from achieving a natural sleep state, which directly affects the accuracy of the results.

[0002] Moreover, PSG technology7is confined to clinical environments due to the need for specialized equipment, which exacerbates the problem. Sleep laboratories are often booked months in advance due to limited bed availability, significantly delaying diagnosis and treatment for patients. This long latency period between symptom onset and diagnosis can lead to worsened sleep conditions and a decline in the patient’s overall health.

[0003] Another major limitation is the reliance on manual interpretation of the data, which is both labor-intensive and time-consuming. Each night of data requires roughly two hours of a professional's time to analyze. Given the rising incidence of sleep disorders, this method is inefficient and strains healthcare resources.

[0004] Perhaps most concerning is that PSG systems are largely unsuitable for home-based or ambulatory use, a critical flaw in today’s era of telemedicine and patient-centric care. The inability to monitor patients in their natural sleep environments diminishes the validity of the data collected, as hospital-induced stress or discomfort can skew results. Home monitoring is becoming increasingly important, as real-world data is often more reflective of a patient’s true sleep patterns. Without portable, user-friendly solutions, current PSG systems and devices fail to meet the growing demand for continuous, real-time, and at-home monitoring.

[0005] In summary7, while PSG remains a cornerstone of sleep disorder diagnosis, it is encumbered by its complex setup, hospital -based limitations, time-consuming data interpretation, and lack of adaptability7for home monitoring. These limitations highlight the urgent need for more advanced, efficient, and patient-friendly sleep monitoring technologies that can keep pace with the growing demand for accurate and accessible diagnostics.Attorney Docket No. 1910-00402BRIEF DESCRIPTION OF DRAWINGS

[0006] These drawings illustrate certain aspects of some examples of the present disclosure and should not be used to limit the disclosure.

[0007] Figure 1 illustrates cunent methods for acquiring biometric sleeping data;

[0008] Figure 2A illustrates the front of flexible bioelectric collection electrode patch;

[0009] Figure 2B illustrates the back of flexible bioelectric collection electrode patch;

[0010] Figure 2C illustrates a horizontal view of flexible bioelectric collection electrode patch;

[0011] Figure 2D illustrates a horizontal view flipped across its vertical axis of flexible bioelectric collection electrode patch;

[0012] Figure 2E illustrates a cross-sectional view of flexible bioelectric collection electrode patch;

[0013] Figure 2F illustrates another cross-sectional view of flexible bioelectric collection electrode patch;

[0014] Figure 3A illustrates detachable housing unit;

[0015] Figure 3B illustrates the top of detachable housing unit comprising signal acquisition circuit board;

[0016] Figure 3C illustrates a side view of detachable housing unit comprising signal acquisition circuit board 306;

[0017] Figure 3D illustrates a side view rotated 90 degrees about its horizontal and vertical axis of detachable housing unit comprising signal acquisition circuit board; and

[0018] Figure 4 illustrates a processing scheme.DETAILED DESCRIPTION

[0019] Methods and systems herein may utilize a flexible bioelectric collection electrode patch, a detachable housing, and a signal acquisition circuit board located within the detachable housing. The flexible bioelectric collection electrode patch may be equipped with a first connector part that enables mechanical and electrical connection with the signal acquisition circuit board. This set up may be less than a minute and sen es very' little to no disruption to sleep cycles. In addition, there is little to no patient discomfort. The patient may feel little to no discomfort as the flexible bioelectric collection electrode patch may be applied for in-home use. The detachable housing may comprise an opening for exposing a second connector part of the signal acquisition circuit board.

[0020] The signal acquisition circuit board may achieve mechanical and electrical connection with the flexible bioelectric collection electrode patch through the cooperation of the first and second connector parts. The signal acquisition circuit board may also comprise an inertial detectionAttorney Docket No. 1910-00402module and an electromyography processing module. The processing may occur in real-time and provide patients with instant results. This also decreases a patient’s time to be diagnosed. In addition, the processing may comprise algorithms for automatized data interpretation. As such, costs are reduced because resources do not have to be allocated for manually interpreting data. Further, real-time biometric data may be acquired in a more convenient and comfortable example. As such, systems and methods herein enable bioelectric and inertial detection of patients and significantly reduces size, providing a comfortable in-home wearing experience which applies state of the real-time automated data processing. This improves the effectiveness of sleep monitoring by allowing for simpler device and less complex measurement capabilities. In addition, in home sleep monitoring may be realized. Further applications may comprise monitoring and controlling Bluetooth capable technologies, such as smart phones, sound systems, air conditioning and heating systems, smell enhancement systems, lighting systems, computers, interface with artificial intelligent platforms, internet of things (loT) systems comprising at least pillow, mattress, aromatherapy device, light, air conditioning, and / or any other electronic or loT device. Additional applications may comprise assistance in the diagnosis and treatment of neural diseases comprising depression, Alzheimer’s, Dementia, and / or the like.

[0021] Figure 1 illustrates current methods for acquiring biometric sleeping data of patient 100. Air flow sensors 102 may be utilized at the nose to measure air flow. However, these sensors are relatively invasive and inhibit patient 100 ability to sleep. In addition, electrodes 104 may be utilized to measure eye and brain movement. For example, scalp electroencephalogram (EEG) signals, and then the circuit board completes the analog-to-digital conversion for further data processing, to be discussed further below. Scalp EEG signals may comprise and kind of signals of brain activity comprising body movements, locational brain activity, extent of brain activity, parameters of sleep quality and determination, and / or the like.

[0022] As illustrated, electrodes 104 must be placed in precise and / or several locations along the head of the patient. These may be uncomfortable for patient 100 and hinder sleep. They also require a trained professional’s expertise to properly implement. This can be time consuming to implement because the cables running from the patient to computer 106 may be heavy and become tangled. This can be difficult and time consuming, hurting the overall process of recording patient 100 sleep. This is merely one example. In addition, data used within the computer of cables running from the patient to computer 106 may be processed manually and / or controlled in some way to another trained professional. Housing information in an onsite location may cause logistical constraints. Wireless techniques, easy to use implementations, electrodes 104 patches as patches, and / or light technology are all utilized herein and not previously before. These examples greatlyAttorney Docket No. 1910-00402reduce the cost and resources required for each patient. A more sophisticated and smaller design may be beneficial.

[0023] Figure 2A illustrates the front of flexible bioelectric collection electrode patch 200, to be placed directly on patient 100 (e.g., referring to Figure 1) forehead. Flexible bioelectric collection electrode patch 200 may comprise electrodes 202 configured to measure current from patient 100 forehead via electrodes 202. The current may be scalp electroencephalogram (EEG) signals, to be discussed further below. Electrodes 202 may be conductive hydrogel electrodes with high conductivity and viscosity. An electrode hydrogel may be a type of soft, flexible, and electrically conductive material made primarily of water and a polymer matrix. It is used to establish a stable electrical connection between an electronic device and biological tissues, such as skin, muscles, or the brain. The hydrogel component provides softness and flexibility, while the conductive properties allow it to transmit electrical signals. In addition, electrode 202 may act as a conductor of scalp EEG signals to conductor 204.

[0024] Figure 2A illustrates one example of four electrodes 202 in an orientation, however, any number of electrodes 202 may apply. Current may then flow from the electrodes 202 to conductors 204. Conductors 204 may be a printed silver paste circuit and flexible to stay in place with flexible bioelectric collection electrode patch 200. Electrodes 202 may be printed onto insulator 206 at 70-100 degrees Celsius for low temperature dr ing. In examples, electrodes 202 may be disposed on top of insulator 206. In other examples, electrodes 202 may be disposed partially on top and within insulator 206, partially behind and within insulator 206, within insulator 206, and / or behind insulator 206. The produced current on conductors 204 may be transmitted to a first connector 208, illustrated on the back of flexible bioelectric collection electrode patch 200. Signals from electrodes 202 may be utilized to measure eye and brain movement and activity. For example, scalp electroencephalogram (EEG) signals, and then the circuit board completes the analog-to-digital conversion for further data processing, to be discussed further below. Scalp EEG signals may comprise and kind of signals of brain activity7comprising body movements, locational brain activity, extent of brain activity', parameters of sleep quality and determination, and / or the like. In addition, signals from electrode 202 may comprise inertial measurement unit (IMU) measurements. In other examples, an actual IMU may be utilized to record measurements. In any example, IMU measurements may comprise any form of body movement comprising eye fluctuation, heart rate, blood pressure, respiratory7rate, body temperature, oxygen saturation, and / or the like. IMU measurements may also be taken by electronic devices comprising wearable watches, remote sensors, any wearable electronic device, and / or any form of artificial intelligence interfaces.Attorney Docket No. 1910-00402

[0025] Figure 2A illustrates one example of one orientation of electrodes 202 and conductors 204. Any other physical embodiment may be possible as well. In effect flexible bioelectric collection electrode patch 200 may not comprise any solid state sensor in direct or indirect contact with the skin, instead only hydrogel may be in direct contact the skin. In examples, electrode 202 may be a sticky conductive hydrogel that may be directly attached to the forehead.

[0026] Figure 2B illustrates the back of flexible bioelectric collection electrode patch 200. As discussed above, current from electrodes 202 may be transmitted to first connector 208. In examples, first connector 208 may be disposed within and / or on flexible bioelectric collection electrode patch 200. Insulator 206 may insulate current and allow flow between electrodes 202 and conductors 204 without great leakage or addition of current. Insulator 206 may provide structure and support for flexible bioelectric collection electrode patch 200. In examples, insulator 206 may be a soft leather or non-woven fabric. Second connector 210 may comprise each measurement from every7electrode 202 within a copper core 280. The current and / or measurements collected at copper core 280 disposed within second connector 210 may be transferred to a signal acquisition circuit board, to be discussed below. In addition, first connector 208 may be configured to connect flexible bioelectric collection electrode patch 200 to detachable housing, to be discussed below.

[0027] Further, characterized in that the first connector part and the second connector part are fixed together through magnetic attraction, characterized in that the second connector part includes magnetic connection points and pogo pin contacts, with the pogo pin contacts located between and aligned with the two magnetic connection points. The second connector part further includes a plastic body, with the magnetic connection points and pogo pin contacts fixed to the plastic body, the flexible bioelectric collection electrode patch employs silver paste or copper foil circuit printed on a non-woven flexible substrate or uses silver paste spraying technology to form the signal collection electrode and signal transmission circuit on the non-woven fabric. The flexible bioelectric collection electrode patch may be integrally combined with hydrogel.

[0028] Figure 2C illustrates a horizontal view of flexible bioelectric collection electrode patch 200. Figure 2D illustrates a horizontal view of flexible bioelectric collection electrode patch 200 flipped across its vertical axis. Figure 2E illustrates a cross-sectional view of flexible bioelectric collection electrode patch 200. Figure 2F illustrates a cross-sectional view of flexible bioelectric collection electrode patch 200 flipped across its horizontal axis. First connector 208 and in examples, second connector 210 may be connected to a detachable housing unit.

[0029] Figure 3A illustrates detachable housing unit 300. In examples, detachable housing unit 300 may be mechanically and / or electrically' coupled to first connector 208 and second connector 210 via slots 302. Nodes 304 may be configured to accept current from electrodes 202 viaAttorney Docket No. 1910-00402conductor 204 and first connector 208, as discussed above. In examples, there may be any number of nodes 304 for any number of electrodes 202. In addition, slots 302 may hold flexible bioelectric collection electrode patch 200 (e.g., referring to Figure 2) and be configured to accept transmitted current from electrodes 202 via any means. Detachable housing unit 300 may comprise a signal acquisition circuit board, to be discussed below.

[0030] In addition, the detachable housing also contains a battery’ electrically connected to the signal acquisition circuit board, a base and a face cover detachably connected to the base, with the base having multiple mounting holes for installing the signal acquisition circuit board. A signal amplification and filtering module electrically connected to the electromyography processing module, an analog-to-digital converter electrically connected to the signal amplification and filtering module, a microprocessor electrically connected to the analog-to-digital converter and the inertial detection module, and a wireless communication module electrically connected to the microprocessor.

[0031] Figure 3B illustrates the top of detachable housing unit 300 comprising signal acquisition circuit board 306. Signal acquisition circuit board 306 may receive and process current from electrodes 202. In examples, the transmission from electrodes 202 to signal acquisition circuit board 306 may be: to conductor 204, to first connector 208, to nodes 304, and then to signal acquisition circuit board 306. Then, the raw data, which is transmitted as a voltage waveform, not image, may be sent to an analog-to-digital converter and converted. The digital signal is then sent to many locations. In an example, one location may comprise to a mobile app via Bluetooth. To be discussed below, the processed measurements may be transmitted to at least a processing unit.

[0032] Figure 3C illustrates a side view of detachable housing unit 300 comprising signal acquisition circuit board 306. Figure 3D illustrates a side view rotated 90 degrees about its horizontal and vertical axis of detachable housing unit 300 comprising signal acquisition circuit board 306.

[0033] In other examples, flexible bioelectric collection electrode patch 200 (e.g., referring to Figure 2) and detachable housing unit 300 (e.g., referring to Figure 3) with all the components described above, may be referred to as a miniaturized wireless Bluetooth bioelectric and inertial monitoring device. The wireless Bluetooth bioelectric and inertial monitoring device may have Bluetooth capabilities. It may also comprise a flexible bioelectric collection electrode patch, detachable housing unit 300, and a signal acquisition circuit board located within the detachable housing unit 300. The flexible bioelectric collection electrode patch may be equipped with a first connector part that enables mechanical and electrical connection with the signal acquisition circuit board. The detachable housing may be provided with an opening for exposing a second connectorAttorney Docket No. 1910-00402part of the signal acquisition circuit board, and the signal acquisition circuit board achieves mechanical and electrical connection with the flexible bioelectric collection electrode patch through the cooperation of the first and second connector parts. The signal acquisition circuit board is equipped with at least an inertial detection module and an electromyography processing module.

[0034] The miniaturized wireless Bluetooth bioelectric and inertial monitoring device may be characterized in that both the first connector part and the second connector part are equipped with contact points for electrical connection and in that the first connector part, the second connector part are fixed together through magnetic attraction, and in that the second connector part includes magnetic connection points and pogo pin contacts, with the pogo pin contacts located between and aligned with the two magnetic connection points. Further, the detachable housing may also contain a battery electrically connected to the signal acquisition circuit board, includes a base and a face cover detachably connected to the base, with the base having multiple mounting holes for installing the signal acquisition circuit board. Additionally, the second connector part may further comprise a plastic body, with the magnetic connection points and pogo pin contacts fixed to the plastic body.

[0035] Additionally, the flexible bioelectric collection electrode patch employs silver paste or copper foil circuit printed on a non-woven flexible substrate or uses silver paste spraying technology to form the signal collection electrode and signal transmission circuit on the non-woven fabric. The flexible bioelectric collection electrode patch is integrally combined with hydrogel. Finally, the signal acquisition circuit board is further equipped with a signal amplification and filtering module electrically connected to the electromyography processing module, an analog-to-digital converter electrically connected to the signal amplification and filtering module, a microprocessor electrically connected to the analog-to-digital converter and the inertial detection module, and a wireless communication module electrically connected to the microprocessor.

[0036] Figure 4 illustrates processing interface 400. As discussed above, raw data may be converted to a digital signal within signal acquisition circuit board 306. Tn examples, the digital signal may be transmitted via communication lines 430 and / or 432 to adaptive processor 402 and application on personal device 410, respectively. In examples, communication lines 430 and 432 may be any wired or wireless communication. Wireless communications may comprise Bluetooth, Radio Frequency Identification (RFID), any networking data transfer, and / or the like. Further, nondigitized raw data and / or digitized signals may be communicated to adaptive processor 402 and / or application on personal device 410 via communication lines 430 and 432. Once received at adaptive processor 402,

[0037] Adaptive processor 402 may comprise control unit 404, arithmetic logic unit (ALU) 406, and register 408. In examples, adaptive processor is a physical processor or a cloud-basedAttorney Docket No. 1910-00402processor with one or more locations. Control unit 404 may acquire algorithms to use for processing. In examples, algorithms may comprise machine learning and classification algorithms. Machine learning and classification algorithms may receive patient’s EEG and IMU measurements in the form of non-digitized raw data and / or digitized signals may be used to produce a sleep report. In examples, feature recognition and classification based on American Academy of Sleep Medicine (AASM) and create some indexes. EEG and IMU combined may yield unique indices, such as Brain Recovery Index, Sleep Demand Dispersal Index, Sleep Memory Consolidation Index, Sleep Immersion Index, Sleep Stability Index etc. All these indices may be defined. In examples, an algorithm may be executed on the data after the screen splitting of SI to obtain a sleep stage prediction for each screen, and four staging parameters, namely, waking time, light sleep time (N1 stage + N2 stage), deep sleep time and rapid eye movement sleep time, are further calculated. The algorithm model may be a deep neural network model obtained through a certain amount of labeled data training. Labeled training data may be pre-defined and / or previously processed data or it may be synthetic modeled data. In other examples, initially EEG and IMU data may be stored on an application on personal device 410 (to be discussed in Figure 4 below) in any format. Upon clicking the report generation button, the data files may be uploaded to multi component networking server or a local server. Subsequently, cloud-based and / or local algorithms may compute the results. The results may then be returned to application on personal device 410 to generate a comprehensive sleep report, to be discussed below.

[0038] In examples, an algorithm may be based on a single-channel sleep staging algorithm. Where each stage is divided through the course of one or more sleeping cycle into different time periods. The EEG signal is input into a lightw eight Convolutional neural network (CNN)- Long short-term memory (LSTM) model for sleep scoring, where CNN may be used for representation learning and LSTM for sequence learning. A CNN is a deep learning model designed for processing structured grid data like images, where it automatically detects patterns and features through layers of convolution and pooling. It excels at tasks like image classification, object detection, and facial recognition by learning spatial hierarchies. An LSTM is a ty pe of recurrent neural network (RNN) designed to capture long-range dependencies in sequential data by using gates to regulate the flow of information. It excels at tasks like time series prediction and natural language processing by maintaining context over long sequences.

[0039] The LSTM may score each stage based on the quality7, length, and any other EEG or IMU measurements. By measuring and analyzing signal quality, body position, and IMU-based sleep staging, the EEG sleep staging may be optimized w hile each stage is computed. Then, the aggregate of each stage may form the whole sleep report. The sleep report may be generated over the courseAttorney Docket No. 1910-00402of one night or multiple nights. The sleep report may convey a pattern unique for every patient 100 (e.g.. referring to Figure 1).

[0040] The outputs of algorithms and indices may be sent to application on personal device 410 via communication line 434. In addition, user inputs from application on personal device 410 may be received via communication 436. Examples of inputs may be requests for more detailed breakdowns of specific times in the night of a sleep report, tracking breathing heart rates in different periods, and / or the like. User inputs may prompt / initiate control unit 404 to alter algorithms or apply new recognition and classification algorithms.

[0041] ALU 406 may operate the algorithms described above. Register 408 may store EEG and IMU measurements in the form of non-digitized raw data and / or digitized signals and / or outputs of the algonthms described above. As discussed above, application on personal device 410 may receive EEG and IMU measurements in the form of non-digitized raw data and / or digitized signals via communication lines 432. In examples, application on personal device 410 may perform the same functions as control unit 404, arithmetic logic unit (ALU) 406, and register 408 in addition to user inputs as discussed above. Further, application on personal device 410 may provide an interface. An interface may allow users to access and interact with outputs from the algorithms discussed above. The interface of application on personal device 410 may be designed for any form of a computer, desktop, laptop, tablet, smartphone, or any other electronic device. In examples, application on personal device 410 may be accessed by health care providers and / or patients.

[0042] The systems and methods may comprise any of the various features disclosed herein, comprising one or more of the following statements.

[0043] Statement 1: A device comprising: a flexible bioelectric collection electrode patch; a detachable housing; and a signal acquisition circuit board located within the detachable housing, wherein the flexible bioelectric collection electrode patch is equipped with a first connector part that enables mechanical and electrical connection with the signal acquisition circuit board, wherein the detachable housing is provided with an opening for exposing a second connector part of the signal acquisition circuit board, and the signal acquisition circuit board achieves mechanical and electrical connection with the flexible bioelectric collection electrode patch through a cooperation of the first and second connector parts, and wherein the signal acquisition circuit board is equipped with at least an inertial detection module and an electromyography processing module.

[0044] Statement 2: The device of statement 1, wherein the first connector part and the second connector part are equipped with contact points for electrical connection.

[0045] Statement 3: The device of statement 2, wherein the first connector part and the second connector part are fixed together through magnetic attraction.Attorney Docket No. 1910-00402

[0046] Statement 4: The device of statement 3, wherein the second connector part includes magnetic connection points and pogo pin contacts, with the pogo pin contacts located between and aligned with two magnetic connection points.

[0047] Statement 5: The device of statement 1, wherein the detachable housing comprises a battery electrically connected to the signal acquisition circuit board.

[0048] Statement 6: The device of statement 1, wherein the detachable housing comprises a base and a face cover detachably connected to the base, with the base having multiple mounting holes for installing the signal acquisition circuit board.

[0049] Statement 7 : The device of statement 4, wherein the second connector part further includes a plastic body, with the magnetic connection points and pogo pin contacts fixed to the plastic body.

[0050] Statement 8: The device of statement 1, wherein the flexible bioelectric collection electrode patch employs silver paste or copper foil circuit printed on a non-woven flexible substrate or uses silver paste spraying technology to form a signal collection electrode and signal transmission circuit on a non-woven fabric.

[0051] Statement 9: The device according of statement 1, wherein the flexible bioelectric collection electrode patch is integrally combined with hydrogel.

[0052] Statement 10: The device of statement 1, wherein the signal acquisition circuit board is further equipped with a signal amplification and filtering module electrically connected to the electromyography processing module, an analog-to-digital converter electrically connected to the signal amplification and filtering module, a microprocessor electrically connected to the analog-to-digital converter and the inertial detection module, and a wireless communication module electrically connected to the microprocessor.

[0053] Statement 11 : A method comprising: receiving an electroencephalogram (EEG) signal with an electrode; transmitting the EEG signal to a processor or application on a device; and computing a sleep report from the EEG signal.

[0054] Statement 12: The method of statement 11, wherein the EEG signal is processed on a signal acquisition circuit board before it is transmitted to the processor or the application on the device.

[0055] Statement 13: The method of statement 12 further comprising processing the EEG signal into a digital signal with an analog-to-digital converter disposed on the signal acquisition circuit board.

[0056] Statement 14: The method of statement 11, wherein computing the sleep report comprises an algorithm disposed on a processor or application on a device.

[0057] Statement 15: The method of statement 14, wherein the algorithm is a deep neural network model obtained through a certain amount of labeled data training.Attorney Docket No. 1910-00402

[0058] Statement 16: The method of statement 15, wherein labeled training data is pre-defined, previously processed data, and / or synthetic modeled data.

[0059] Statement 17: The method of statement 14, wherein the algorithm is a single-channel sleep staging algorithm comprising one or more stages.

[0060] Statement 18: The method of statement 17, wherein each stage is divided through a course of one or more sleeping cycle into different time periods.

[0061] Statement 19: The method of statement 18, wherein EEG signal is input into the singlechannel sleep staging algorithm, and wherein the single-channel sleep staging algorithm comprises a lightweight CNN (Convolutional neural network) and a long short-term memory model (LSTM), and wherein CNN is be used for representation learning and LSTM for sequence learning.

[0062] Statement 20: The method of statement 11, further comprising receiving an inertial measurement unit (IMU) with a wearable electronic device.

[0063] As it is impracticable to disclose every conceivable embodiment of the technology described herein, the figures, examples, and description provided herein disclose only a limited number of potential embodiments. A person of ordinary skill in the art would appreciate that any number of potential variations or modifications may be made to the explicitly disclosed embodiments, and that such alternative embodiments remain within the scope of the broader technology. Accordingly, the scope should be limited only by the attached claims. Further, the compositions and methods are described in terms of "comprising." "containing," or "including" various components or steps, the compositions and methods may also "consist essentially of' or "consist of the various components and steps. Moreover, the indefinite articles "a" or "an," as used in the claims, are defined herein to mean one or more than one of the elements that it introduces. Certain technical details, known to people of ordinary' skill in the art, may be omitted for brevity and to avoid cluttering the description of the novel aspects.

[0064] For further brevity, descriptions of similarly named components may be omitted if a description of that similarly named component exists elsewhere in the application. Accordingly, any component described with respect to a specific figure may be equivalent to one or more similarly named components shown or described in any other figure, and each component incorporates the description of every similarly named component provided in the application (unless explicitly noted otherwise). A description of any component is to be interpreted as an optional embodiment — which may be implemented in addition to, in conjunction with, or in place of an embodiment of a similarly-named component described for any other figure.

[0065] As used herein, adjective ordinal numbers (e.g., first, second, third, etc.) are used to distinguish between elements and do not create any particular ordering of the elements. As anAttorney Docket No. 1910-00402example, a "first element" is distinct from a "second element", but the "first element" may come after (or before) the "second element" in an ordering of elements. Accordingly, an order of elements exists only if ordered terminology is expressly provided (e.g., "before", "between", "after", etc.) or a t pe of "order" is expressly provided (e.g., "chronological", "alphabetical", "by size", etc.). Further, use of ordinal numbers does not preclude the existence of other elements. As an example, a "table with a first leg and a second leg" is any table with two or more legs (e.g., two legs, five legs, thirteen legs, etc.). A maximum quantity of elements exists only if express language is used to limit the upper bound (e.g., "two or fewer", "exactly five", "nine to twenty", etc.). Similarly, singular use of an ordinal number does not imply the existence of another element. As an example, a "first threshold" may be the only threshold and therefore does not necessitate the existence of a "second threshold".

[0066] As used herein, the word "data" may be used as an "uncountable" singular noun — not as the plural form of the singular noun "datum". Accordingly, throughout the application, "data" is generally paired with a singular verb (e.g., "the data is modified"). However, "data" is not redefined to mean a single bit of digital information. Rather, as used herein, "data" means any one or more bit(s) of digital information that are grouped together (physically or logically). Further, "data" may be used as a plural noun if context provides the existence of multiple "data" (e.g., "the two data are combined").

[0067] As used herein, the term "operative connection" (or "operatively connected") means the direct or indirect connection between devices that allows for interaction in some way (e.g., via the exchange of information). For example, the phrase 'operatively connected' may refer to a direct connection (e.g., a direct wired or wireless connection between devices) or an indirect connection (e.g., multiple wired and / or wireless connections between any number of other devices connecting the operatively connected devices).

[0068] As used herein, indefinite articles "a" and "an" mean "one or more". That is, the explicit recitation of " an" element does not preclude the existence of a second element, a third element, etc. Further, definite articles (e g., "the", "said") mean "any one of' (the "one or more" elements) when referring to previously introduced element(s). As an example, there may exist "a processor", where such a recitation does not preclude the existence of any number of other processors. Further, "the processor receives data, and the processor processes data" means "any one of the one or more processors receives data" and "any one of the one or more processors processes data". It is not required that the same processor both (i) receive data and (ii) process data. Rather, each of the steps ("receive" and "process") may be performed by different processors.

Claims

Attorney Docket No. 1910-00402CLAIMSWhat is claimed is:

1. A device comprising:a flexible bioelectric collection electrode patch;a detachable housing; anda signal acquisition circuit board located within the detachable housing, wherein the flexible bioelectric collection electrode patch is equipped with a first connector part that enables mechanical and electrical connection with the signal acquisition circuit board, wherein the detachable housing is provided with an opening for exposing a second connector part of the signal acquisition circuit board, and the signal acquisition circuit board achieves mechanical and electrical connection with the flexible bioelectric collection electrode patch through a cooperation of the first and second connector parts, and wherein the signal acquisition circuit board is equipped with at least an inertial detection module and an electromyography processing module.

2. The device of claim 1, wherein the first connector part and the second connector part are equipped with contact points for electrical connection.

3. The device of claim 2, wherein the first connector part and the second connector part are fixed together through magnetic attraction.

4. The device of claim 3, wherein the second connector part includes magnetic connection points and pogo pin contacts, with the pogo pin contacts located between and aligned with tw o magnetic connection points.

5. The device of claim 1 , wherein the detachable housing comprises a battery’ electrically connected to the signal acquisition circuit board.

6. The device of claim 1, wherein the detachable housing comprises a base and a face cover detachably connected to the base, with the base having multiple mounting holes for installing the signal acquisition circuit board.

7. The device of claim 4, wherein the second connector part further includes a plastic body, with the magnetic connection points and pogo pin contacts fixed to the plastic body.Attorney Docket No. 1910-004028. The device of claim 1, wherein the flexible bioelectric collection electrode patch employs silver paste or copper foil circuit printed on a non-woven flexible substrate or uses silver paste spraying technology to form a signal collection electrode and signal transmission circuit on a non-woven fabric.

9. The device according of claim 1. wherein the flexible bioelectric collection electrode patch is integrally combined with hydrogel.

10. The device of claim 1, wherein the signal acquisition circuit board is further equipped with a signal amplification and filtering module electrically connected to the electromyography processing module, an analog-to-digital converter electrically connected to the signal amplification and filtering module, a microprocessor electrically connected to the analog-to-digital converter and the inertial detection module, and a wireless communication module electrically connected to the microprocessor.

11. A method comprising:receiving an electroencephalogram (EEG) signal with an electrode;transmitting the EEG signal to a processor or application on a device; andcomputing a sleep report from the EEG signal.

12. The method of claim 11, wherein the EEG signal is processed on a signal acquisition circuit board before it is transmitted to the processor or the application on the device.

13. The method of claim 12 further comprising processing the EEG signal into a digital signal with an analog-to-digital converter disposed on the signal acquisition circuit board.

14. The method of claim 11, wherein computing the sleep report comprises an algorithm disposed on a processor or application on a device.

15. The method of claim 14, wherein the algorithm is a deep neural network model obtained through a certain amount of labeled data training.

16. The method of claim 15, wherein labeled training data is pre-defined, previously processed data, and / or synthetic modeled data.Attorney Docket No. 1910-0040217. The method of claim 14, wherein the algorithm is a single-channel sleep staging algorithm comprising one or more stages.

18. The method of claim 17, wherein each stage is divided through a course of one or more sleeping cycle into different time periods.

19. The method of claim 18, wherein EEG signal is input into the single-channel sleep staging algorithm, and wherein the single-channel sleep staging algorithm comprises a lightweight CNN (Convolutional neural network) and a long short-term memory model (LSTM). and wherein CNN is be used for representation learning and LSTM for sequence learning.

20. The method of claim 11, further comprising receiving an inertial measurement unit (IMU) with a wearable electronic device.

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