Systems and methods for multivariate stroke detection

Abstract

The system for detecting abnormal events of a person includes a body in contact with a skin surface of the person; a heat source for heating the skin surface to a target temperature; a skin temperature sensor for measuring the temperature of the skin surface in contact with the heat source; a blood volume sensor for measuring the blood volume of the skin surface; and a hardware processor, which is communicatively connected to the heat source, the blood volume sensor, the skin temperature sensor, and the ambient temperature sensor. The hardware processor is configured to receive a baseline blood volume signal, output a heating signal to the heat source to start a heating cycle, receive a second blood volume signal from the blood volume sensor, compare the second blood volume signal with the baseline blood volume signal, and determine whether an abnormal biological event has occurred.

Description

[0001] Incorporated by Reference

[0002] This application claims priority to U.S. Provisional Patent Application No. 62 / 915,269 filed on October 15, 2019 and U.S. Provisional Patent Application No. 63 / 053,265 filed on July 17, 2020. Each provisional patent application is hereby incorporated by reference in its entirety and constitutes a part of the present disclosure. Any features, structures, materials, methods, or steps described and / or shown in any embodiment of the foregoing provisional patent applications may be used together with or substituted for any features, structures, materials, methods, or steps described in the following paragraphs of the present specification and / or shown in the accompanying drawings. Technical Field

[0003] The present disclosure relates generally to the field of disease detection and, more particularly, to stroke detection. Background Art

[0004] A stroke is the result of brain tissue dying as a result of an interruption in blood flow to the brain. An ischemic stroke occurs when there is a blockage in blood flow to the brain, usually due to a blood clot. A hemorrhagic stroke occurs when a blood vessel in the brain ruptures, causing bleeding into brain tissue and surrounding spaces.

[0005] There are many physiological symptoms of a stroke that vary depending on the location of the affected tissue. Early symptoms of a progressive stroke may be able to decrease or even resolve if blood flow disruption is resolved quickly before tissue has died. One type of symptom is visual disruption, including blurring, dimming (often likened to a curtain falling), or even complete loss of vision. Stroke patients also often experience eye deviation or difficulty tracking the eyes.

[0006] Just as a stroke can affect the parts of the brain associated with vision, it can also affect the parts of the brain associated with language, comprehension, and communication. People who suffer a stroke may exhibit slurred or jumbled speech that makes them unintelligible.

[0007] Another common symptom of a stroke is weakness on one side of the body. This can manifest as partial or complete paralysis of one side of the face, one arm, one leg, or the entire side of the body.

[0008] Ischemic strokes are the most common type of stroke and are usually painless when experienced, but hemorrhagic strokes are very painful and are often described as "the worst headache of my life" that comes on suddenly. Often, many people's headaches are accompanied by feelings of dizziness, nausea, and vomiting. Smell and taste can also be affected during a stroke.

[0009] Anything that affects the brain, from trauma to a stroke, can cause cognitive impairment. Sometimes a feeling of confusion or constant second-guessing about a person's actions occurs in the days before a stroke.

[0010] Another common symptom of stroke is the sudden onset of weakness.

[0011] The duration of stroke symptoms can vary and occur with or without pain, which can make stroke detection difficult. In addition, strokes can occur during sleep, making detection even more difficult. If a stroke does occur while a person is sleeping, the person may not be awakened immediately. As a result, when the patient wakes up with symptoms, it is unclear whether the stroke has just begun or has already occurred during sleep.

[0012] If a stroke is detected and the patient seeks care quickly, there are many evidence-based interventions that can significantly reduce death and disability caused by this disease. In severe ischemic stroke, every minute of delay in restoring blood flow is equivalent to one week of disability-adjusted life year (DALY) lost. Despite the availability of these treatments, less than 20% of patients receive them. Even in patients who do receive intervention, outcomes are often suboptimal because of the delay in intervention. Stroke detection is difficult because strokes often do not hurt, mimic other health events, and have a variety of manifestations. Improvements in the detection and care of stroke attacks can significantly reduce death and disability associated with the disease.

[0013] Like stroke, COVID-19 has been shown to have a variety of symptoms, many of which mimic those of neurologic disease. Recent publications show early evidence of encephalopathy, inflammatory CNS syndrome, ischemic stroke, and peripheral neuropathy in patients treated for COVID-19. (Zubair, JAMA Neurology, 2020) With the majority of COVID-19 patients being managed remotely, and a significant percentage of hospitalized patients requiring invasive ventilation, monitoring for overt symptoms of neurologic disruption may be difficult. Therefore, improvements in remote monitoring and care for patients with COVID-19 could significantly reduce death and disability associated with the disease. SUMMARY OF THE INVENTION

[0015] One aspect of the present disclosure relates to a wearable system for detecting abnormal biological events of a person. The system includes a body having a first surface opposite to a second surface in contact with a skin surface of the person; a thermal stimulus source, such as a heat source or a Peltier cooler in communication with the skin surface, so that the heat source is configured to heat the skin surface to a target temperature; a skin temperature sensor, which is positioned on the second surface and configured to measure the temperature of the skin surface in contact with the heat source; a blood volume sensor, which is positioned on the second surface and configured to measure the blood volume of the skin surface; and a hardware processor, which is communicatively connected to the heat source, the blood volume sensor, the skin temperature sensor, and the ambient temperature sensor, the ambient temperature sensor being configured to measure the temperature of the environment surrounding the wearable system. The hardware processor is configured to receive a baseline blood volume signal from the blood volume sensor; output a heating signal to the heat source to start a heating cycle so that the heating cycle includes heating the skin surface to the target temperature; receive a second blood volume signal from the blood volume sensor in response to the skin surface reaching the target temperature; compare the second blood volume signal with the baseline blood volume signal; and determine whether an abnormal biological event has occurred based on the comparison.

[0016] In some embodiments, the second blood volume signal comprises a set of blood volume signals such that the blood volume at the skin surface is repeatedly measured before, during, and after a heating cycle of the heat source. In some embodiments, the second blood volume signal comprises a plurality of blood volume signals such that the blood volume at the skin surface is continuously measured before, during, and after a heating cycle of the heat source.

[0017] In some embodiments, the hardware processor is further configured to receive a second blood volume signal after the target temperature is reached, after a predetermined period of time has expired, or after one or more heating cycles have ended.

[0018] In some embodiments, comparing the second blood volume signal to the baseline blood volume signal includes calculating a baseline ratio of alternating current (AC) to direct current (DC) of the baseline blood volume signal and a second ratio of AC to DC of the second blood volume signal, and comparing the baseline ratio to the second ratio.

[0019] In some embodiments, the ambient temperature sensor is positioned on a first side of the body of the wearable system.

[0020] In some embodiments, the system further comprises a remote computing device in communication with the wearable system, the remote computing device comprising an ambient temperature sensor. In some embodiments, the remote computing device comprises one of a laptop computer, a cellular device, a workstation, a server, a desktop computer, a personal digital assistant, a second wearable system or device, or a netbook.

[0021] In some embodiments, the heat source is positioned on the second surface of the body.

[0022] In some embodiments, the hardware processor is further configured to receive a baseline temperature signal from the skin temperature sensor and the ambient temperature sensor, determine a target temperature based on the baseline temperature signal, and determine whether the target temperature is below a maximum temperature value.

[0023] In some embodiments, the hardware processor is further configured to cycle the heat source to maintain the target temperature.

[0024] In some embodiments, the system further includes one or more electrodermal activity sensors positioned on the second surface.

[0025] In some embodiments, the one or more electrodermal activity sensors are spaced apart from the heating element by about 0.25 inches to about 4 inches.

[0026] In some embodiments, the system also includes one or more motion sensors configured to measure movement of a body part connected to the wearable system.

[0027] In some embodiments, the first surface and the second surface define a cavity therebetween to provide airflow between the first surface and the second surface.

[0028] In some embodiments, the hardware processor resides on or within the first surface.

[0029] In some embodiments, a cavity defined by the first surface and the second surface physically separates a heat source from a hardware processor on or within the first surface.

[0030] In some embodiments, the cavity defined by the first surface and the second surface has a sufficient volume to facilitate cooling of the heat source between heating cycles.

[0031] In some embodiments, the abnormal biological event comprises a stroke event.

[0032] In some embodiments, a wearable system is positioned on a left limb of a user and a second wearable system is positioned on a right limb of the user, wherein the second wearable system includes a second heating element, a second skin temperature sensor, and a second blood volume sensor, wherein the hardware processor is further configured to compare the right blood volume signal to the left blood volume signal to determine whether an abnormal biological event has occurred.

[0033] In some embodiments, the hardware processor is further configured to synchronize the signals received from the left limb and the right limb in time; and compare the synchronized signals from the left limb and the right limb to determine whether an abnormal biological event occurs. In some embodiments, the comparison takes into account the baseline difference between the left limb and the right limb.

[0034] In some embodiments, the system further comprises a tensionable strap coupled to the body. In some embodiments, the tensionable strap further comprises a visual indicator to indicate when one or more of the heating element, the skin temperature sensor, the blood volume sensor, or a combination thereof is sufficiently connected to the skin surface to enable accurate sensor readings. In some embodiments, one or more ends of the tensionable strap are connected to the body at a position centered relative to the one or more sensors located on the second surface.

[0035] In some embodiments, the heat source is concentrically positioned around one or both of the blood volume sensor and the skin temperature sensor.

[0036] In some embodiments, the blood volume sensor comprises a photoplethysmographic sensor or an impedance plethysmographic sensor.

[0037] In some embodiments, the skin temperature sensor comprises a thermocouple, a resistance temperature detector, a thermistor, or an infrared temperature sensor.

[0038] In some embodiments, the system further includes a support structure coupled to the heat source and configured to couple the heat source to the second surface and at least partially expose the heat source to the cavity.

[0039] In some embodiments, the blood volume sensor is further configured to measure one or more of heart rate, heart rate variability, or oxygen saturation.

[0040] In some embodiments, the target temperature is personalized to the user. In some embodiments, the personalization of the target temperature includes receiving user input related to the perceived temperature of the skin surface. In some embodiments, the personalization of the target temperature is based on a signal received from a blood volume sensor.

[0041] In some embodiments, the heat source includes one of a heating element or ambient temperature.

[0042] Another aspect of the present invention relates to a wearable system for detecting abnormal biological events of a person. The system includes a body having a first surface opposite to a second surface in contact with a skin surface of a person, the first surface and the second surface defining a cavity therebetween to provide airflow between the first surface and the second surface; a heating element positioned on the second surface and configured to heat the skin surface for a predetermined period of time; a skin temperature sensor positioned on the second surface and configured to measure the temperature of the skin surface in contact with the heating element; a blood volume sensor positioned on the second surface and configured to measure the blood volume of the skin surface; and a hardware processor communicatively connected to the heating element, the blood volume sensor, the skin temperature sensor, and an ambient temperature sensor, the ambient temperature sensor being configured to measure the temperature of the environment surrounding the wearable system.

[0043] The hardware processor is configured to receive a baseline blood volume signal from the blood volume sensor; output a heating signal to the heating element to initiate a heating cycle, such that the heating cycle includes heating the skin surface to a target temperature; receive a second blood volume signal from the blood volume sensor in response to the skin surface reaching the target temperature; compare the second blood volume signal with the baseline blood volume signal; and determine whether an abnormal biological event has occurred based on the comparison.

[0044] Another aspect of the present invention relates to a wearable system for detecting abnormal biological events of a person. The system includes a body having a first surface opposite to a second surface in contact with a skin surface of a person; a heat source in communication with the skin surface, such that the heat source is configured to heat the skin surface to a target temperature; a skin temperature sensor positioned on the second surface and configured to measure the temperature of the skin surface in contact with the heat source; a sensor positioned on the second surface and configured to measure a parameter of interest of the person; and a hardware processor communicatively connected to the heat source, the sensor, the skin temperature sensor, and an ambient temperature sensor, the ambient temperature sensor being configured to measure the temperature of the environment surrounding the wearable system.

[0045] The hardware processor is configured to receive a baseline sensor signal from the sensor; output a heating signal to the heat source to initiate a heating cycle, wherein the heating cycle includes heating the skin surface to the target temperature; receive a second sensor signal from the sensor in response to the skin surface reaching the target temperature; compare the second sensor signal with the baseline sensor signal; and determine whether an abnormal biological event has occurred based on the comparison.

[0046] In some embodiments, the sensor is selected from a stretch sensor, a skin electrodermal activity sensor, an electrocardiogram sensor, a camera, or a blood volume sensor.

[0047] In some embodiments, the parameters of interest include one or more of blood pressure, heart rate, heart rate variability, gaze, facial expression, skin conductance response, vasodilation response, or dilation response.

[0048] BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The above is an overview and is therefore necessarily limited in detail. The above aspects and other aspects, features and advantages of the present technology are described below in conjunction with various embodiments with reference to the accompanying drawings.

[0050] Figure 1A One embodiment of a multivariate system for stroke detection is shown.

[0051] Figure 1B Another embodiment of a multivariate system for stroke detection is shown.

[0052] Figure 2 Displays blood pressure and pulse of various parts of the body.

[0053] Figure 3 One embodiment of a wearable device for stroke detection is shown.

[0054] Figure 4 Another embodiment of a wearable device for stroke detection is shown.

[0055] Figure 5 It is shown that when the wearable device moves, the plane of action also moves, causing the accelerometer to track the changes in the plane and adjust the movement in three dimensions accordingly.

[0056] Figure 6 The measurement of azimuth, roll and pitch angles by accelerometers is shown.

[0057] Figure 7 One embodiment of a data capture workflow involving motion data measurements (eg, acceleration) is shown.

[0058] Figure 8 One embodiment of a workflow for calculating a tremor metric from captured acceleration data is shown.

[0059] Fig. 9 A graphical representation of acceleration data analyzed using an application on a computing device is shown.

[0060] Fig.10 A graphical representation of distance data analyzed using an application on a computing device is shown.

[0061] Fig.11 A graphical representation of movement data analyzed using an application on a computing device is shown.

[0062] Fig.12 One embodiment of a system for detecting symmetric limb movements is shown.

[0063] Fig.13 One embodiment of a system for detecting asymmetric limb movements is shown.

[0064] Fig.14 Another embodiment of a system for detecting asymmetric limb movements is shown.

[0065] Fig.15 Another embodiment of a system for detecting symmetric limb movements is shown.

[0066] Fig.16 Another embodiment of a system for detecting asymmetric limb movements is shown.

[0067] Fig.17 Another embodiment of a system for detecting asymmetric limb movements is shown.

[0068] Fig.18 Another embodiment of a system for detecting symmetric limb movements is shown.

[0069] Fig.19 Another embodiment of a system for detecting asymmetric limb movements is shown.

[0070] Fig. 20 Another embodiment of a system for detecting symmetric limb movements is shown.

[0071] Fig.21 Another embodiment of a system for detecting asymmetric limb movements is shown.

[0072] Fig. 22 Another embodiment of a system for detecting symmetric limb movements is shown.

[0073] Fig.23 Another embodiment of a system for detecting asymmetric limb movements is shown.

[0074] Fig.24 Another embodiment of a system for detecting symmetric limb movements is shown.

[0075] Fig.25 Another embodiment of a system for detecting asymmetric limb movements is shown.

[0076] Fig.26 One embodiment of an application on a computing device for comparing two sets of data from two limbs is shown.

[0077] Fig. 27 A graphical representation of the acceleration data from both wrists is shown.

[0078] Fig.28 A graphical representation of distance data from two wrists is shown.

[0079] Fig.29 A graphical representation of movement data from two wrists is shown.

[0080] Fig.30 A graphical representation of movement data from two wrists is shown while using a zoom feature of an application on a computing device.

[0081] Fig.31 A graphical representation of distance data from two wrists is shown.

[0082] Fig.32 A graphical representation of the acceleration data from both wrists is shown.

[0083] Fig.33 One embodiment of the architecture of the data processing module is shown.

[0084] Fig.34 One embodiment of a machine learning model for modeling a person's movement patterns, for example while sleeping, is shown.

[0085] Fig.35 Another implementation of a machine learning model for modeling human movement patterns is shown.

[0086] Fig.36 Another implementation of a machine learning model for modeling human movement patterns is shown.

[0087] Fig.37 An embodiment of a system for detecting stroke is shown.

[0088] Fig.38 An implementation of a digital "FAST" test is shown.

[0089] Fig.39 An embodiment of a system for detecting stroke is shown that is configured to stimulate a response symmetrically and measure an output of the response to determine whether the response is symmetrical or asymmetrical.

[0090] Fig.40 An embodiment of a wearable system for detecting abnormal biological events is shown.

[0091] Fig.41 Another embodiment of a wearable system for detecting abnormal biological events is shown.

[0092] Fig.42 A support structure for a heat source connected to one embodiment of a wearable system for detecting abnormal biological events is shown.

[0093] Fig.43 A cross-sectional view showing a wearable system for detecting abnormal biological events.

[0094] Fig.44 One embodiment of a tensionable strap for connecting a wearable system to the surface of the skin is shown.

[0095] Fig.45 First and second wearable systems are shown for measuring response asymmetry across right and left limbs, respectively.

[0096] Fig.46A A method of processing a signal received from a blood volume sensor is shown in graphical form.

[0097] Fig.46B A method of monitoring heating cycles and corresponding vasodilation responses over time is shown in graphical form.

[0098] Fig.47 The vasodilation response of the skin surface in response to applied heat is shown in graphical form over time.

[0099] Fig.48 A method for detecting abnormal biological events by measuring the vasodilation response of the skin surface in response to applied heat over time is shown.

[0100] Fig.49 An embodiment of a thermal stimulator that can be integrated into a wearable system is shown.

[0101] Fig.50 Another embodiment of a thermal stimulator integrated into a wearable system is shown.

[0102] Fig.51 An in-ear wearable system for measuring one or more biometric characteristics is shown.

[0103] Fig.52 A method of detecting abnormal biological events is shown.

[0104] Fig.53 A method of measuring a user's heart rate variability is shown.

[0105] Figure 54-55 A graph including electrocardiogram data for detecting abnormal biological events is shown.

[0106] Fig.56 A graph including asymmetric electrodermal activity data for detecting abnormal biological events is shown.

[0107] Fig.57 A graph including multiple parameters of interest in electrodermal activity data is shown.

[0108] Fig.58 A method for measuring a user's heart rate variability and various feature analyses is shown.

[0109] Fig.59 Shown is a time domain analysis of heart rate variability data.

[0110] Fig.60 Shown is a geometric analysis of heart rate variability data.

[0111] Fig.61 Shown is a frequency domain analysis of the heart rate variability data.

[0112] Fig.62 Nonlinear analysis of heart rate variability data is shown.

[0113] Fig.63 A method of measuring skin conductance response is shown.

[0114] Fig.64 Shown is a graph including asymmetric skin conductance responses over time.

[0115] Fig.65 Shown are graphs including the amplitude of the asymmetric skin conductance response over time.

[0116] The embodiments shown are examples only and are not intended to limit the present disclosure. Schematic diagrams are drawn to illustrate features and concepts and are not necessarily drawn to scale. DETAILED DESCRIPTION OF THE INVENTION

[0118] The foregoing is an overview and is therefore necessarily limited in detail. The above-mentioned aspects and other aspects, features and advantages of the present application technology will now be described in conjunction with various embodiments. The inclusion of the following embodiments is not intended to limit the disclosure to these embodiments, but to enable those skilled in the art to make and use the intended invention. Other embodiments may be utilized and may be modified without departing from the spirit or scope of the subject matter presented herein. As described and illustrated herein, the various aspects of the present disclosure may be arranged, combined, modified and designed in a variety of different ways, all of which are clearly intended to form a part of the present disclosure.

[0119] Described herein are systems, devices, and methods for multivariate detection of stroke. Multivariate may include the use of more than one, at least two or more factors, markers, or other parameters to detect stroke. In some embodiments, multivariate may include a parameter measured using multiple sites or positions or multiple times (e.g., random or fixed intervals, on demand, automatically, etc.). In various embodiments, multivariate may include symmetrically or asymmetrically detecting the measured parameters. The measured parameters may include functional parameters (e.g., gait, speech, facial changes, etc.); biological parameters or markers (e.g., blood proteins, metabolites, etc.); quantitative parameters (e.g., limb asymmetry, heart rate variability, etc.); one or more (e.g., 2, 3, 4, 5, 10, 15, 20, etc.) measured parameters of space (e.g., neck and chest; arms and legs; etc.); and / or one or more measured parameters of time differences.

[0120] In some embodiments, there may be two types of measurement data, physiological or quantitative signals (e.g., skin electromagnetic potential, Doppler blood flow signal abnormality, hyperhidrosis, skin blood flow, cerebral perfusion, heart rate variability, etc.), and / or clinical manifestations or functional parameters (e.g., limb asymmetry, slurred speech, facial ptosis, retinal abnormalities, etc.). Clinical manifestations occur after the onset of a stroke, but the weak signal from the combination of clinical manifestation measurement and physiological signal measurement can detect or predict the possibility of a stroke before the onset of a stroke. Parameters that can be measured before, during or after a stroke include quantitative parameters, functional parameters and / or blood / fluid parameters. Any parameter shown / described herein can be measured asymmetrically, as described elsewhere herein. Illustrative, non-limiting examples of quantitative parameters include: volume impedance spectroscopy, EEG asymmetry, cerebral perfusion, skin / body temperature (e.g., a cold paretic limb is 6°C or 16% cooler than a non-paretic limb), hyperhidrosis (e.g., an increase of greater than 40-60% in a paretic limb), limb asymmetry, drift and pronation tests, skin blood flow, muscle tone, heart rate variability (e.g., a greater than 10X decrease in spectral components that persists 3-7 days after stroke onset), facial surface EMG, cerebral blood flow (CBF), carotid stenosis, salivary cortisol, neuron-specific enolase (NSE), saliva (NSE), etc. Exemplary non-limiting examples of functional parameters include: voice change, speech comprehension, text comprehension, consciousness, coordination / orientation, facial muscle weakness, arm weakness, body weakness (e.g., grip), leg weakness, foot weakness, unilateral weakness, difficulty walking, dizziness, sudden visual problems, limited visual field, altered gaze, thunderclap headache, nuchal stiffness (neck), respiration, blood pressure (e.g., increase to 60% in both systolic (200 mHg) and diastolic (140 mmHg)), etc. Exemplary non-limiting examples of blood / fluid parameters include: CoaguCheck (Roche), HemoChron (ITC), iSTAT (Abbott), Cornell University, ReST (Valtari Bio Inc.), SMARTChip (sarissa Biomedical), etc.

[0121] In some embodiments, multiple measurement locations (e.g., radial artery, brachial artery, etc.) can be used to measure differences in signals or data patterns between those locations, compared to nominal healthy location measurements or compared to individual baselines as input to the data processing module. For example, an individual baseline can be recorded over time, and when an adverse event occurs, the change from the baseline (e.g., absolute or relative value) is determined unilaterally or bilaterally. In some embodiments, after an adverse event occurs, a new baseline can be established. In addition, for example, Figure 2As shown, the blood pressure pulse varies according to the position in the body, indicating that slightly different signals are measured according to the position. For example, if only one position is measured, the changes over time are observed. If multiple positions are monitored and / or measured, the changes over time and the changes relative to each other and / or the baseline can be used to identify the occurrence of patterns or asymmetric signals. In some embodiments, a personalized baseline is further calculated based on the patient's health history (e.g., diabetes, cardiac pacing, previous stroke, etc.), demographics, lifestyle (e.g., smokers, active exercisers, drinking, etc.), etc.

[0122] In some embodiments, such as Figure 1A-1B As shown, the system 100 for multivariate detection of stroke includes hardware components (e.g., wearable devices, sensors, computing devices, remote sensing devices, etc.) and data processing modules stored in or in communication with the hardware. The hardware components, such as one or more sensors, can be positioned on the user of the system, bilaterally positioned on the user of the system, or entirely at a location occupied by the user. Optionally (shown in dashed lines), the system for multivariate detection of stroke can further include third-party devices, such as those described in further detail elsewhere herein. or For example, there may be bidirectional communication (eg, via a wired connection or wireless communication) between a hardware component and a data processing module, a data processing module and a third-party device, and / or a third-party device and a hardware component.

[0123] In one exemplary non-limiting embodiment of the system of FIG. 1 , a digital FAST (i.e., face drooping, arm weakness, difficulty speaking, help seeking time) test can be performed by the system of FIG. 1 . 1. For example, the hardware components can include one or more cameras positioned throughout a user's occupation and configured to detect changes in facial expressions (e.g., drooping) as a result of a stroke (e.g., using computer vision techniques), such as Fig.38As shown (i.e., the "F" part of the FAST test). In addition, one or more sensors or other hardware components (e.g., cameras, microphones, etc.) may be positioned throughout the position occupied by the user. The one or more sensors are communicatively connected to the data processing module so that the parameters sensed by the sensors can be transmitted to the data processing module for digitization, filtering, processing and / or analysis. In the case of the digital FAST test, one or more sensors may sense asymmetric arm weakness. In order to identify speech difficulties, a third-party device configured to receive and evaluate speech quality may be communicatively connected to the data processing module and / or hardware components. Therefore, the user may be prompted to speak by a third-party device, and the user's response may be sensed by a hardware component (e.g., one or more microphones), so that the user's speech quality may be determined. One or more of these detected parameters may be analyzed and optionally sent to a caregiver, approved family and / or friends, a health care provider, a doctor, and / or an emergency service provider.

[0124] In some embodiments, the system for multivariate stroke detection may further include an application downloaded and / or stored on the hardware component or an application downloaded and / or stored on a computing device (e.g., a mobile computing device) communicatively connected to the hardware component. The application may be configured to process sensor data, camera data, speech data, etc. and / or display data sensed or captured in real time, such as in a graphical representation, and / or allow zooming to view various features of the data.

[0125] In some embodiments, data may be transmitted to and / or from a device for detecting stroke to a central hub, a mobile computing device, a server, or other storage and / or computing device. Data transmission may include wireless communication (e.g., near field communication (NFC) protocol, low energy Protocols, other radio frequency (RF) communication protocols, etc.). In other embodiments, data transmission can include wired communication between sensor locations on the subject and / or sensor locations on the central hub. In some embodiments, the central hub can be a monitor in a medical facility, a home monitor, a patient's mobile computing device, or other wireless device. Optionally, one or more sensors on the subject can serve as the central hub. The hub device can wirelessly send a signal to activate a medical care pathway and / or notify one or more individuals (e.g., family, friends, doctors, EMS, etc.).

[0126] In some embodiments, data transmission to a central hub following multivariate analysis can alert patients, relatives, and / or third parties to identify possible false positives or negatives.

[0127] In some embodiments, a device for stroke detection can be worn on the patient's exterior or skin surface or implanted as hardware before and / or during a stroke (including up to several days before the event and during the event) to provide continuously variable monitoring of various physiological parameters. Various embodiments described herein can be wearable devices or implantable devices.

[0128] In some embodiments, a device for detecting stroke may include a wearable device, such as a patch, headband or sweatband, ring, watch (e.g., measuring Figure 7 movement shown), tape, helmet, bracelet, anklet, socks (e.g., measuring heart rate, heart rate variability, temperature, gait, etc.), insoles (e.g., measuring heart rate, heart rate variability, temperature, gait, etc.), clothing, belt, necklace, earrings (e.g., on or in the ear to measure heart rate, heart rate variability, EEG asymmetry, etc.), hearing aids, earplugs, glasses or sunglasses or smart glasses (e.g., measuring EOG, EMG, EEG, gaze, facial muscle movement or droop, etc.), smart tattoos (e.g., measuring EEG, ECG, etc.), bras, bra clips, chest straps, contact lenses (e.g., measuring tear composition, etc.), masks or bite plates (e.g., measuring salivary neuron-specific enolase, cortisol, temperature, movement, etc.), hats or caps (e.g., using ultrasound to measure various signals), wearable speakers (e.g., measuring heart rate, heart rate variability, movement, etc.), or sensors integrated into any wearable clothing, accessory, or device. For example, a patch (e.g., wearable on the neck) can be used to estimate cerebral blood flow using Doppler ultrasound, blood oxygen content, or other blood characteristics as an indicator of blood entering the brain (carotid artery) or leaving the brain (jugular vein); a patch or strip (e.g., wearable on the head) can be used to detect EEG or sEMG. In addition, for example, a wearable device for detecting stroke may include one or more transdermal sensors configured to measure changes in one or more gases infused through the skin (e.g., nitric oxide (NO) can be measured directly, or by measuring specific biproducts); one or more biomarkers that diffuse into the subcutaneous area or diffuse into the epidermis in the blood and can be measured externally. In some embodiments, a wearable device for detecting stroke may include a wristband or patch in combination with microneedles that is configured to measure subcutaneous fluid or interstitial fluid (e.g., similar to a continuous glucose monitor).

[0129] In some embodiments, a wearable device for detecting stroke may include a wearable indicator array (e.g., a color indicator) configured to measure chemicals, analytes, proteins, etc. in a body fluid of an individual (e.g., blood, interstitial fluid, etc.). For example, the array may include a membrane having an array printed thereon, and when the array is exposed to one or more analytes, a subset of indicator spots responds by changing color or properties. For example, a camera or other image sensor on a computing device may be used to optically read the color reaction of the indicator and compare it to a baseline reading or a reference or standard. A color difference map may be generated by superimposing and / or subtracting two images (baseline and experimental, or experimental and reference / standard). As an exemplary non-limiting analyte, an increase in nitric oxide may be detected in the blood or interstitial fluid of an individual after a stroke event, and / or changes in nitric oxide to one or more proteins may be detected in the blood or interstitial fluid of an individual after a stroke event, and / or one or more intermediates or byproducts of nitric oxide may be detected in the blood or interstitial fluid of an individual after a stroke event. For example, nitric oxide has been shown to modify proteins by: 1) binding to metal centers; 2) nitrosylation of thiol and amine groups; 3) nitration of tyrosine, tryptophan, amine, carboxylic acid, and phenylalanine groups; and 4) oxidation of thiols (cysteine ​​and methionine residues) and tyrosine. This approach can bypass the need to measure asymmetric changes in one or more parameters, as described elsewhere herein.

[0130] In some embodiments, a system for stroke detection may include one or more Doppler radar sensors, microphones, and cameras throughout the home to detect visual signs of stroke, comparable to a "FAST" test using computer vision or similar technology, such as Fig.38 For example, a machine learning model can be trained on a training dataset of images of stroke patients to identify asymmetric facial features, such as facial droop. Fig.38 As shown, the system is able to identify droop in the patient's mouth, nose, and eye positioning. Facial capillary asymmetry through high frame rate Euler video processing techniques can also be detected by the system described herein. The system can also use confirmatory biometrics such as HR / HRV, respiration rate (e.g., via Doppler radar), and / or bidirectional temperature via an infrared camera (i.e., FLIR)

[0131] In some embodiments, a device for detecting stroke may include a device that can be positioned in a room, office, home, vehicle, or other location; or a device positioned in or on a bed or other furniture (e.g., a bedside monitor; a monitor within a mattress, bedding, etc.). For example, a smart speaker (e.g., prompting a user to respond to questions to analyze speech quality), a microphone, a camera, and / or a mirror may be positioned in a location to detect a user's voice, activity, movement, gait, facial appearance, heart rate, and / or heart rate variability. The device may include a data processing module for comparing changes in measured parameters to healthy, known patient data or personalized baseline data to distinguish. This may also be referred to as reference data. The learned healthy patient data may be unique to a particular user or may be an aggregate value predetermined based on previous studies. The learned healthy patient data or personalized patient data may be stored as one or more parameters or tags.

[0132] In some embodiments, such as Figure 3 As shown, the device can be one or a pair of rings that are worn on each hand or each foot to measure temperature; volume impedance spectroscopy; hyperhidrosis; heart rate or heart rate variability by monitoring blood flow rate, such as through a PPG sensor; and / or motion (e.g., by including an accelerometer and / or gyroscope therein) to measure, for example, limb asymmetry or gait changes. The temperature measurement device may include, but is not limited to, an infrared sensor, a thermometer, a thermistor, or a heat flux transducer. The hyperhidrosis measurement device may include, but is not limited to, detecting analytes (including ions, metabolites, acids, hormones, and small proteins) by potentiometry, chronoamperometry, cyclic voltammetry, square wave stripping voltammetry, or detection of changes in conductivity. The sensor measurement device may include, but is not limited to, a photoplethysmography (PPG) device, a skin conductance sensor that measures skin conductance / galvanic skin response (GSR) or skin electrical activity (EDA), or a skin temperature measurement device (e.g., a contact device and a non-contact device, such as an IR imaging camera).

[0133] In some embodiments, the ring may incorporate a stretchable or expandable element or stretch sensor to allow the ring to expand or stretch as the finger swells. The element may include, but is not limited to, elastomeric film polymers of various degrees of adhesion to allow for different pliable elements or to measure reflectivity of polarized light. The element may include plastic segments of the ring that can be loosened / tightened, or slidable elements that can be pulled apart by construction. Non-limiting examples of stretch sensors include, but are not limited to, strain gauges or electrical components configured to change inductance, resistance, or capacitance when stretched.

[0134] In some embodiments, the device can be a strip that measures brain waves by electroencephalography and / or muscle contractions by surface electromyography (sEMG). The EEG measurements can be compared to baseline values ​​to detect changes or asymmetries in the EEG. In some embodiments, EMG measures facial muscle changes compared to baseline measurements to identify muscle weakness and muscle tone.

[0135] In some embodiments, such as Figure 4 As shown, the device can be a wearable eyewear device that measures electrooculogram (EOG), EMG, EEG, gaze, and facial muscle symmetry. The EOG measurement identifies changes in the angular retinal standing potential between the front and back of the eye, which can detect changes in gaze and visual field size and can be compared to the other eye or a previous baseline value.

[0136] In some embodiments, such as Figure 5-6 As shown, the device for stroke detection may include a wearable device for measuring changes in motion (e.g., on three axes), for example, asymmetric motion for detecting tremors. In some embodiments, the device for stroke detection may include a wearable device for measuring changes in motion (e.g., on three axes), for example, asymmetric motion for detecting tremors. Such a device may include an accelerometer, gyroscope, inclinometer, compass, or other device for measuring acceleration, distance, and / or movement. For example, as Figure 5 As shown in , when the wearable device moves, the plane of action also moves. The accelerometer can track the changes in the plane and adjust the three-dimensional movement accordingly. In addition, as Figure 6 As shown, the accelerometer can track azimuth, roll, and pitch.

[0137] In some embodiments, an apparatus for detecting stroke can be configured to detect an asymmetric response, output, or signal. For example, one or more devices described herein (eg, rings, watches, etc.) can be used to measure symmetric and asymmetric limb movements. Figure 12-25 Various symmetric and asymmetric motions that can be measured by one or more embodiments described herein are shown. For example, Fig.12 , 15 , 18, 20, 22 and 24 show various embodiments of symmetrical movements between two limbs (e.g., up and down movement, left and right movement, rotational movement, etc.) that can be measured by the various devices described herein. Figure 13-14 , 16-17, 19, 21, 23 and 25 show various embodiments of asymmetric movements of limbs (e.g., up and down movement, left and right movement, rotational movement, etc.) that can be measured by the various devices described herein.

[0138] In some embodiments, such as Fig.39As shown, the device or system for detecting stroke can be configured to stimulate response and measure the response on each side of the user's body (e.g., detecting asymmetric response) to determine whether the response or the difference in response between the two sides indicates a stroke event. For example, a thermal (i.e., hot or cold) stimulus can be applied to a portion of the skin on the user's body (shown in the top figure), and the response of the body to the thermal stimulus can be monitored over time (shown in the bottom figure) to determine whether a steady state is reached and / or there is a difference in response or return rate between the two sides of the body (in other words, determine whether there is an asymmetric response). Further examples include using electrical signals to stimulate muscles or nervous systems, and using electromyography, bioimpedance or electroneurography to monitor the response over time and / or between the two sides, respectively. These "stimulators / transmitters" and "receivers / detectors" can be in the same area, or can be separated to measure various areas of the body.

[0139] As described above, if a stroke is detected and the patient seeks care quickly, death and disability can be significantly reduced. Continuous monitoring of stroke events can improve response time. However, continuous monitoring of abnormal biological events such as stroke events can be challenging using existing monitors. These monitors are cumbersome and can be difficult for users to wear for long periods of time. In contrast, the inventors of the present application recognize that wearable devices such as watches with integrated sensors and electronics can improve continuous monitoring of stroke events. An impaired vasodilator response can indicate stroke, heart failure, hypertension, diabetes, menopause or other diseases.

[0140] Applying thermal stress to a portion of the skin can enable detection of vasodilation responses. Thus, the systems and methods described below can detect impaired vasodilation in a form factor that improves continuous abnormal cardiac event monitoring. In some embodiments, such as Fig.40 As shown, the system or device 400 for detecting abnormal biological events can be used to heat the skin surface and measure the vasodilation response of the skin surface. The system or device 400 can also be used to measure one or more additional parameters, biological signals, etc., as will be described in more detail elsewhere in this article.

[0141] In one example, a system or device 400 for detecting an abnormal biological event may include a body 416 having a first surface 404 opposite to a second surface 402 in contact with a human skin surface. The first surface 404 and the second surface 402 may be connected via one or more or a plurality of sidewalls 405. For example, one or more sidewalls 405 may extend from the periphery of the first surface 404 and be connected to the periphery of the second surface 402. The first surface 404 and / or the second surface 402 may include one or more sensors located thereon. For example, one or more sensors on the first surface 404 may measure the environment in which the user wears or uses the wearable system, and one or more sensors on the second surface 402 may measure one or more attributes, features or characteristics of the user's skin surface, and thus measure the user himself. Optionally, the first surface 404 may include one or more sensors or imagers or cameras for evaluating the user's facial area, for example, via a FAST test.

[0142] The wearable device 400 may be secured to a user (e.g., a limb of the user or a skin surface of the user) via a connection element 408 (e.g., a tensionable strap), which will be described in more detail elsewhere herein. The connection element 408 may be adjustable so that the wearable device may be tightened or tensioned to facilitate greater contact and thus connection between the wearable device and the skin surface or release tension to reduce contact or connection between the wearable device and the skin surface. Fig.41 As shown, the connection element 408 can be connected to the body 416 of the wearable device via one or more connectors 422a, 422b, 422c, 422d. For example, the connection element 408 can be connected to the body 416 of the wearable device via a connector 422 including one or more pin joints, a snap-fit ​​connection with the connection element 408, a slide and fit connection with the connection element 408, etc. When the tensionable band 408 is connected to the body 416 via the connector 422, the tensionable band is centered relative to the one or more sensors located on the second surface so that there is sufficient connection between the sensor and the skin surface.

[0143] The wearable device 400 may include a heat source 410 in communication with the skin surface. The heat source 410 is configured to heat the skin surface to a target temperature or a predetermined temperature. The heat source 410 can be a heating element; an ambient heat source, such as a warm room, a warm environment (e.g., under a cover, on a hot day, etc.); a thin film resistive flexible heater; a polyimide heater; or the like. In some embodiments, the heat source 410 is positioned on the second surface 402 of the body 416 such that there is a connection or contact between the heat source 410 and the skin surface. Alternatively, the heat source 610 or one or more sensors 612, 626 can be positioned on the connection element 608 of the system 600, such as Fig.50As shown, the body 616 is separated from the sensor module 609 including the heat source 610 and one or more sensors 612, 626. Optionally, the heat source and / or one or more sensors may be distributed between the connecting element, the body and the sensor module, depending on which sensors are incorporated into the system and their specific requirements or parameters.

[0144] In some embodiments, such as Fig.49 As shown, the heat source 710 may include a thermal stimulator that includes a single printed layer of resistive ink on a polyimide film 702. Thermal traces 704 and traces to one or more sensors 706 (e.g., a blood volume sensor, an infrared sensor, a temperature sensor, etc.) may also be printed on the polyimide film 702, as shown. Fig.49 shown.

[0145] In yet another embodiment, the sensor module 809 may be positioned in an in-ear device (e.g., an earlobe clip, an earplug, a hearing aid, etc.), such as Fig.51 The sensor module can be configured to measure one or more parameters, such as blood pressure, temperature and / or oxygen saturation, depending on the presence of sensors.

[0146] In addition, the heat source 410 can be communicatively connected to the hardware processor so that the hardware processor outputs a heating signal to the heat source 410 to activate the heat source to start a heating cycle. For example, the heating cycle can include receiving a baseline temperature signal from a skin temperature sensor and an ambient temperature sensor, determining a target temperature based on the baseline temperature signal, and determining whether the target temperature is below a maximum temperature value.

[0147] In some embodiments, the target temperature can be equal to the baseline skin temperature measured by the skin temperature sensor plus about 1 to about 20 degrees, such as about 1 to about 5 degrees, about 1 to about 10 degrees, about 5 to about 10 degrees, about 5 to about 15 degrees, about 8 to about 12 degrees, etc. In one embodiment, the target temperature is equal to the baseline skin temperature measured by the skin temperature sensor plus about 5 degrees to about 15 degrees. In another embodiment, the target temperature is equal to the baseline skin temperature measured by the skin temperature sensor plus about 7 degrees to about 13 degrees. In another embodiment, the target temperature is equal to the baseline skin temperature measured by the skin temperature sensor plus about 10 degrees. If the target temperature is greater than the maximum temperature value, the system pauses or delays until the baseline skin temperature drops below the minimum threshold or the target temperature is recalculated so that the target temperature is less than the maximum temperature value. If the target temperature is less than the maximum temperature sensor, the system continues to operate to activate the heat source to heat the skin surface to the target temperature.

[0148] In some embodiments, the heat source is cycled between a target temperature and a deactivated or off state, or between a target temperature and a temperature below the target temperature but above the skin's baseline temperature, e.g., to maintain the target temperature, hereinafter referred to as a dwell time.

[0149] In some embodiments, the duration of the heating cycle is associated with a target temperature and is based on the user's preference for heat on the skin surface or the user's perception or the user's vasodilation response. For example, a higher target temperature may be used for a shorter period of time, or a lower target temperature may be used for a longer period of time.

[0150] In addition, the system or device 400 can be configured to receive one or more user inputs related to a thermal sensation perceived on the skin surface and / or to the sensitivity of the user's vasodilatory response. For example, the user can input, for example, via a user input element (e.g., a button) that the target temperature feels too hot or too cold, such that the system responds by lowering the target temperature but extending the amount of time the skin is heated. Additionally or alternatively, based on user preferences, preset configurations (e.g., during manufacturing), or as a result of sensed data (e.g., based on sensor data), the heat source can reach the target temperature via one of a plurality of ramp functions, such as a slow ramp function, a larger step function, etc. Alternatively, the heat source can reach the target temperature via a plurality of microstimuli. Furthermore, for example, the target temperature can be personalized for the user based on the sensitivity of the user's vasodilatory response.

[0151] In some embodiments, the device or system 400 for detecting an abnormal biological event includes a support structure 428 coupled to a heat source 410 and configured to couple the heat source 410 to a second surface 402. For example, Fig.42 As shown, the support structure 428 includes an arm 432 extending toward the center of the heat source 410 to support the heat source 410 and one or more spokes 430 extending from the arm 432 to the periphery of the heat source 410. The spokes 430 may be approximately equidistant from adjacent spokes 430. The spokes 430 may also be arranged circumferentially around a pin or joint 434. The spokes 430 of the support structure 428 further define air flow holes 442 to allow air to interact with the heat source 410 to cool the heat source 410. The spokes 430 further define air flow holes 422 to at least partially expose the heat source to the cavity defined by the first and second surfaces, as described elsewhere herein. Alternatively or additionally, the heat source 410 may be cooled by one or more vents, a blower for passing air through the heat source 410, a coolant, or another mechanism known to those skilled in the art.

[0152] In some embodiments, the support structure 428 applies pressure to the heat source 410 to increase the contact or connection between the heat source 410 and the skin surface. In one embodiment, the tensionable belt includes a strain gauge that determines the tensile stress to which the belt is subjected. The strain gauge output or signal can then be visualized or displayed to the user so that the user knows whether the belt is tensioned to the appropriate level for the heat source and / or sensor. Alternatively, the spring constant (k) of the material can be used to calculate the force (F=kx), so that depending on the amount the material is stretched (placed in tension), the belt can indicate the force based on displacement. Therefore, the support structure 428 can include a flexible material, such as a flexible plastic. In other embodiments, the support structure 428 includes a rigid material.

[0153] In addition, if Figure 40-41 As shown, the device or system 400 for detecting abnormal biological events also includes a skin temperature sensor 414 and a blood volume sensor 412. The blood volume sensor 412 can be integrated into the form factor of the device or system 400, such as improving continuous abnormal cardiac event monitoring. The blood volume sensor 412 can measure parameters that can provide vasodilation response. In addition, the skin temperature sensor 414 can also be integrated into the device or system 400. The skin temperature sensor 414 is located on the second surface 402 and is configured to measure the temperature of the skin surface in contact with the heat source 410. The blood volume sensor 412 is located on the second surface 402 and is configured to measure the blood volume on the skin surface. The blood volume sensor can be a photoelectric plethysmography sensor or an impedance plethysmography sensor. The blood volume sensor can use 530nm (green), 645nm (red), 470nm (blue) wavelengths of light or a combination thereof. Different wavelengths can be more suitable for different applications, for example, for heart rate measurement (e.g., heart rate variability, heart rate, etc.), green (530 nanometers) light can be more accurate. Additionally or alternatively, the blood volume sensor may also be configured to measure one or more of heart rate, heart rate variability, or oxygen saturation.

[0154] The system or apparatus 400 for detecting an abnormal biological event may include an ambient temperature sensor configured to measure the temperature of the environment surrounding the wearable system 400. For example, the ambient temperature sensor may be positioned on a first side 404 of a body 416 of the wearable system, opposite a second side 402 including a heat source 410. Optionally, the system or apparatus 400 may be communicatively connected to an ambient temperature sensor on or in a remote computing device. For example, the remote computing device may include a laptop computer, a cellular device, a workstation, a server, a desktop computer, a personal digital assistant, a second wearable system or device, a netbook, etc.

[0155] The skin temperature sensor and / or the ambient temperature sensor may include a thermocouple, a resistance temperature detector, a thermistor, or an infrared temperature sensor. The type of temperature sensor selected may depend on error rate, connection to the skin surface efficiency, and other characteristics.

[0156] In some embodiments, such as Figure 40-41 As shown, heat source 410 is concentrically positioned about one or both of blood volume sensor 412 and skin temperature sensor 414. However, it is contemplated that blood volume sensor 412 and skin temperature sensor 414 may be coupled to locations or positions on the surface of the skin.

[0157] A hardware processor (within or communicatively connected to the wearable system) communicatively connected to the skin temperature sensor 414 and the ambient temperature sensor can be configured to perform a method including: a method of receiving a first temperature signal using the skin temperature sensor and a method of receiving a second temperature signal using the ambient temperature sensor; and calculating the temperature difference between the skin temperature and the ambient temperature. For example, if the temperature difference is below a set threshold, the difference between the target temperature and the maximum temperature value can be increased. Conversely, if the temperature difference is above a set threshold, the difference between the target temperature and the maximum temperature value can be reduced. The ambient temperature sensor can also be used to determine an analysis of erroneous results, such as a false positive indication of an abnormality. By comparing signals before and after stimulation and / or by comparing the left limb with the right limb, the external effects of this ambient temperature response can be reduced when analyzing abnormalities.

[0158] In addition, the hardware processor can be connected to the heat source 410 and the blood volume sensor 412. In some cases, the above system 400 can achieve non-invasive monitoring of vasodilation and / or vasoconstriction. The human body regulates stable balance through homeostatic processes. For example, if a stimulus is applied to the patient's body, one or more homeostatic processes will try to counteract the effect of the stimulus. For example, for an induced thermal stimulus that increases or decreases the temperature at a tissue site, the body will try to reverse the temperature change through blood flow (vasodilation or vasoconstriction). Therefore, the system 400 can induce and measure a vasodilation response. As described above, stroke and other abnormalities can impair the vasodilation response. Therefore, in some cases, it may be advantageous to monitor changes in the vasodilation response to determine abnormalities (such as stroke). A blood volume sensor, such as an optical sensor, is capable of monitoring blood flow and corresponding vasodilation responses. In some cases, one or more temperature sensors (via a thermistor or a detector based on optical radiation) can also achieve determination of the vasodilation response by monitoring how quickly the temperature of the skin returns to equilibrium after stimulation. In some embodiments, the vasodilator response is related to the rate of change or slope of the measured parameter (e.g., blood volume parameters, temperature, and other parameters discussed herein). In other examples, the vasodilator response can be related to the steepness of the rate of change. This can be calculated using the second derivative.

[0159] In some cases, it is advantageous to use a combination of heat source 410 and blood volume sensor 412 to improve cardiac monitoring. Heat source 410 and blood volume sensor 412 can be integrated into a user-wearable form factor for continuous monitoring. Repeated measurements can be made non-invasively without significant discomfort to the patient. In addition, Fig.46A -B and 47, the response time between the application of heat and the change in blood volume is relatively small. This enables relatively rapid determination of abnormal biological events. Therefore, it is advantageous to integrate a heat source and a blood volume sensor in any wearable system disclosed herein to improve continuous cardiac monitoring. In some cases, a Peltier cooler can be used as a heat source in place of heat source 410 or in addition to heat source 410.

[0160] In addition, in some cases, the stimulation may be electrical stimulation in addition to or in place of thermal stimulation. For example, the system 400 may include a plurality of electrodes for inducing and / or measuring electrical activity across tissue sites. The electrical activity may include bioimpedance for detecting high or low muscle tension, which may occur with hemiplegia. The system 400 may include at least two electrodes. In some cases, the system 400 may include at least four electrodes. For example, the system 400 may include two pairs of electrodes for measuring bioimpedance. The four electrodes may be located on the second surface 402. The electrodes may also be positioned on the strip 408 or an external attachment to which the system 400 may be attached. Bioimpedance can measure intercellular and intercellular muscles, which can be used to detect hemiplegia, and can be used for detection and rehabilitation. The EDA electrode may also be mounted anywhere on the strip 408 along the second surface facing the skin. In addition, the system 400 may also include six or more electrodes. The electrodes may be integrated on the system 400 so that they are in contact with the user's skin tissue.

[0161] As described above, an optical sensor such as the blood volume sensor 412 can interrogate the target tissue to determine parameters related to the vasodilatory response. Other sensors can also be used to extract parameters for determining the vasodilatory response. For example, the system 400 can use minimally invasive and / or invasive sensors to determine hemodynamic parameters, such as cardiac output, to provide an indication of the vasodilatory response. The system 400 can also include one or more electrical-based sensors, such as bioimpedance sensors, EDA sensors, electrocardiogram sensors, electroencephalogram sensors, myoelectric signal sensors, etc. The electrical sensor can enable the measurement of hydration, skin conductivity, bioimpedance, and other electrical parameters related to hemodynamic function, or measure electrical signals of neural activity and its effects. In addition, the system 400 can include one or more ultrasonic sensors to obtain hemodynamic parameters. The temperature sensor can also determine the vasodilatory response. Therefore, the system 400 can include a combination of some or all of the sensors discussed above to extract one or more parameters related to hemodynamic function or maintaining homeostasis.

[0162] The following table shows exemplary physiological phenomena and corresponding parameters that can be monitored:

[0163]

[0164]

[0165] Patients are often monitored in a neuro-ICU after a stroke. This can be expensive because nurses need to perform regular checks on the patient. Therefore, system 400 can achieve improved monitoring without requiring the patient to be in a neuro-intensive care unit and / or without requiring regular checks by a caregiver. Although system 400 is described as a wearable system, in some examples, some or all components of system 400 may be positioned close to the user but not directly attached or worn by the user. For example, when it is necessary to monitor the user in a hospital environment, some or all components of system 400 may be positioned near the user's hospital bed. For example, the thermal stimulation source may include a laser.

[0166] Thus, the hardware processor can be configured to perform Fig.52 The method shown in the figure includes: receiving a baseline blood volume signal from a blood volume sensor S5202, outputting a heating signal to a heat source to start a heating cycle S5204, receiving a second blood volume signal from a blood volume sensor S5206, comparing the second blood volume signal with the baseline blood volume signal S5208, and determining whether an abnormal biological event has occurred based on the comparison S5210. The steps of the method can be cyclically repeated at least once, once or more times, or more times according to the doctor, caregiver or user preference or other means.

[0167] In some embodiments, the second blood volume signal is a set of blood volume signals such that the blood volume on the skin surface is repeatedly measured before, during, and / or after a heating cycle of the heat source. The blood volume on the skin surface can be measured at preset intervals, such as every about 10 milliseconds to about 1 second, about 1 second to about 5 seconds, about 5 seconds to about 10 seconds, etc. Alternatively, the blood volume on the skin surface is measured randomly or only when a temperature change on the skin surface is detected or only when a vasodilation change is detected by the blood volume sensor. The measurement frequency can be personalized for the user, for example, if the user is very sensitive to the vasodilation reaction of the response to heat, the frequency of blood volume measurement may need to be reduced. On the contrary, if the user is not so sensitive to the vasodilation reaction of the response to heat, the frequency of blood volume measurement may need to be increased.

[0168] In some embodiments, the second blood volume signal is a plurality of blood volume signals such that blood volume at the skin surface is continuously measured before, during, and / or after a heating cycle of the heat source.

[0169] In some embodiments, block S5206 includes receiving a second blood volume signal after the target temperature is reached, after a predetermined period of time has expired, after a dwell time (i.e., cycling the heat source on and off during a heating cycle or cycling the heat source between the target temperature and a lower temperature during a heating cycle) has expired, or after one or more heating cycles have expired. The sampling relative to the thermal cycle (before, during, or after the thermal cycle) and / or the frequency of the sampling can be based on the biology of the user, such that the sampling is personalized.

[0170] In some embodiments, block S5208 includes calculating a baseline ratio of alternating current (AC) to direct current (DC) of the baseline blood volume signal and a second ratio of AC to DC of the second blood volume signal, and comparing the baseline ratio to the second ratio, such as Fig.46A The method and principles of AC to DC ratio are described in Tusman et al. "Advanced uses of pulseoximetry for monitoring mechanically ventilated patients." Anesth Analg 2017; 124: 62-71, which is incorporated herein by reference in its entirety. Fig.46A The upper left panel shows the raw PPG amplitude data and the corresponding DC and AC components of the signal. Taking the ratio of the AC to DC of the raw signal produces the upper right panel. The PPG data in the lower left panel was collected during a double heating cycle experiment. The AC and DC components of the signal are represented in separate stacked graphs. When the ratio of AC to DC is calculated for this double heating cycle experiment, a normalized PPG signal is achieved, which is shown in the lower right panel. Fig.46BThe same PPG data is shown in , overlaid with thermal cycle data. As shown, during each thermal cycle, the temperature of the skin surface reaches the target temperature (i.e., approximately 42°C), as shown by the shaded portion of the figure. In response to the application of heat, the perfusion index or normalized PPG signal similarly spikes during each thermal cycle. Fig.47 Shown with Figures 46A-46B Same data, with additional definitions of baseline, vasodilation, and post-vasodilation windows. The heat cycle was 5 minutes off, 5 minutes on, 15 minutes off, 5 minutes on, and 10 minutes off. The time windows selected for comparison were: baseline time window (e.g., at least 2 minutes before "heat source first on"), vasodilation time window (e.g., at most 2 minutes after "heat source on"), first post-vasodilation time window (e.g., at least 2 minutes after "heat source first on"), and second post-vasodilation time window (e.g., at least 2 minutes after "heat source second on"). Figures 46A-47 As shown, application of heat induced a vasodilatory response that was reproducible over multiple cycles.

[0171] As described above, tracking vasodilation responses can be used to monitor abnormalities, such as stroke. However, the user's vasodilation response can be affected by several sources that are unrelated to the stroke or abnormality being monitored. Therefore, using the system 400 in only one tissue site may result in false positives. The inventors of the present application have observed that by monitoring multiple tissue sites, the monitoring results can more closely track abnormalities and reduce erroneous results. The first system 400 and the second system 500 are arranged approximately symmetrically on the right and left limbs. Therefore, if the stimulation is applied approximately synchronously between the first system 400 and the second system 500, the degree of symmetry or asymmetry in the measurement in response to the approximately simultaneous stimulation can be used to determine the stroke and reduce erroneous results. Although the disclosure herein provides a stroke as an example of an abnormality, the system 400 and method described herein can also be used to monitor other abnormalities. For example, other abnormalities or physiological deviations may include menopause, diabetes, and peripheral blood circulation disorders that can affect peripheral blood circulation. In some cases, menopause, diabetes, and other diseases may affect all parts of the body or may evenly affect certain parameters. For example, in conditions such as menopause, the vasodilatory response may be uniformly impaired compared to stroke where there is a high likelihood of asymmetry. Thus, based on the asymmetry observed in the vasodilatory response and other multilateral measurements, stroke can be distinguished from these other abnormalities, and vice versa. In another example, the vasodilatory response may be affected, but the electrical measurements using EDA and bioimpedance described herein may remain the same. Thus, asymmetry in the measurements can also be used to determine abnormalities.

[0172] In some embodiments, such as Fig.48 As shown, the method 4800 for detecting an abnormal biological event includes: applying a high temperature stimulus (e.g., Figure 46B-47 In response to a high temperature stimulus, receiving one or more signals indicating blood volume, blood flow, or blood perfusion in a user's tissue S4820; extracting one or more features of the one or more signals S4830; comparing the right and left sides of the user (e.g., right and left limbs, such as Fig.45 and calculating an acute stroke classification score S4850. In addition, method 4800 can optionally compare baseline measurements before and after applying the stimulation, such as in combination with Fig.52 The left and right limbs are discussed in more detail. During monitoring of multiple tissue sites, e.g. Fig.45 During the left and right limb monitoring shown, system 500 may include all the same components as system 400 described above. In other cases, system 500 may include fewer components than system 400. For example, both systems may not require a display. In addition, one system may include computing power, while the other system collects data and transmits it to the paired system for calculation. Therefore, one of systems 400 and 500 may not include a hardware processor. Therefore, systems 400 and 500 may operate in a master-slave configuration. Systems 400 and 500 may be paired wirelessly via Bluetooth or other wireless protocols. In some cases, systems 400 and 500 may be paired with an external computing system, such as a patient monitor, a hub, or a smartphone.

[0173] In some embodiments of box S4830, one or more features include, but are not limited to, amplitude or systolic or diastolic waves, waveform shape, waveform complexity, perfusion index (i.e., the relationship between the pulsatile (AC) and non-pulsatile (DC) components of the PPG signal), DC offset, stiffness index (i.e., the time between the peaks of the forward and backward waves along the vascular tree; h / ΔT, where h is the patient's height), reflectivity index (i.e., the ratio between the heights of the backward and forward waves; B / A×100), notch location (i.e., the location of the dichrotic notch; for example, as the vessel contracts, this location moves to the left into the systolic wave), peak-to-peak phase shift, slope onset of the temperature signal and / or blood volume signal, slope decay of the temperature signal and / or blood volume signal, midpoint of the slope rise of the temperature signal and / or blood volume signal, vasodilation response as an indication of the collateral status of the brain and / or heart, and the like.

[0174] In any of the embodiments described herein, a wearable system or device for detecting an abnormal biological event may include one or more electrodermal activity sensors and / or a tensionable band of the system located on a second surface. Fig.41As shown, galvanic skin sensors 424, 426 are located on the second surface 402 of the wearable system 400. The galvanic skin sensors 424, 426 can be spaced apart from each other by a distance 444 equal to about 5 mm to about 10 mm, about 10 mm to about 20 mm, about 20 mm to about 30 mm, about 30 mm to about 40 mm, about 40 mm to about 50 mm, about 50 mm to about 60 mm, about 60 mm to about 70 mm, about 70 mm to about 80 mm, about 80 mm to about 90 mm, about 90 mm to about 100 mm, measured from the center point of each sensor. In addition, the skin electrical sensors 424, 426 can be separated from the heat source by a distance 446, which is equal to about 10 mm to about 20 mm, about 20 mm to about 30 mm, about 30 mm to about 40 mm, about 40 mm to about 50 mm, about 50 mm to about 60 mm, about 60 mm to about 70 mm, about 70 mm to about 80 mm, about 80 mm to about 90 mm, about 90 mm to about 100 mm, measured from the center point of the sensor and the center point of the heat source.

[0175] like Fig.56 As shown in FIG. 1 , as an example, the electrodermal activity (EDA) of the user's skin surface can be measured over time. The left and right electrodermal activities can be measured and compared over time. Fig.56 The left and right electrodermal activity including events (shown as triangles) that may indicate abnormal biological events are shown. The signals collected by the electrodermal activity sensor can be processed to extract one or more features. For example, Fig.57 As shown, one or more characteristics may include rise time (i.e., SCR start to apex), amplitude (i.e., EDA at apex minus EDA at SCR start), skin conductance response (SCR) width (i.e., between 50% of the amplitude on the slope side and 50% of the amplitude on the decline side), decay time (i.e., time from peak to 50% of the amplitude), area under the curve (i.e., SCR width multiplied by amplitude), maximum derivative and / or peak value of the SCR.

[0176] Fig.63 Method 6300 for analyzing electronic data is shown; Figure 64-65 Representative EDA data are shown. Method 6300 for analyzing EDA data includes obtaining data from one or more EDA sensors (e.g., Fig.56 Detect and / or remove one or more artifacts (e.g., Fig.56 Calculate or extract one or more skin conductance response (SCR) features (e.g., Fig.57 Calculate the average or mean of one or more features S6340; and calculate the SCR for a period of time S6350. For example, the SCR amplitude is Fig.65The one-minute intervals are shown graphically in FIG. 1 . As shown, for this individual, the SCR amplitude varies over time and asymmetrically (i.e., comparing the response on the right side to the response on the left side). Furthermore, if the SCRs per minute on the left and right sides are compared, then Fig.64 As shown, the SCR per minute varies with time and is asymmetrical.

[0177] In any of the embodiments described herein, a wearable system or device for detecting an abnormal biological event may include one or more motion sensors 436 configured to measure the motion of a body part to which the wearable system is connected, such as Fig.43 As shown in . For example, one or more motion sensors can measure acceleration in six or nine degrees of freedom. As described elsewhere herein, a wearable system or device for detecting stroke can be combined with measuring a vasodilation response in response to the application of heat, and can measure asymmetric movement or tremor of the left and right limbs. One or more motion sensors can be positioned anywhere on the wearable device. For example, in one embodiment, the motion sensor is positioned in or on a first surface. In another embodiment, the motion sensor is positioned in or on a second surface. In another embodiment, the motion sensor is positioned between the first surface and the second surface. In another embodiment, the motion sensor is positioned on a side wall of the body of the wearable device. In another embodiment, the motion sensor is positioned adjacent to a vasodilation sensor or temperature sensor of the system, for example, concentrically surrounded by a heat source, such as Fig.43 shown.

[0178] The heat source of the wearable device or system 400 can be cooled between heating cycles to ensure that a baseline or substantial baseline of vasodilatory response at the skin surface is restored between heating cycles. Thus, the heat source can be cooled by an airflow system (e.g., a fan), a vacuum or vibrating mechanism (e.g., a solenoid and diaphragm, an oscillating piezoelectric element) configured to displace, pull, or move ambient air, or the like. In one embodiment, as Figure 40-43As shown in, a wearable system or device for detecting abnormal biological events includes a first surface 404 and a second surface 402, which define a cavity 406 between them to provide airflow between the first surface 404 and the second surface 402. The cavity 406 defined by the first surface 404 and the second surface 402 physically separates the heat source 410 from the hardware processor 409 located on or within the first surface 404. The hardware processor 409 may include a microcontroller, a digital signal processor, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic, a discrete hardware component or any combination thereof designed to perform the functions described herein. The cavity 406 is used to expose the heat source 410 to the outside world or the environment or the surrounding air to cool the heat source 410 to a temperature close to, substantially equal to, or equal to the air temperature or the ambient temperature in the environment. The cavity 406 can be an empty space, a gap space, a space for accommodating one or more components, etc. In some embodiments, the cavity 406 formed by the first 404 and second 402 surfaces is open to the outside or ambient air such that the side walls 405 connecting the first surface 404 and the second surface 402 are opposite to each other such that the cavity 406 is open to the ambient air on opposite sides, such as Figure 40-41 Alternatively, the side walls 405 are connected to each other and adjacent to each other, so that the cavity is open to the ambient air on the adjacent or connected sides.

[0179] For example, in some embodiments, the cavity 406 defined by the first surface 404 and the second surface 402 has a sufficient volume to promote cooling of the heat source 410 between heating cycles. Alternatively or additionally, the cavity 406 may further include an airflow system, a vacuum or vibration mechanism, or other airflow mechanism to promote airflow through the cavity 406 to reduce the temperature or cool the heat source 410.

[0180] In some embodiments of a wearable system or device, the device includes a port 420 for electrically connecting the device to a power source, such as for charging a battery 407 in the device. Additionally or alternatively, the port 420 electrically connects the wearable device to an external or remote computing device (e.g., a laptop, desktop computer, server, workstation, etc.) to download data from the device or upload system parameters or install updates to the wearable device. The wearable device may also include one or more user input elements 418 to turn the device on and off; input user-specific responses, features, or characteristics, customize the interface or functionality of the user device, etc.

[0181] In some embodiments, such as Fig.45As shown, a wearable system for detecting abnormal biological events includes a first system or device 400 located on the left limb of a user and a second system or device 500 located on the right limb of the user. The first and second devices 400, 500 can measure similar parameters or features so that the parameters or features can be compared over time and / or on an event-by-event basis to detect asymmetric biological responses. For example, a hardware processor that is part of the system or communicatively connected to a device (e.g., a laptop computer 450 or a mobile computing device 46) can be configured to compare a right blood volume signal (e.g., in response to applied heat) with a left blood volume signal (e.g., in response to applied heat) to determine whether an abnormal biological event has occurred. The right and left blood volume signals can be compared to baseline right and left blood volume signals, respectively, to account for any asymmetric baseline differences that may exist between the left and right sides. In addition, the method performed by the hardware processor can include: synchronizing signals received from the left and right limbs in a timely manner; and comparing synchronized signals from the left and right limbs to determine whether an abnormal biological event has occurred.

[0182] Watch now Fig.44 , which shows a connection element 408, which is configured to connect a wearable system for detecting abnormal events to a limb or body part of a user. For example, the connection element can be a tensionable belt for connecting a detection system or device to a limb or body part of a user. The tensionable belt is formed by or includes a stretchable material (e.g., silicone, rubber, lycra, spandex, spandex, neoprene, leather, fabric, etc.). Alternatively, a portion or segment 440 of the connection element can be stretchable so that the stretchable portion or segment 400 can be stretched or retracted by applying different amounts of tension to the connection element. Therefore, the connection element can be adjustable so that the connection element is suitable for the shape and size of multiple body parts. For example, the connection element can have an adjustable circumference. The connection element can also include a visual indicator 438 to indicate when the heating element, skin temperature sensor, blood volume sensor, or a combination thereof is fully connected to the skin surface to enable accurate sensor readings.

[0183] Reference Fig.37 , a system for detecting stroke may include collecting data from one or more sources, such as contact-based sources, non-contact-based sources, and sources that stimulate a response and then measure the response output. Fig.37 As shown, the system may include a main station or docking station and / or a measuring station for one or more measuring devices. For example, a heart rate monitor, a device for measuring asymmetric reactions or effects (e.g., a watch worn on each wrist), etc. may be included in the system. The system may be portable so that it may be located in a mobile stroke detection unit for rapid detection of stroke or may be located in the home of a high risk patient.

[0184] For example, Figure 8 As shown, a method for detecting tremor (i.e., asymmetric wrist movement) includes: measuring the acceleration in the x, y, and / or z planes of two limbs (e.g., two arms or two legs) of an individual; measuring the distance in the x, y, and / or z planes of the two limbs of the individual; and calculating the movement of each limb of the individual relative to the other limb. In some embodiments, symmetric movement indicates healthy, non-stroke movement, while asymmetric movement indicates tremor or a stroke event. Exemplary acceleration data (XYZ) is shown in Fig. 9 The distance data (XYZ) is shown in Fig.10 and distance (MM / S; moving) data are shown in Fig.11 In some embodiments, a specific pattern of time series movement is unique to an individual and is classified as a tremor based on data collected over time. For example, hours of tremor data can be collected, including wake cycles and sleep cycles. The statistical modeling of the tremor then becomes a label for each patient. This label also allows a baseline to be set for each patient. Again, this baseline behavior is unique to the individual, even unique to the individual's "wake" and "sleep cycles."

[0185] like Fig.26 As shown, an application downloaded and / or stored on a hardware component of a stroke detection system or computing device collates and analyzes acceleration and distance data sensed by a sensor (e.g., an accelerometer). A comparison of two data sets (i.e., Test Run 1 and Test Run 2) derived from devices located on two limbs (e.g., wrists) of a user is shown in Fig.26 For example, an application on a computing device may be configured to compare two acceleration data sets from devices located on two wrists of a user ( Fig. 27 ,32). Two distance datasets ( Fig.28 ,31); and two mobile datasets ( Fig.29 , 30 ).like Figure 29-30 As shown, the application on the computing device may further include a zoom feature, for example, for viewing a subset of the total data collected during a period of time (eg, overnight, during a seismic event, etc.).

[0186] In some embodiments of the device for detecting tremor or asymmetric movement, the device may include a feedback mechanism (e.g., visual, tactile, or audio) when a threshold is reached or exceeded or various comparison criteria are met, such as when the current movement pattern matches a previously identified tremor pattern of the individual. In some embodiments, a mobile computing device communicatively connected to the motion sensor or wearable device generates a vibration signal in the wearable device, sensor, and / or computing device if the comparison between the two signals exceeds a predetermined threshold.

[0187] To determine which implementations are best for stroke detection, several factors may be considered: alert 911 capability; passive monitoring; detection when the patient is alone; and detection when the patient is asleep. Additional factors may include, but are not limited to: full mobility; patient-specific algorithms; active patient engagement after passive alerts; detection of cognitively impaired patients; detection of prior stroke patients; detection of all strokes including posterior; diagnosis of stroke type; passive monitors to wake the patient; and initiation of stroke treatment. For example, if a possible stroke event is detected, the wearable system may initiate tactile, auditory, and / or visual alarms to determine whether the user is conscious, unconscious, experiencing other stroke symptoms, etc. If the patient does not respond within a predetermined time window, the stroke event may be notified to the caregiver, emergency services, physician, etc. The wearable device may be linked to a clinician computing system. The alarm may be transmitted directly to the clinician computing system, which may prompt a telemedicine assessment. The clinician may conduct an NIH stroke score assessment in response to the alarm and / or data received from the wearable system. In some cases, the wearable system can enable self-assessment by itself or in conjunction with a personal computing system, with the person walking and / or available witnesses in a FAST (Facial Drooping, Arm Weakness, Dysphasia, and Time) assessment.

[0188] In some cases, the wearable system can send a signal to the user's home automation system or to at least one electronically enabled door lock to unlock at least one door and / or disable the user's home alarm system in response to an alarm of a stroke event. The wearable system can also initiate the transmission of a floor plan access path that enters from the access point to the patient's location in a home or facility where the user has signs of a potential stroke. The patient's location can be determined based on a local area network or differential GPS. In some embodiments, the stroke detection device or system can trigger an audible alarm to warn the patient or caregiver that a stroke event has occurred, for example, while sleeping. The audible alarm can also enable emergency services to locate the patient when the patient enters the home. All of these measures help reduce the time required for emergency services or paramedics to reach the patient.

[0189] Home automation systems may also include smart displays and smart speakers. These smart displays and speakers may be used to transmit information to emergency medical responders, such as identifying medications that a patient should take and, if available, information about whether the patient is complying with the prescribed regimen. Information such as the identity of the physician, medical history, allergies, and the existence of a health care proxy or advance directive associated with the patient may also be communicated.

[0190] In addition, when an emergency service provider or physician is alerted, data including medical history can be transmitted directly from the wearable system or from a remote storage to the emergency service provider or physician computing system, initiated by a signal from the wearable system. In addition to the alert, the wearable system can also instruct the user to perform or automatically activate certain stroke treatments. Stroke treatments can include inducing hypothermia to provide a neuroprotectant to the patient. The wearable system can trigger the inhalation of cooling gas, activate a cooling helmet, activate an ultrasound helmet to rag, or ingest a drug patch or pill or trigger the application of a drug patch or pill. The trigger can be an instruction to the patient or medical responder, or automatically activated. In some cases, for ischemic stroke, the wearable system can trigger mechanisms to increase blood pressure and dilate blood vessels (through some of the mechanisms discussed above).

[0191] Treatment in response to detection of a potential stroke can be initiated by the patient (if they are conscious and competent), or by medical responders via a home automation system. Patients in certain high-risk categories may have been previously fitted with a wearable therapeutic device, which can be activated automatically in response to a signal indicating detection of a potential stroke, or by medical personnel following a clinical examination initiated by an alert from a wearable system.

[0192] In some embodiments, a stroke detection device or system can trigger an audible alarm to warn a patient or caregiver that a stroke event has occurred, for example, during sleep. The audible alarm can also enable emergency services to locate the patient when entering the home.

[0193] In any of the embodiments described herein, a stroke detection device or system can record the onset of a stroke event and / or provide a "last known well" indicator to help inform treatment decisions.

[0194] In some embodiments, a system for detecting a stroke includes a data processing module. The data processing module can be configured to extract a pattern. The pattern may indicate that any ischemic or hemorrhagic attack is very early, possibly imminent before the actual stroke event. In some embodiments, the pattern can be empirically determined, for example, based on population-wide analysis, cohort analysis, and / or individual analysis of the signal, to analyze parameters and / or patterns for indicating a stroke attack. In some embodiments, signal processing can use signal processing tools such as filtering, extraction, digitization, data deconvolution, machine learning, and / or other methods known in the art. Specifically, signal processing can use higher-order statistics to determine hidden patterns in the data. Using higher-order statistics called cumulants and their Fourier spectra (commonly referred to as multispectra) not only displays high-order amplitude information (such as amplitude information carried by power spectra or autocorrelations), but also can include phase information. Phase information can reveal significant features of the data that otherwise cannot be obtained from simple harmonic analysis. Another important feature of multispectra is the fact that they are blind to Gaussian processes. As a result, they can automatically process Gaussian processes, thereby improving the signal-to-noise ratio and allowing new detection. In some embodiments, multiple spectra and their operations can be selected to identify hidden patterns in sensed signals, such as BP(t), ECG(t)(), etc.

[0195] For example, Figure 53-55 As shown, a wearable system can collect electrocardiogram (ECG) data, pre-process the data, identify peaks in the data, and apply decision logic to the data. Fig.54 Electrocardiogram data collected over time is shown. Fig.55 RR intervals (ie, the time between heart beats shown in milliseconds) extracted from the electrocardiogram data are shown. Fig.53 The method 5300 shown in FIG. 5300 can be used to calculate an individual's heart rate and / or heart rate variability (i.e., the specific variation in the time between consecutive heart beats). Fig.53As shown, ECG data is input to method 5300, which detects QRS complexes (i.e., ventricular depolarization and main spikes in ECG signals) in electrocardiogram signals. Preprocessing at box S5310 includes applying signal processing techniques for QRS feature extraction. For example, preprocessing can be applied to reduce the effects of muscle noise, power line interference, baseline drift and / or T wave interference. For example, peak detection at box S5320 includes QRS peak detection with an adaptive threshold. Each potential peak is compared with a baseline value. A baseline skin temperature is established by measuring unstimulated skin over a period of time. Once a baseline is determined, stimulation (e.g., applying heat) can reach a time limit or a temperature limit. The temperature limit can be absolute or relative to the baseline skin temperature. The baseline value is updated according to the amplitude of the detected peak. The decision logic at block S5330 uses peak slope and / or peak-to-peak interval to classify current peaks as QRS, T waves, or false heartbeats.

[0196] like Figure 58-62 As shown in FIG. 1 , several methods can be used to process ECG data to extract various features, calculate one or more features (e.g., heart rate variability, heart rate, total power, etc.), etc. For example, time domain analysis ( Fig.58 )、Geometric Analysis( Fig.59 )、frequency domain analysis( Fig.60 ) and / or nonlinear analysis ( Fig.61 )analyze.

[0197] like Fig.58 As shown, ECG data (e.g., Fig.54 ) is fed to method 5800. The method includes: receiving ECG data of a user using ECG; detecting heartbeats in the ECG data (e.g., detecting R peaks in the ECG data) S5810; identifying and correcting irregular heartbeats (e.g., missed beats, extra and ectopic beats; using adjacent beats to correct each beat) S5820; identifying intervals between normal R peaks (i.e., NNI interval time series (NNIs)) S5830; preprocessing data (e.g., correcting outliers of NNI) S5840; and performing one or more analyses S5850. For example, Fig.59 The time domain analysis shown can be used to calculate heart rate (e.g., 60 divided by the mean of the NNIs); standard deviation of the NNIs (SDNN); root mean square of successive differences (RMSSD); and the percentage of adjacent NNIs that differ by more than 50 ms from each other ((pNN50)). In addition, for example, Fig.61As shown, the frequency domain analysis can be used to calculate relative power (e.g., relative power of each frequency band (VLF / LF, LF / LF, HF / LF)); normalized power (e.g., normalized power of LF and HF frequency bands (LF / (LF+HF), HF / (LF+HF)); LF / HF ratio (e.g., LF power / HF power); and / or total power (e.g., total power over all frequency bands). In addition, for example, Fig.60 As shown, geometric analysis can be used to calculate the baseline width of the interpolated triangle (TINN); and / or the ratio between the total number of NNIs and the maximum value of the NNI histogram distribution (i.e., the triangular index). In addition, for example, Fig.62 As shown, nonlinear analysis can be used to perform Poincare analysis (i.e., analyzing Poincare plots of NNI - SD1, SD2, SD ratio, ellipse area); DFA (detrended fluctuation analysis (i.e., short-term and long-term fluctuations of NNI); and / or entropy analysis (i.e., calculating approximate entropy, sample entropy, and fuzzy entropy of NNI).

[0198] In some embodiments, the data processing module can use continuously monitored or intermittently monitored physiological signals to distinguish changes from healthy "learned" or personalized baseline data. For example, the module can continuously learn signals from a single patient instead of using a statistical average taken from many patients. Customized reference signals can significantly improve small changes in physiological signals of individual patients. In some embodiments, physiological parameters can be processed as a function of time, which includes the shape of the curve changes, including hidden harmonics, changes in higher-order derivatives, etc.

[0199] Fig.33 One embodiment of various components of a data processing module is shown. The core engine of one embodiment of a data processing module may include one or more of the following parameters: fast processing, support for complex analysis, real-time stream processing, integration with NoSQL and RDBMS, and integration with Hadoop.

[0200] The data processing module may use various machine learning methods to identify patterns, extract patterns, identify parameters that indicate the onset of a stroke, etc. Machine learning can be broadly defined as the application of any computer-enabled algorithm that can be applied to a data set to find patterns in the data. Machine learning algorithms are used to determine the relationship between the inputs and outputs of a system using a learning data set that represents all the behaviors found in the system. This learning may be supervised or unsupervised. For example, Fig.34 As shown, a simple neural network called a multilayer perceptron (MLP) can be used to model various parameters or patterns of an individual, such as during sleep. Each node is a neuron using a nonlinear activation function. This simple neural network can be used to distinguish data that cannot be separated linearly. In some embodiments, such as Fig.35 As shown, a deep learning network can be used. The deep learning network can include leveraging recurrent neural network (RNN) implementations such as Fig.36 The system creates interconnected network layers, where each layer corresponds to a time slice. RNNs have proven to be very effective in processing time series data, assuming that the training inputs are time-dependent, can accurately model / predict changes over time, can generate actual output values ​​for data points rather than just giving ranges, and that each time slice is its own feed-forward network - specified by the user.

[0201] In some embodiments, the system for providing comprehensive stroke care includes one or more of the following: educational resources customized for patients based on demographics, stroke type, complications, medications, etc.; management tools to assist with drastic lifestyle changes, such as reminders (e.g., medications, rehabilitation appointments, etc.), collaborative care resources (e.g., for spouses, doctors, physical therapists, caregivers, etc.), activity tracking with continuous data collection via wearable devices, fitness tracking and guided meditation, stroke risk level assessments, etc.; a community with others as part of the First National Stroke Survivor Network, where stroke survivors can give and receive support and encouragement connecting patients and caregivers, "check in" with others in the group to ensure they are making progress toward their goals and are doing well psychologically, share stories and relate to others, receive telehealth / rehabilitation resources with speech therapists or mental health counselors; patient rehabilitation and monitoring, or other enabling technologies; setting recovery goals and tracking progress, cognitive assessment tools, etc.; stroke detection via calls / messages, communication tools for patients with aphasia, etc. to alert caregivers.

[0202] Implementation 1

[0203] The stroke detection capabilities of various functional symptoms, quantitative markers, and blood / fluid products are scored. The scoring criteria are as follows: should be based on scientific principles, should be highly sensitive (>90%), should have only very few false positives (<10%), and stroke detection should be passive (automatic). Each of these parameters is scored from 0 to 5, except for passive detection, which is scored on a scale of 0 (active detection) to 1 (passive detection). The scores are then multiplied by weighting factors, as shown in Table 1 below, and all weighting factors are added to produce a total score.

[0204] As shown in Tables 2 and 5 below, the functional symptoms with the highest total scores were facial muscle weakness, unilateral weakness, visual field restriction, gaze change, and speech change. Among these functional symptoms, only facial muscle weakness, unilateral weakness, and speech change can be detected passively.

[0205] Table 1. Analyzed factors and associated weights

[0206] Factor (each score (0-5)) Weight Factor Should be based on scientific principles 5 Should be highly sensitive (>90%) 5 Should have very few FPs (<10%) 2 Stroke detection should be passive (automatic) 4

[0207] Table 2. Analysis of functional symptoms of stroke

[0208]

[0209]

[0210] As shown in Tables 3 and 5, the quantitative markers with the highest total scores were cerebral blood flow, EEG asymmetry, carotid artery stenosis, volume impedance spectroscopy, and limb asymmetry. Among these quantitative markers, all are considered to be passively detectable.

[0211] Table 3. Analysis of quantitative symptoms of stroke

[0212]

[0213]

[0214] As shown in Tables 4 and 5, the products with the highest total scores are SMARTChip and ReST from Cornell University, none of which are considered passive detection.

[0215] Table 4. Analysis of products used for rapid stroke diagnosis

[0216]

[0217] Table 5. Results

[0218] Function Total score symptom #1 62 Facial muscle weakness #2 62 Unilateral weakness #3 56 Limited field of vision #4 56 Gaze changes #5 55 Speech changes

[0219]

[0220] In summary, a multivariate system for stroke detection may include detecting one or more of cerebral blood flow, EEG asymmetry, carotid stenosis, volume impedance spectroscopy, limb asymmetry, facial muscle weakness, unilateral weakness, and speech changes. In some embodiments, these different parameters may be measured at multiple locations and / or times to determine after the onset, occurrence, or effects of a stroke.

[0221] Implementation 2

[0222] Symmetrical and asymmetric acceleration and distance use The watch measures and displays it in a graphical representation in the computing device's application ( Figure 9-11 , 27-32). For this embodiment, the implementation also measures The resolution and current API capabilities of the Watch accelerometer sensor.

[0223] For this embodiment, the device is worn on the user's wrist. Any acceleration of the wrist is recorded and saved in the onboard database, including acceleration of the x-axis, y-axis, and z-axis. The computing device has a "sync" function that allows the data to be transferred to the computing device for analysis. Tables 6-8 show the acceleration of the wrist using the device worn on each wrist of the user. The watch acquires acceleration data, distance data, and calculated movement data (i.e., distance traveled). Figure 9-11 , as shown in 27-32, the data values ​​are recorded at each time point.

[0224] Table 6. Wrist acceleration (XYZ)

[0225] 30 60 90 120 150 Acceleration X axis ～10 ～0 ～0 ～15 ～0 Acceleration Y axis ～10 ～0 ～0 ～15 ～0 Acceleration Z axis ～10 ～0 ～0 ～15 ～0

[0226] Table 7. Wrist distance measurements

[0227] 30 60 90 120 150 Acceleration X axis ～10 ～0 ～0 ～15 ～0 Acceleration Y axis ～10 ～0 ～0 ～15 ～0 Acceleration Z axis ～10 ～0 ～0 ～15 ～0

[0228] Table 8. Wrist motion calculations

[0229] 10 20 30 40 Description tag 143 51 247 207

[0230] In summary, a system for stroke detection can include detecting one or more of: acceleration in the x-, y-, and / or z-axes; and / or distance in the x-, y-, and / or z-axes; and, in some embodiments, calculating distance traveled (i.e., movement) to determine asymmetric limb movements, gait, etc. that may indicate a stroke event.

[0231] The systems and methods of the preferred embodiments and variations thereof may be implemented and / or realized at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions. The instructions are preferably executed by a computer-executable component, which is preferably integrated with one or more portions of a hardware processor on the system and the device for detecting stroke and / or a computing device. The computer-readable medium may be stored on any suitable computer-readable medium, such as RAM, ROM, flash memory, EEPROM, optical devices (e.g., CD or DVD), hard drives, floppy drives, or any suitable device. The computer-executable component is preferably a general-purpose or application-specific hardware processor, but any suitable dedicated hardware or hardware / firmware combination may alternatively or additionally execute instructions.

[0232] As used in the specification and claims, the singular forms "a," "an," and "the" include singular and plural references unless the context clearly dictates otherwise. For example, the term "signal" may include, and is intended to include, a plurality of signals. At times, the claims and the disclosure may include terms such as "plurality," "one or more," or "at least one"; however, the absence of such terms does not imply, and should not be interpreted to mean that a plurality is not contemplated.

[0233] When used before a numerical expression or range (e.g., to define a length or pressure), the term "about" or "approximately" means that the approximate value may vary by (+) or (-) 5%, 1%, or 0.1%. All numerical ranges provided herein include the stated beginning and ending values. The term "substantially" means a majority (i.e., greater than 50%) or substantially all of a device, substance, or composition.

[0234] As used herein, the term "comprising" or "including" means that the device, system and method include the elements, and may also include any other elements. The term "consisting essentially of" means that the device, system and method include the listed elements, and exclude other elements that are important to the combination for the purpose. Therefore, a system or method consisting essentially of elements as defined herein will not exclude other materials, features or steps that will not substantially affect the basic and novel characteristics of the claimed content. The term "consisting of" means that the device, system and method include the elements, and exclude anything other than unimportant or insignificant elements or steps. Embodiments defined by each of these transition terms are within the scope of the present disclosure.

[0235] The examples and diagrams included herein show by way of example and not limitation, specific embodiments in which the subject matter can be implemented. Other embodiments can be utilized and derived therefrom, so that structural and logical replacement and changes can be made without departing from the scope of the present disclosure. These embodiments of the subject matter of the present invention may be referred to individually or collectively by the term "invention" herein, only for convenience, rather than intentionally and actively limiting the scope of the present application to any single invention or inventive concept, if multiple inventions or inventive concepts are actually disclosed. Therefore, although specific embodiments have been shown and described herein, any arrangement calculated to achieve the same purpose can replace the specific embodiments shown. The present disclosure is intended to cover any and all modifications or variations of various embodiments. After reviewing the above description, it will be apparent to those skilled in the art that the above-mentioned embodiments and the combination of other embodiments not specifically described herein will be apparent.

[0236] Exemplary embodiments

[0237] A wearable system for detecting abnormal biological events in a person, comprising one or more of the following:

[0238] a body having a first surface opposite a second surface that contacts a skin surface of a person;

[0239] a heat source in communication with the skin surface, wherein the heat source is configured to heat the skin surface to a target temperature;

[0240] a skin temperature sensor positioned on the second surface and configured to measure a temperature of the skin surface in contact with the heat source;

[0241] a blood volume sensor positioned on the second surface and configured to measure blood volume at the skin surface; and

[0242] a hardware processor communicatively connected to the heat source, the blood volume sensor, the skin temperature sensor, and an ambient temperature sensor, the ambient temperature sensor configured to measure a temperature of an environment surrounding the wearable system, wherein the hardware processor is configured to:

[0243] A baseline blood volume signal is received from the blood volume sensor.

[0244] A heating signal is output to the heat source to initiate a heating cycle, wherein the heating cycle includes heating the skin surface to the target temperature.

[0245] In response to the skin surface reaching the target temperature, a second blood volume signal is received from the blood volume sensor.

[0246] comparing the second blood volume signal to the baseline blood volume signal, and

[0247] A determination is made based on the comparison whether an abnormal biological event has occurred.

[0248] The wearable system of any embodiment disclosed herein, wherein the second blood volume signal comprises a set of blood volume signals such that the blood volume at the skin surface is repeatedly measured before, during, and after a heating cycle of the heat source.

[0249] The wearable system of any embodiment disclosed herein, wherein the second blood volume signal comprises a plurality of blood volume signals such that the blood volume at the skin surface is continuously measured before, during and after a heating cycle of the heat source.

[0250] The wearable system of any embodiment disclosed herein, wherein the hardware processor is further configured to receive a second blood volume signal after the target temperature is reached, after a predetermined period of time has expired, or after one or more heating cycles have expired.

[0251] The wearable system of any embodiment disclosed herein, wherein the comparing comprises calculating a baseline ratio of alternating current (AC) to direct current (DC) for the baseline blood volume signal and a second ratio of AC to DC for the second blood volume signal, and comparing the baseline ratio to the second ratio.

[0252] The wearable system of any embodiment disclosed herein, wherein the ambient temperature sensor is positioned on a first side of a body of the wearable system.

[0253] The wearable system of any embodiment disclosed herein further includes a remote computing device in communication with the wearable system and includes an ambient temperature sensor.

[0254] The wearable system of any embodiment disclosed herein, wherein the remote computing device comprises one of a laptop computer, a cellular device, a workstation, a server, a desktop computer, a personal digital assistant, a second wearable system or device, or a netbook.

[0255] The wearable system of any embodiment disclosed herein, wherein the heat source is positioned on the second surface of the body.

[0256] The wearable system of any embodiment disclosed herein, wherein the hardware processor is further configured to:

[0257] Baseline temperature signals are received from the skin temperature sensor and the ambient temperature sensor.

[0258] determining the target temperature based on the baseline temperature signal, and

[0259] Determine if the target temperature is below the maximum temperature value.

[0260] The wearable system of any embodiment disclosed herein, wherein the hardware processor is further configured to cycle the heat source to maintain the target temperature.

[0261] The wearable system of any embodiment disclosed herein further includes one or more electrodermal activity sensors located on the second surface.

[0262] The wearable system of any of the embodiments disclosed herein, wherein the one or more electrodermal activity sensors are spaced apart from the heating element by about 0.25 inches to about 4 inches.

[0263] The wearable system of any embodiment disclosed herein further includes one or more motion sensors configured to measure motion of a body part connected to the wearable system.

[0264] The wearable system of any embodiment disclosed herein, wherein the first surface and the second surface define a cavity therebetween to provide airflow between the first surface and the second surface.

[0265] The wearable system of any embodiment disclosed herein, wherein the hardware processor is located on or within the first surface.

[0266] The wearable system of any embodiment disclosed herein, wherein a cavity defined by the first surface and the second surface physically separates the heat source from a hardware processor on or within the first surface.

[0267] The wearable system of any embodiment disclosed herein, wherein the cavity defined by the first surface and the second surface has a sufficient volume to facilitate cooling of the heat source between heating cycles.

[0268] The wearable system of any embodiment disclosed herein, wherein the abnormal biological event comprises a stroke event.

[0269] The wearable system of any embodiment disclosed herein, wherein the wearable system is located on a left limb of a user and the second wearable system is located on a right limb of the user, wherein the second wearable system includes a second heating element, a second skin temperature sensor, and a second blood volume sensor, wherein the hardware processor is further configured to compare the right blood volume signal with the left blood volume signal to determine whether an abnormal biological event has occurred.

[0270] The wearable system of any embodiment disclosed herein, wherein the hardware processor is further configured to:

[0271] Synchronize the signals received from the left and right limbs in time; and

[0272] The synchronized signals from the left and right limbs are compared to determine whether an abnormal biological event has occurred.

[0273] The wearable system of any embodiment disclosed herein, wherein the comparison takes into account a baseline difference between the left limb and the right limb.

[0274] The wearable system of any embodiment disclosed herein further comprises a tensionable strap connected to the body.

[0275] The wearable system of any embodiment disclosed herein, wherein the tensionable band further comprises a visual indicator to indicate when one or more of the heating element, the skin temperature sensor, the blood volume sensor, or a combination thereof is sufficiently connected to the skin surface to enable accurate sensor readings.

[0276] The wearable system of any embodiment disclosed herein, wherein one or more ends of the tensionable band are connected to the body at a position centered relative to the one or more sensors located on the second surface.

[0277] The wearable system of any embodiment disclosed herein, wherein the heat source is concentrically positioned around one or both of the blood volume sensor and the skin temperature sensor.

[0278] The wearable system of any embodiment disclosed herein, wherein the blood volume sensor comprises a photoplethysmographic sensor or an impedance plethysmographic sensor.

[0279] The wearable system of any embodiment disclosed herein, wherein the skin temperature sensor comprises a thermocouple, a resistance temperature detector, a thermistor, or an infrared temperature sensor.

[0280] The wearable system of any embodiment disclosed herein further includes a support structure connected to the heat source, wherein the support structure is configured to connect the heat source to the second surface and at least partially expose the heat source to the cavity.

[0281] The wearable system of any embodiment disclosed herein, wherein the blood volume sensor is further configured to measure one or more of heart rate, heart rate variability, or oxygen saturation.

[0282] The wearable system of any embodiment disclosed herein, wherein the target temperature is personalized to the user.

[0283] The wearable system of any embodiment disclosed herein, wherein personalizing the target temperature comprises receiving user input related to the perceived temperature of the skin surface.

[0284] The wearable system of any embodiment disclosed herein, wherein the personalization of the target temperature is based on a signal received from a blood volume sensor.

[0285] The wearable system of any embodiment disclosed herein, wherein the heat source comprises one of a heating element or ambient temperature.

[0286] The wearable system of any embodiment disclosed herein, wherein the hardware processor is configured to transmit electronic information to a first electronic system in response to the determination of the abnormal biological event, and the first electronic system is configured to electronically manage a home automation system.

[0287] The wearable system of any embodiment disclosed herein, wherein the home automation system includes a door lock, and wherein the electronic information is configured to instruct the first electronic system to unlock the door lock.

[0288] The wearable system of any embodiment disclosed herein, wherein the home automation system includes a home alarm system, and wherein the electronic information is configured to instruct the first electronic system to disable the home alarm system.

[0289] The wearable system of any embodiment disclosed herein, wherein the home automation system includes a display, and wherein the electronic information is configured to instruct the first electronic system to display medical information of the user.

[0290] The wearable system of any embodiment disclosed herein, wherein the medical information includes medication information and / or medication regimen compliance.

[0291] The wearable system of any embodiment disclosed herein, wherein the home automation system includes a display, and wherein the electronic information is configured to instruct the first electronic system to display a stroke treatment user interface.

[0292] The wearable system of any embodiment disclosed herein, wherein the home automation system includes a speaker system, and wherein the electronic information is configured to instruct the first electronic system to trigger an audible alarm using the speaker system.

[0293] The wearable system of any embodiment disclosed herein, wherein the hardware processor is further configured to issue an alert to a third-party computing system in response to the determination of the abnormal biological event.

[0294] The wearable system of any embodiment disclosed herein, wherein the third party computing system includes an emergency services system.

[0295] The wearable system of any embodiment disclosed herein, wherein the third party computing system comprises a clinician computing system.

[0296] The wearable system of any embodiment disclosed herein, wherein the hardware processor is further configured to initiate a treatment regimen in response to detection of an abnormal biological event.

[0297] The wearable system of any embodiment disclosed herein further includes a wearable processing system, and the processing scheme is configured to activate the wearable processing system.

[0298] The wearable system of any embodiment disclosed herein, wherein the wearable processing system comprises an ultrasound helmet.

[0299] The wearable system of any embodiment disclosed herein, wherein the wearable processing system comprises a cooling gas delivery system.

[0300] The wearable system of any embodiment disclosed herein, wherein the wearable processing system comprises a cooling helmet.

[0301] A wearable system for detecting abnormal biological events in a person, comprising one or more of the following:

[0302] a body having a first surface opposite to a second surface that contacts a skin surface of a person, the first surface and the second surface defining a cavity therebetween to provide airflow between the first surface and the second surface;

[0303] a heating element positioned on the second surface and configured to heat the skin surface for a predetermined period of time;

[0304] a skin temperature sensor positioned on the second surface and configured to measure a temperature of the skin surface in contact with the heating element;

[0305] a blood volume sensor positioned on the second surface and configured to measure blood volume at the skin surface;

[0306] a hardware processor communicatively connected to the heating element, the blood volume sensor, the skin temperature sensor, and an ambient temperature sensor, the ambient temperature sensor being configured to measure a temperature of an environment surrounding the wearable system, wherein the hardware processor is configured to:

[0307] A baseline blood volume signal is received from the blood volume sensor.

[0308] A heating signal is output to the heating element to initiate a heating cycle, wherein the heating cycle includes heating the skin surface to a target temperature.

[0309] In response to the skin surface reaching the target temperature, a second blood volume signal is received from the blood volume sensor.

[0310] comparing the second blood volume signal to the baseline blood volume signal, and

[0311] A determination is made based on the comparison whether an abnormal biological event has occurred.

[0312] A wearable system for detecting abnormal biological events in a person, comprising one or more of the following:

[0313] a body having a first surface opposite a second surface that contacts a skin surface of a person;

[0314] a heat source in communication with the skin surface, wherein the heat source is configured to heat the skin surface to a target temperature;

[0315] a skin temperature sensor positioned on the second surface and configured to measure a temperature of a skin surface in contact with the heat source;

[0316] a sensor positioned on the second surface and configured to measure a parameter of interest of the person; and

[0317] a hardware processor communicatively connected to the heat source, the sensor, the skin temperature sensor, and an ambient temperature sensor, the ambient temperature sensor being configured to measure a temperature of an environment surrounding the wearable system, wherein the hardware processor is configured to:

[0318] A baseline sensor signal is received from the sensor.

[0319] A heating signal is output to the heat source to initiate a heating cycle, wherein the heating cycle includes heating the skin surface to the target temperature.

[0320] A second sensor signal is received from the sensor in response to the skin surface reaching the target temperature.

[0321] comparing the second sensor signal to the baseline sensor signal, and

[0322] A determination is made based on the comparison whether an abnormal biological event has occurred.

[0323] The wearable system of any embodiment disclosed herein, wherein the sensor is selected from a stretch sensor, a skin electrode activity sensor, an electrocardiogram sensor, a camera, or a blood volume sensor.

[0324] The wearable system of any embodiment disclosed herein, wherein the parameter of interest includes one or more of the following: blood pressure, heart rate, heart rate variability, gaze, facial expression, skin conductance response, vasodilation response, or dilation response.

[0325] A wearable system for detecting abnormal biological events in a person, comprising one or more of the following:

[0326] a body having a first surface opposite to a second surface that contacts a skin surface of a person;

[0327] a stimulation source in communication with the skin surface, wherein the stimulation source is configured to apply stimulation to the skin surface;

[0328] a blood volume sensor positioned on the second surface and configured to measure blood volume at the skin surface; and

[0329] a hardware processor communicatively connected to the stimulation source and the blood volume sensor, wherein the hardware processor is configured to:

[0330] A baseline blood volume signal is received from the blood volume sensor.

[0331] A stimulation signal is output to the stimulation source to start a stimulation cycle.

[0332] In response to initiation of the stimulation cycle, a second blood volume signal is received from the blood volume sensor.

[0333] comparing the second blood volume signal to the baseline blood volume signal, and

[0334] A determination is made based on the comparison whether an abnormal biological event has occurred.

[0335] The wearable system of any embodiment disclosed herein, wherein the stimulation source comprises a heat source.

[0336] The wearable system of any embodiment disclosed herein, wherein the stimulation source comprises a power source.

[0337] The wearable system of any embodiment disclosed herein, wherein the comparing comprises determining a change in the vasodilatory response.

[0338] The wearable system of any embodiment disclosed herein, wherein the stimulation source comprises a Peltier cooler.

[0339] The wearable system of any embodiment disclosed herein, wherein the second blood volume signal comprises a set of blood volume signals such that the blood volume at the skin surface is repeatedly measured before, during, and after a stimulation cycle.

[0340] The wearable system of any embodiment disclosed herein, wherein the second blood volume signal comprises a plurality of blood volume signals such that the blood volume at the skin surface is continuously measured before, during and after a stimulation cycle.

[0341] The wearable system of any embodiment disclosed herein, wherein the hardware processor is further configured to receive a second blood volume signal after target stimulation is achieved, after a predetermined period of time has expired, or after one or more stimulation cycles have ended.

[0342] The wearable system of any embodiment disclosed herein, wherein the comparing comprises calculating a baseline ratio of alternating current (AC) to direct current (DC) for the baseline blood volume signal and a second ratio of AC to DC for the second blood volume signal, and comparing the baseline ratio to the second ratio.

[0343] The wearable system of any embodiment disclosed herein, wherein the blood volume sensor is positioned on a first side of a body of the wearable system.

[0344] The wearable system of any embodiment disclosed herein further includes a remote computing device in communication with the wearable system and includes a blood volume sensor.

[0345] The wearable system of any embodiment disclosed herein, wherein the remote computing device comprises one of a laptop computer, a cellular device, a workstation, a server, a desktop computer, a personal digital assistant, a second wearable system or device, or a netbook.

[0346] The wearable system of any embodiment disclosed herein, wherein the stimulation source is positioned on a second surface of the body.

[0347] The wearable system of any embodiment disclosed herein, wherein the hardware processor is further configured to:

[0348] A baseline blood volume signal is received from the blood volume sensor.

[0349] determining the target blood volume based on the baseline blood volume signal, and

[0350] It is determined whether the target blood volume is lower than the maximum blood volume value.

[0351] The wearable system of any embodiment disclosed herein, wherein the hardware processor is further configured to cycle the stimulation source to maintain the target blood volume.

[0352] The wearable system of any embodiment disclosed herein further includes one or more electrodermal activity sensors located on the second surface.

[0353] The wearable system of any of the embodiments disclosed herein, wherein the one or more electrodermal activity sensors are spaced apart from the stimulation source by about 0.25 inches to about 4 inches.

[0354] The wearable system of any embodiment disclosed herein further includes one or more motion sensors configured to measure motion of a body part connected to the wearable system.

[0355] The wearable system of any embodiment disclosed herein, wherein the first surface and the second surface define a cavity therebetween to provide airflow between the first surface and the second surface.

[0356] The wearable system of any embodiment disclosed herein, wherein the hardware processor is located on or within the first surface.

[0357] The wearable system of any embodiment disclosed herein, wherein a cavity defined by the first surface and the second surface physically separates the stimulation source from a hardware processor on or within the first surface.

[0358] The wearable system of any embodiment disclosed herein, wherein the cavity defined by the first surface and the second surface has a sufficient volume to facilitate cooling of the stimulation source between stimulation cycles.

[0359] The wearable system of any embodiment disclosed herein, wherein the abnormal biological event comprises a stroke event.

[0360] A wearable system of any embodiment disclosed herein, wherein the wearable system is positioned on a left limb of a user and a second wearable system is positioned on a right limb of the user, wherein the second wearable system comprises a second stimulus source and a second blood volume sensor, wherein the hardware processor is further configured to compare the right blood volume signal with the left blood volume signal to determine whether an abnormal biological event has occurred.

[0361] The wearable system of any embodiment disclosed herein, wherein the hardware processor is further configured to:

[0362] Synchronize the signals received from the left and right limbs in time; and

[0363] The synchronized signals from the left and right limbs are compared to determine whether an abnormal biological event has occurred.

[0364] The wearable system of any embodiment disclosed herein, wherein the comparison takes into account a baseline difference between the left limb and the right limb.

[0365] The wearable system of any embodiment disclosed herein further comprises a tensionable strap connected to the body.

[0366] The wearable system of any embodiment disclosed herein, wherein the tensionable band further comprises a visual indicator that indicates when one or more of the stimulation source, the blood volume sensor, or a combination thereof is sufficiently connected to the skin surface to enable accurate sensor readings.

[0367] The wearable system of any embodiment disclosed herein, wherein one or more ends of the tensionable band are connected to the body at a position centered relative to the one or more sensors located on the second surface.

[0368] The wearable system of any embodiment disclosed herein, wherein the stimulation source is positioned concentrically around the blood volume sensor.

[0369] The wearable system of any embodiment disclosed herein, wherein the blood volume sensor comprises a photoplethysmographic sensor or an impedance plethysmographic sensor.

[0370] The wearable system of any embodiment disclosed herein further includes a support structure connected to the stimulation source, wherein the support structure is configured to connect the stimulation source to the second surface and at least partially expose the stimulation source to the cavity.

[0371] The wearable system of any embodiment disclosed herein, wherein the blood volume sensor is further configured to measure one or more of heart rate, heart rate variability, or oxygen saturation.

[0372] The wearable system of any embodiment disclosed herein, wherein the stimulation cycle is personalized to the user.

[0373] The wearable system of any embodiment disclosed herein, wherein personalizing the stimulation cycle comprises receiving user input related to the perceived stimulation of the skin surface.

[0374] The wearable system of any embodiment disclosed herein, wherein personalization of the stimulation cycle is based on a signal received from a blood volume sensor.

[0375] The wearable system of any embodiment disclosed herein, wherein the stimulus source comprises one of a heating element or ambient temperature.

[0376] The wearable system of any embodiment disclosed herein, wherein the hardware processor is configured to transmit electronic information to a first electronic system in response to the determination of the abnormal biological event, and the first electronic system is configured to electronically manage a home automation system.

[0377] The wearable system of any embodiment disclosed herein, wherein the home automation system includes a door lock, and wherein the electronic information is configured to instruct the first electronic system to unlock the door lock.

[0378] The wearable system of any embodiment disclosed herein, wherein the home automation system includes a home alarm system, and wherein the electronic information is configured to instruct the first electronic system to disable the home alarm system.

[0379] The wearable system of any embodiment disclosed herein, wherein the home automation system includes a display, and wherein the electronic information is configured to instruct the first electronic system to display medical information of the user.

[0380] The wearable system of any embodiment disclosed herein, wherein the medical information includes medication information and / or medication regimen compliance.

[0381] The wearable system of any embodiment disclosed herein, wherein the home automation system includes a display, and wherein the electronic information is configured to instruct the first electronic system to display a stroke treatment user interface.

[0382] The wearable system of any embodiment disclosed herein, wherein the home automation system includes a speaker system, and wherein the electronic information is configured to instruct the first electronic system to trigger an audible alarm using the speaker system.

[0383] The wearable system of any embodiment disclosed herein, wherein the hardware processor is further configured to issue an alert to a third-party computing system in response to the determination of the abnormal biological event.

[0384] The wearable system of any embodiment disclosed herein, wherein the third party computing system includes an emergency services system.

[0385] The wearable system of any embodiment disclosed herein, wherein the third party computing system comprises a clinician computing system.

[0386] The wearable system of any embodiment disclosed herein, wherein the hardware processor is further configured to initiate a treatment regimen in response to detection of an abnormal biological event.

[0387] The wearable system of any embodiment disclosed herein further includes a wearable processing system, and the processing scheme is configured to activate the wearable processing system.

[0388] The wearable system of any embodiment disclosed herein, wherein the wearable processing system comprises an ultrasound helmet.

[0389] The wearable system of any embodiment disclosed herein, wherein the wearable processing system comprises a cooling gas delivery system.

[0390] The wearable system of any embodiment disclosed herein, wherein the wearable processing system comprises a cooling helmet.

[0391] A system for detecting abnormal biological events in a human, the system comprising one or more of the following:

[0392] a first stimulation source configured to stimulate a first tissue site on the right side of the person's body at a first time;

[0393] a second stimulation source configured to stimulate a second tissue site on the left side of the person's body at a second time; and

[0394] One or more hardware processors configured to:

[0395] determining a first vasodilatory response based on stimulation of the first tissue site;

[0396] determining a second vasodilatory response based on stimulation of the second tissue site;

[0397] determining one or more differences in the first vasodilator response and the second vasodilator response; and

[0398] An abnormal biological event is detected based on one or more differences in the determined first vasodilator response and the second vasodilator response.

[0399] The system of any embodiment disclosed herein, wherein the first stimulation source comprises at least one or more of: a heat source, a cooling source, or a power source.

[0400] The system of any embodiment disclosed herein, wherein the second stimulation source comprises at least one or more of: a heat source, a cooling source, or an electrical source.

[0401] The system of any embodiment disclosed herein, wherein the first time is synchronized with the second time.

[0402] The system of any of the embodiments disclosed herein, wherein the first vasodilator response is determined based on a parameter responsive to a measurement from the first blood volume sensor.

[0403] The system of any of the embodiments disclosed herein, wherein the second vasodilator response is determined based on a parameter responsive to a measurement from a second blood volume sensor.

[0404] The system of any of the embodiments disclosed herein, wherein the first vasodilatory response is determined based on a parameter responsive to a measurement from the electrical activity sensor.

[0405] The system of any of the embodiments disclosed herein, wherein the second vasodilatory response is determined based on a parameter responsive to a measurement from the electrical activity sensor.

[0406] The system of any of the embodiments disclosed herein, wherein the one or more hardware processors are further configured to determine a first baseline vasodilator response prior to stimulation at the first tissue site, and determine a second baseline vasodilator response prior to stimulation at the second tissue site.

[0407] A wearable system for detecting a stroke event in a person, the wearable system comprising one or more of the following:

[0408] A first wearable device, the first wearable device is configured to contact a first skin surface of a person, the first wearable device is configured to be fixed to a left limb of the person, and the first wearable device includes:

[0409] a first heat source in communication with the first skin surface, wherein the first heat source is configured to heat the first skin surface to a first target temperature;

[0410] a first skin temperature sensor configured to measure a first temperature of the first skin surface; and

[0411] a first blood volume sensor configured to measure a first blood volume at a first tissue site proximate to the first skin surface;

[0412] a second wearable device, the second wearable device being configured to contact a second skin surface of the person, the second wearable device being configured to be fixed to a right limb of the person, the second wearable device comprising:

[0413] a second heat source in communication with the second skin surface, wherein the second heat source is configured to heat the second skin surface to a second target temperature;

[0414] a second skin temperature sensor configured to measure a second temperature of the second skin surface; and

[0415] a second blood volume sensor configured to measure a second blood volume at a second tissue site proximate to the second skin surface; and

[0416] One or more hardware processors configured to:

[0417] receiving a first baseline blood volume signal from the first blood volume sensor;

[0418] receiving a second baseline blood volume signal from the second blood volume sensor;

[0419] outputting a first heating signal to the first heat source to initiate a first heating cycle at a first time, wherein the first heating cycle includes heating the first skin surface to the first target temperature;

[0420] receiving a first post-stimulation blood volume signal from the first blood volume sensor in response to the first skin surface reaching the first target temperature;

[0421] outputting a second heating signal to the second heat source to initiate a second heating cycle at a second time, wherein the second heating cycle includes heating the second skin surface to the second target temperature;

[0422] receiving a second post-stimulation blood volume signal from the second blood volume sensor in response to the second skin surface reaching the second target temperature; and

[0423] A stroke event is determined based on the first baseline blood volume signal, the second baseline blood volume signal, the first post-stimulation blood volume signal, and the second post-stimulation blood volume signal.

[0424] The wearable system of any embodiment disclosed herein, wherein the second post-stimulation blood volume signal comprises a set of blood volume signals such that the second blood volume of the second skin surface is repeatedly measured before, during, and after a heating cycle of the second heat source.

[0425] The wearable system of any embodiment disclosed herein, wherein the second post-stimulation blood volume signal comprises a plurality of blood volume signals such that the second blood volume of the second skin surface is continuously measured before, during and after a heating cycle of the second heat source.

[0426] The wearable system of any embodiment disclosed herein, wherein the one or more hardware processors are further configured to calculate a first baseline ratio of alternating current (AC) to direct current (DC) of the first baseline blood volume signal and a second baseline ratio of AC to DC of the second blood volume signal, and compare the first baseline ratio to the second baseline ratio.

[0427] The wearable system of any embodiment disclosed herein, wherein the first wearable device further comprises an ambient temperature sensor.

[0428] The wearable system of any embodiment disclosed herein further includes a remote computing device communicatively connected to the first wearable device and the second wearable device.

[0429] The wearable system of any embodiment disclosed herein, wherein the remote computing device comprises one of a laptop computer, a cellular device, a workstation, a server, a desktop computer, a personal digital assistant, a second wearable system or device, or a netbook.

[0430] The wearable system of any embodiment disclosed herein further includes one or more electrodermal activity sensors.

[0431] The wearable system of any of the embodiments disclosed herein, wherein the one or more electrodermal activity sensors are spaced apart from at least one of the first heat source or the second heat source by about 0.25 inches to about 4 inches.

[0432] The wearable system of any embodiment disclosed herein further includes one or more motion sensors configured to measure movement of a body part connected to at least one of the first wearable device or the second wearable device.

[0433] The wearable system of any embodiment disclosed herein further comprises at least one tensionable strap connected to the body.

[0434] The wearable system of any embodiment disclosed herein, wherein the first heat source is concentrically positioned around one or both of the first blood volume sensor and the first skin temperature sensor.

[0435] The wearable system of any embodiment disclosed herein, wherein the second heat source is concentrically positioned around one or both of the second blood volume sensor and the second skin temperature sensor.

[0436] The wearable system of any embodiment disclosed herein, wherein the first blood volume sensor comprises a photoplethysmographic sensor or an impedance plethysmographic sensor.

[0437] The wearable system of any embodiment disclosed herein, wherein the second blood volume sensor comprises a photoplethysmographic sensor or an impedance plethysmographic sensor.

[0438] The wearable system of any embodiment disclosed herein, wherein the first skin temperature sensor comprises a thermocouple, a resistance temperature detector, a thermistor, or an infrared temperature sensor.

[0439] The wearable system of any embodiment disclosed herein, wherein the second skin temperature sensor comprises a thermocouple, a resistance temperature detector, a thermistor, or an infrared temperature sensor.

[0440] The wearable system of any embodiment disclosed herein, wherein the first blood volume sensor is further configured to measure one or more of heart rate, heart rate variability, or oxygen saturation.

[0441] The wearable system of any embodiment disclosed herein, wherein the second blood volume sensor is further configured to measure one or more of heart rate, heart rate variability, or oxygen saturation.

[0442] The wearable system of any embodiment disclosed herein, wherein at least one of the first target temperature and the second target temperature is user personalized.

Claims

1. A wearable system for detecting abnormal biological events in a person, comprising: A first wearable device, configured to contact a first skin surface of a person, the first wearable device configured to be fixed to a left limb of the person, the first wearable device comprising: a first body having a first surface opposite to a second surface, the second surface being in contact with a first skin surface of a person; a first heat source in communication with the first skin surface, wherein the first heat source is configured to heat the first skin surface to a first offset temperature, wherein the first offset temperature is a baseline skin temperature of the first skin surface plus about 1 degree to about 20 degrees; a first skin temperature sensor positioned on the second surface and configured to measure a temperature of the skin surface in contact with the first heat source; and a first blood volume sensor positioned on the second surface and configured to measure blood volume at the first skin surface; A second wearable device, configured to contact a second skin surface of the person, the second wearable device configured to be fixed to a right limb of the person, the second wearable device comprising: a second body having a first surface opposite to a second surface that contacts a second skin surface of a person; a second heat source in communication with a second skin surface, wherein the second heat source is configured to heat the second skin surface to a second offset temperature, wherein the second offset temperature is the baseline skin temperature of the second skin surface plus about 1 degree to about 20 degrees; a second skin temperature sensor positioned on the second surface and configured to measure a second temperature of the second skin surface; and a second blood volume sensor positioned on the second surface and configured to measure a second blood volume at a second tissue site proximate to the second skin surface; and one or more hardware processors communicatively connected to the first and second wearable devices and an ambient temperature sensor configured to measure a temperature of an environment surrounding the wearable system, wherein the one or more hardware processors are configured to: receiving a first baseline blood volume signal from the first blood volume sensor, receiving a second baseline blood volume signal from the second blood volume sensor, outputting a first heating signal to the first heat source to initiate a first heating cycle, wherein the first heating cycle includes heating the first skin surface to the first offset temperature, receiving a first post-stimulation blood volume signal from the first blood volume sensor in response to the first skin surface reaching the first offset temperature, outputting a second heating signal to the second heat source to initiate a second heating cycle, wherein the second heating cycle includes heating the skin surface to the second offset temperature, receiving a second post-stimulation blood volume signal from the second blood volume sensor in response to the second skin surface reaching the second offset temperature, Calculate the left difference between the first post-stimulation blood volume signal and the first baseline blood volume signal, Calculate the right-side difference between the second post-stimulation blood volume signal and the second baseline blood volume signal, compare the left difference to the right difference, and A determination is made based on the comparison whether an abnormal biological event has occurred.

2. A wearable system according to claim 1, wherein the post-stimulation blood volume signal comprises a set of blood volume signals such that the blood volumes of the first and second skin surfaces are repeatedly measured before, during and after the heating cycles of the first and second heat sources.

3. A wearable system according to claim 1, wherein the post-stimulation blood volume signal includes multiple blood volume signals so that the blood volume of the first and second skin surfaces is continuously measured before, during and after the heating cycle of the first and second heat sources.

4. The wearable system of claim 1 , wherein the one or more hardware processors are further configured to receive the post-stimulation blood volume signal after the offset temperature is reached, after a predetermined period of time has expired, or after one or more heating cycles have ended.

5. The wearable system of claim 1 , wherein comparing comprises calculating a baseline ratio of alternating current to direct current of the baseline blood volume signal and a second ratio of alternating current to direct current of the post-stimulation blood volume signal, and comparing the baseline ratio to the second ratio.

6. The wearable system of claim 1, wherein the ambient temperature sensor is positioned on a first surface of the first or second body.

7. The wearable system of claim 1, further comprising a remote computing device communicatively coupled to the wearable system, wherein the remote computing device comprises the ambient temperature sensor.

8. The wearable system of claim 7, wherein the remote computing device comprises one of: a laptop computer, a cellular device, a workstation, a server, a desktop computer, a personal digital assistant, a second wearable system, or a netbook.

9. The wearable system of claim 1, wherein the first and second heat sources are positioned on the second surface of the first or second body.

10. The wearable system of claim 9, wherein the one or more hardware processors are further configured to: receiving baseline temperature signals from the first and second skin temperature sensors and the ambient temperature sensor, determining the first and second offset temperatures based on the baseline temperature signal, and A determination is made as to whether the first and second offset temperatures are below a maximum temperature value.

11. The wearable system of claim 10, wherein the one or more hardware processors are further configured to cycle the first and second heat sources to maintain the first and second offset temperatures.

12. The wearable system of claim 1, further comprising one or more electrodermal activity sensors positioned on the second surface of the first or second wearable device.

13. The wearable system of claim 12, wherein the one or more electrodermal activity sensors are spaced apart from the first heat source or the second heat source by about 0.25 inches to about 4 inches.

14. The wearable system of claim 1, further comprising one or more motion sensors configured to measure movement of a body part connected to at least one of the first wearable device or the second wearable device.

15. The wearable system of claim 1, wherein the first surface and the second surface of the first wearable device and the second wearable device define a cavity therebetween to provide airflow between the first surface and the second surface.

16. The wearable system of claim 15, wherein the one or more hardware processors are located on or within the first surface of the first and second wearable devices.

17. The wearable system of claim 16, wherein the cavity defined by the first surface and the second surface physically separates the first and second heat sources from the one or more hardware processors on or within the first surface.

18. The wearable system of claim 16, wherein the cavity defined by the first surface and the second surface has a sufficient volume to facilitate cooling of the first and second heat sources between heating cycles.

19. The wearable system of claim 1, wherein the abnormal biological event comprises a stroke event.

20. The wearable system of claim 1, wherein the one or more hardware processors are further configured to: Synchronize the signals received from the left and right limbs in time; and The synchronized signals from the left and right limbs are compared to determine whether an abnormal biological event has occurred.

21. The wearable system of claim 20, wherein the comparison takes into account a baseline difference between the left limb and the right limb.

22. The wearable system of claim 1, further comprising a tensionable strap connected to the first or second body.

23. The wearable system of claim 22, wherein the tensionable strap further comprises a visual indicator that indicates when one or more of the first or second heat source, the first or second skin temperature sensor, the first or second blood volume sensor, or a combination thereof, is sufficiently connected to the first or second skin surface to enable an accurate sensor reading.

24. The wearable system of claim 23, wherein one or more ends of the tensionable strap are connected to the first or second body at a location centered relative to one or more sensors located on the second surface.

25. The wearable system of claim 1, wherein the first heat source is positioned concentrically around one or both of the first blood volume sensor and the first skin temperature sensor; and the second heat source is positioned concentrically around one or both of the second blood volume sensor and the second skin temperature sensor.

26. The wearable system of claim 1, wherein the first blood volume sensor comprises a photoplethysmographic sensor or an impedance plethysmographic sensor.

27. The wearable system of claim 1, wherein the first skin temperature sensor comprises a thermocouple, a resistance temperature detector, a thermistor, or an infrared temperature sensor.

28. The wearable system of claim 15, further comprising a support structure connected to the first heat source and configured to connect the first heat source to the second surface and at least partially expose the first heat source to the cavity.

29. The wearable system of claim 1, wherein the first blood volume sensor is further configured to measure one or more of heart rate, heart rate variability, or oxygen saturation.

30. The wearable system of claim 1, wherein the first offset temperature or the second offset temperature is personalized to the person.

31. The wearable system of claim 30, wherein personalizing the first offset temperature or the second offset temperature comprises receiving a user input related to a perceived temperature of the first skin surface or the second skin surface.

32. The wearable system of claim 30, wherein personalization of the first offset temperature or the second offset temperature is based on a signal received from the first blood volume sensor or the second blood volume sensor.

33. The wearable system of claim 1, wherein the first or second heat source comprises one of a heating element or ambient temperature.

34. The wearable system of claim 1, wherein the one or more hardware processors are configured to transmit electronic information to a first electronic system in response to the determination of the abnormal biological event, the first electronic system being configured to electronically manage a home automation system.

35. The wearable system of claim 34, wherein the home automation system comprises a door lock, and wherein the electronic information is configured to instruct the first electronic system to unlock the door lock.

36. A wearable system according to any one of claims 34 to 35, wherein the home automation system comprises a home alarm system, and wherein the electronic information is configured to instruct the first electronic system to disable the home alarm system.

37. A wearable system according to any one of claims 34 to 35, wherein the home automation system includes a display, and wherein the electronic information is configured to instruct the first electronic system to display medical information of the user.

38. The wearable system of claim 37, wherein the medical information includes medication information and / or medication regimen compliance.

39. The wearable system of claim 34, wherein the home automation system includes a display, and wherein the electronic information is configured to instruct the first electronic system to display a stroke treatment user interface.

40. A wearable system according to any one of claims 34 to 35, wherein the home automation system comprises a speaker system, and wherein the electronic information is configured to instruct the first electronic system to trigger an audible alarm using the speaker system.

41. The wearable system of claim 1, wherein the hardware processor is further configured to issue an alert to a third party computing system in response to the determination of the abnormal biological event.

42. The wearable system of claim 41, wherein the third party computing system comprises an emergency services system.

43. The wearable system of claim 41, wherein the third party computing system comprises a clinician computing system.

44. The wearable system of claim 1, wherein the hardware processor is further configured to initiate a treatment regimen in response to detection of an abnormal biological event.

45. The wearable system of claim 44, further comprising a wearable processing system, and the processing scheme is configured to activate the wearable processing system.

46. ​​The wearable system of claim 45, wherein the wearable processing system comprises an ultrasound helmet.

47. The wearable system of claim 45, wherein the wearable processing system comprises a cooling gas delivery system.

48. The wearable system of claim 45, wherein the wearable processing system comprises a cooling helmet.

49. A wearable system for detecting abnormal biological events in a person, comprising: A first device configured to track the left side of the person, having a first body, the first body having a first surface opposite to a second surface, the second surface contacting a first skin surface of the person, the first surface and the second surface defining a cavity therebetween to provide airflow between the first surface and the second surface, the first device comprising: a first heating element in thermal communication with the first skin surface, wherein the first heating element comprises a first surface area, is positioned on the second surface and is configured to heat the first skin surface for a predetermined period of time; a first skin temperature sensor positioned on the second surface and configured to measure a first temperature of a first skin surface in contact with the first heating element, wherein the first skin temperature sensor is positioned in a first opening surrounded by the first surface area; and a second device configured to track the right side of the person, the second device having a second body, the second body having a first surface opposite to a second surface, the second surface in contact with a second skin surface of the person, the second device comprising: a second heating element in thermal communication with the second skin surface, wherein the second heating element comprises a second surface area, is positioned on the second surface and is configured to heat the second skin surface for a predetermined period of time; a second skin temperature sensor positioned on the second surface and configured to measure a second temperature of a second skin surface in contact with the second heating element, wherein the second skin temperature sensor is positioned in a second opening surrounded by the second surface area; one or more hardware processors communicatively connected to the first and second devices and configured to: receiving a first baseline temperature signal from the first skin temperature sensor, receiving a second baseline temperature signal from the second skin temperature sensor, outputting a first thermal stimulation signal to the first heating element to start a first cycle and a first time period at a first time, receiving a first temperature response of the first skin surface in response to the first thermal stimulation signal, wherein the first temperature response is measured by the first skin temperature sensor; outputting a second thermal stimulation signal to the second heating element to start a second cycle second time period at a second time, wherein the first time is synchronized with the second time, receiving a second temperature response of the second skin surface in response to the second thermal stimulation signal, wherein the second temperature response is measured by the second skin temperature sensor, comparing the first temperature response to the second temperature response to determine whether a difference between the first temperature response and the second temperature response indicates a temperature asymmetry between the left and right sides of the person, and An alarm is generated based on the determined indication of temperature asymmetry to indicate an abnormal biological event.

50. A wearable system for detecting abnormal biological events in a person, comprising: A first device positioned on the left limb of the person, comprising a first body, the first body having a first surface opposite to a second surface, the second surface being in contact with a first skin surface of the person, the first device comprising: a first heat source in communication with the first skin surface, wherein the first heat source is configured to heat the first skin surface to a first target temperature; a first skin temperature sensor positioned on the second surface and configured to measure a temperature of the first skin surface in contact with the first heat source; and a first sensor positioned on the second surface and configured to measure a parameter of interest of the person; a second device positioned on the right limb of the person, comprising a second body having a first surface opposite to a second surface, the second surface being in contact with a second skin surface of the person, the second device comprising: a second heat source in communication with a second skin surface, wherein the second heat source is configured to heat the second skin surface to a second target temperature; a second skin temperature sensor positioned on the second surface and configured to measure a temperature of the second skin surface in contact with the second heat source; and a second sensor positioned on the second surface and configured to measure a parameter of interest of the person; and a hardware processor communicatively connected to the heat source, the sensor, the skin temperature sensor, and an ambient temperature sensor, the ambient temperature sensor configured to measure a temperature of an environment surrounding the wearable system, wherein the hardware processor is configured to: receiving a first baseline sensor signal from the first sensor, Receive a second baseline sensor signal from the second sensor outputting a first heating signal to the first heat source to initiate a heating cycle, wherein the heating cycle includes heating the first skin surface to the first target temperature, receiving a first post-stimulation sensor signal from the first sensor in response to the first skin surface reaching the first target temperature, outputting a second heating signal to the second heat source to initiate a second heating cycle, wherein the second heating cycle includes heating the second skin surface to the second target temperature, receiving a second post-stimulation sensor signal from the second sensor in response to the second skin surface reaching the second target temperature, Calculate the left difference between the first post-stimulus sensor signal and the first baseline sensor signal, Calculate the right-hand difference between the second post-stimulation sensor signal and the second baseline sensor signal, comparing the left difference to the right difference, and A determination is made based on the comparison whether an abnormal biological event has occurred.

51. The wearable system of claim 50, wherein the sensor is selected from a stretch sensor, a skin electrode activity sensor, an electrocardiogram sensor, a camera, or a blood volume sensor.

52. The wearable system of claim 50, wherein the parameters of interest include one or more of: blood pressure, heart rate, heart rate variability, gaze, facial expression, skin conductance response, vasodilation response, or dilation response.

53. A wearable system for detecting abnormal biological events in a person, comprising: A first device configured to track the left side of the person and located on the left limb of the person, comprising a first body having a first surface opposite to a second surface, the second surface being in contact with a first skin surface of the person, the first device comprising: a first thermal stimulation source in thermal communication with the first skin surface, wherein the first thermal stimulation source comprises a first surface area extending over a first body surface of the first device, wherein the first thermal stimulation source is configured to apply stimulation to the first skin surface; a first blood volume sensor positioned on the second surface and configured to measure blood volume at the first skin surface; a second device located on a right limb of the person and configured to track the right side of the person, comprising a second body having a first surface opposite to a second surface, the second surface being in contact with a second skin surface of the person, the second device comprising: a second thermal stimulation source in thermal communication with the second skin surface, wherein the second thermal stimulation source comprises a second surface area extending over the first body surface of the second device, wherein the second thermal stimulation source is configured to apply stimulation to the second skin surface; a second blood volume sensor positioned on the second surface and configured to measure blood volume at the second skin surface; as well as a hardware processor communicatively connected to the first and second stimulation sources and the first and second blood volume sensors, wherein the hardware processor is configured to: receiving a first baseline blood volume signal from the first blood volume sensor, receiving a second baseline blood volume signal from the second blood volume sensor, outputting a first stimulation signal to the first stimulation source to start a first stimulation cycle, In response to the initiation of the first stimulation cycle, receiving a first post-stimulation blood volume signal from the first blood volume sensor, outputting a second stimulation signal to the second stimulation source to start a second stimulation cycle, In response to the initiation of the second stimulation cycle, receiving a second post-stimulation blood volume signal from the second blood volume sensor, Calculate the left difference between the first post-stimulation blood volume signal and the first baseline blood volume signal, Calculate the right-side difference between the second post-stimulation blood volume signal and the second baseline blood volume signal, comparing the left difference to the right difference, and A determination is made based on the comparison whether an abnormal biological event has occurred.

54. The wearable system of claim 53, wherein the stimulus source comprises a heat source.

55. The wearable system of claim 53, wherein the stimulation source comprises a power source.

56. The wearable system of claim 53, wherein the comparing comprises determining a change in a vasodilatory response.

57. The wearable system of claim 53, wherein the stimulation source comprises a Peltier cooler.

58. A wearable system according to claim 53, wherein the second post-stimulation blood volume signal comprises a set of blood volume signals such that the blood volume at the skin surface is repeatedly measured before, during and after the stimulation cycle.

59. A wearable system according to claim 53, wherein the second post-stimulation blood volume signal includes multiple blood volume signals so that the blood volume at the skin surface is continuously measured before, during and after the stimulation cycle.

60. The wearable system of claim 53, wherein the hardware processor is further configured to receive a second post-stimulation blood volume signal after target stimulation is achieved, after a predetermined period of time has expired, or after one or more stimulation cycles have ended.

61. A wearable system according to claim 53, wherein comparing comprises calculating a baseline ratio of alternating current to direct current of the baseline blood volume signal and a second ratio of alternating current to direct current of the second post-stimulation blood volume signal, and comparing the baseline ratio to the second ratio.

62. The wearable system of claim 53, wherein the blood volume sensor is positioned on a first side of a first or second body of the wearable system.

63. The wearable system of claim 53, further comprising a remote computing device communicatively coupled to the wearable system.

64. The wearable system of claim 63, wherein the remote computing device comprises one of: a laptop computer, a cellular device, a workstation, a server, a desktop computer, a personal digital assistant, a second wearable system, or a netbook.

65. The wearable system of claim 53, wherein the stimulation source is positioned on the second surface of the first or second body.

66. The wearable system of claim 65, wherein the hardware processor is further configured to: receiving a baseline blood volume signal from the blood volume sensor, determining a target blood volume based on the baseline blood volume signal, and It is determined whether the target blood volume is lower than the maximum blood volume value.

67. The wearable system of claim 66, wherein the hardware processor is further configured to cycle the stimulation source to maintain the target blood volume.

68. The wearable system of claim 53, further comprising one or more electrodermal activity sensors positioned on the second surface.

69. The wearable system of claim 68, wherein the one or more electrodermal activity sensors are spaced apart from the stimulation source by about 0.25 inches to about 4 inches.

70. The wearable system of claim 53, further comprising one or more motion sensors configured to measure motion of a body part connected to the wearable system.

71. A wearable system according to claim 53, wherein the first surface and the second surface of the first or second body define a cavity therebetween to provide airflow between the first surface and the second surface.

72. The wearable system of claim 71 , wherein the hardware processor is located on or within the first surface.

73. The wearable system of claim 72, wherein the cavity defined by the first and second surfaces physically separates the stimulation source from the hardware processor on or within the first surface.

74. The wearable system of claim 72, wherein the cavity defined by the first and second surfaces has a sufficient volume to facilitate cooling of the stimulation source between stimulation cycles.

75. The wearable system of claim 53, wherein the abnormal biological event comprises a stroke event.

76. The wearable system of claim 53, wherein the second thermal stimulus source is concentrically positioned around one or both of the second blood volume sensor and the second skin temperature sensor.

77. The wearable system of claim 53, wherein the hardware processor is further configured to: Synchronize the signals received from the left and right limbs in time; and The synchronized signals from the left and right limbs are compared to determine whether an abnormal biological event has occurred.

78. A wearable system according to claim 77, wherein the comparison takes into account a baseline difference between the left limb and the right limb.

79. The wearable system of claim 53, further comprising a tensionable strap connected to the first or second body.

80. The wearable system of claim 79, wherein the tensionable band further comprises a visual indicator that indicates when one or more of the stimulation source, the blood volume sensor, or a combination thereof, is sufficiently connected to the skin surface to enable an accurate sensor reading.

81. A wearable system according to claim 80, wherein one or more ends of the tensionable strap are connected to the first or second body at a position centered relative to one or more sensors located on the second surface.

82. The wearable system of claim 53, wherein the first thermal stimulus source is concentrically positioned around one or both of the first blood volume sensor and the first skin temperature sensor.

83. The wearable system of claim 53, wherein the blood volume sensor comprises a photoplethysmographic sensor or an impedance plethysmographic sensor.

84. The wearable system of claim 71, further comprising a support structure connected to the stimulation source and configured to connect the stimulation source to the second surface and at least partially expose the stimulation source to the cavity.

85. The wearable system of claim 53, wherein the blood volume sensor is further configured to measure one or more of heart rate, heart rate variability, or oxygen saturation.

86. The wearable system of claim 53, wherein the first and second stimulation cycles are personalized to the person.

87. The wearable system of claim 86, wherein personalization of the stimulation cycle comprises receiving user input related to perceived stimulation of the skin surface.

88. The wearable system of claim 86, wherein individualization of the stimulation cycle is based on a signal received from the blood volume sensor.

89. The wearable system of claim 53, wherein the stimulus source comprises one of a heating element or ambient temperature.

90. The wearable system of claim 54, wherein the hardware processor is configured to transmit electronic information to a first electronic system in response to the determination of the abnormal biological event, the first electronic system being configured to electronically manage a home automation system.

91. A wearable system according to claim 90, wherein the home automation system includes a door lock, and wherein the electronic information is configured to instruct the first electronic system to unlock the door lock.

92. A wearable system according to any one of claims 90 to 91, wherein the home automation system includes a home alarm system, and wherein the electronic information is configured to instruct the first electronic system to disable the home alarm system.

93. A wearable system according to any one of claims 90 to 91, wherein the home automation system includes a display, and wherein the electronic information is configured to instruct the first electronic system to display medical information of the user.

94. A wearable system according to claim 93, wherein the medical information includes medication information and / or medication regimen compliance.

95. The wearable system of claim 90, wherein the home automation system comprises a display, and wherein the electronic information is configured to instruct the first electronic system to display a stroke treatment user interface.

96. A wearable system according to any one of claims 90 to 91, wherein the home automation system includes a speaker system, and wherein the electronic information is configured to instruct the first electronic system to trigger an audible alarm using the speaker system.

97. The wearable system of claim 53, wherein the hardware processor is further configured to issue an alert to a third party computing system in response to the determination of the abnormal biological event.

98. The wearable system of claim 97, wherein the third party computing system comprises an emergency services system.

99. The wearable system of claim 97, wherein the third party computing system comprises a clinician computing system.

100. The wearable system of claim 53, wherein the hardware processor is further configured to initiate a treatment regimen in response to detection of an abnormal biological event.

101. The wearable system of claim 100, further comprising a wearable processing system, and the processing scheme is configured to activate the wearable processing system.

102. The wearable system of claim 101, wherein the wearable processing system comprises an ultrasound helmet.

103. The wearable system of claim 101, wherein the wearable processing system comprises a cooling gas delivery system.

104. The wearable system of claim 101, wherein the wearable processing system comprises a cooling helmet.

105. A wearable system for detecting a stroke event in a person, the wearable system comprising: A first wearable device, configured to contact a first skin surface of a person, the first wearable device configured to be fixed to a left limb of the person, the first wearable device comprising: a first heat source in communication with the first skin surface, wherein the first heat source is configured to heat the first skin surface to a first offset temperature, wherein the first offset temperature is a baseline skin temperature of the first skin surface plus about 1 degree to about 20 degrees; a first skin temperature sensor configured to measure a first temperature of the first skin surface; and a first blood volume sensor configured to measure a first blood volume at a first tissue site proximate to the first skin surface; a second wearable device configured to contact a second skin surface of the person, the second wearable device configured to be fixed to a right limb of the person, the second wearable device comprising: a second heat source in communication with the second skin surface, wherein the second heat source is configured to heat the second skin surface to a second offset temperature, wherein the second offset temperature is a baseline skin temperature of the second skin surface plus about 1 degree to about 20 degrees; a second skin temperature sensor configured to measure a second temperature of the second skin surface; and a second blood volume sensor configured to measure a second blood volume at a second tissue site proximate to the second skin surface; and One or more hardware processors communicatively coupled to the first and second wearable devices and configured to: receiving a first baseline blood volume signal from the first blood volume sensor; receiving a second baseline blood volume signal from the second blood volume sensor; outputting a first heating signal to the first heat source to initiate a first heating cycle at a first time, wherein the first heating cycle includes heating the first skin surface to the first offset temperature; receiving a first post-stimulation blood volume signal from the first blood volume sensor in response to the first skin surface reaching the first offset temperature; outputting a second heating signal to the second heat source to initiate a second heating cycle at a second time, wherein the second heating cycle includes heating the second skin surface to the second offset temperature, wherein the first time is synchronized with the second time; receiving a second post-stimulation blood volume signal from the second blood volume sensor in response to the second skin surface reaching the second offset temperature; Calculate the left difference between the first post-stimulation blood volume signal and the first baseline blood volume signal, Calculate the right-side difference between the second post-stimulation blood volume signal and the second baseline blood volume signal, comparing the left difference to the right difference; and A stroke event is determined based on the comparison.

106. A wearable system according to claim 105, wherein the second post-stimulation blood volume signal comprises a set of blood volume signals such that the second blood volume of the second skin surface is repeatedly measured before, during and after a heating cycle of the second heat source.

107. A wearable system according to claim 105, wherein the second post-stimulation blood volume signal includes multiple blood volume signals so that the second blood volume of the second skin surface is continuously measured before, during and after the heating cycle of the second heat source.

108. A wearable system according to claim 105, wherein the one or more hardware processors are further configured to calculate a first baseline ratio of alternating current to direct current of the first baseline blood volume signal and a second baseline ratio of alternating current to direct current of the second blood volume signal, and compare the first baseline ratio to the second baseline ratio.

109. The wearable system of claim 105, wherein the first wearable device further comprises an ambient temperature sensor.

110. The wearable system of claim 105, further comprising a remote computing device communicatively coupled to the first wearable device and the second wearable device.

111. The wearable system of claim 110, wherein the remote computing device comprises one of: a laptop computer, a cellular device, a workstation, a server, a desktop computer, a personal digital assistant, a second wearable system, or a netbook.

112. The wearable system of claim 105, further comprising one or more electrodermal activity sensors.

113. A wearable system according to claim 112, wherein the one or more skin electrodermal activity sensors are separated from at least one of the first heat source or the second heat source by about 0.25 inches to about 4 inches.

114. The wearable system of claim 105, further comprising one or more motion sensors configured to measure movement of a body part connected to at least one of the first wearable device or the second wearable device.

115. The wearable system of claim 105, further comprising at least one tensionable strap connected to the first or second body.

116. The wearable system of claim 105, wherein the first heat source is concentrically positioned around one or both of the first blood volume sensor and the first skin temperature sensor.

117. The wearable system of claim 105, wherein the second heat source is positioned concentrically around one or both of the second blood volume sensor and the second skin temperature sensor.

118. The wearable system of claim 105, wherein the first blood volume sensor comprises a photoplethysmographic sensor or an impedance plethysmographic sensor.

119. The wearable system of claim 105, wherein the second blood volume sensor comprises a photoplethysmographic sensor or an impedance plethysmographic sensor.

120. The wearable system of claim 105, wherein the first skin temperature sensor comprises a thermocouple, a resistance temperature detector, a thermistor, or an infrared temperature sensor.

121. The wearable system of claim 105, wherein the second skin temperature sensor comprises a thermocouple, a resistance temperature detector, a thermistor, or an infrared temperature sensor.

122. The wearable system of claim 105, wherein the first blood volume sensor is further configured to measure one or more of heart rate, heart rate variability, or oxygen saturation.

123. The wearable system of claim 105, wherein the second blood volume sensor is further configured to measure one or more of heart rate, heart rate variability, or oxygen saturation.

124. The wearable system of claim 105, wherein at least one of the first offset temperature and the second offset temperature is personalized to the person.

125. The wearable system of claim 105, wherein the determination of the stroke event is further based on stored reference data corresponding to healthy individuals.

126. A wearable system for detecting a stroke event in a person, the wearable system comprising: A first wearable device, configured to contact a first skin surface of a person, the first wearable device configured to be fixed to a left limb of the person, the first wearable device comprising: a first stimulus source in communication with the first skin surface, wherein the first stimulus source is configured to apply a first stimulus to the first skin surface; and a first sensor configured to measure a baseline measurement at a first tissue site proximate to the first skin surface; a second wearable device configured to contact a second skin surface of the person, the second wearable device configured to be fixed to a right limb of the person, the second wearable device comprising: a second stimulation source in communication with the second skin surface, wherein the second stimulation source is configured to apply a second stimulation to the second skin surface; and a second sensor configured to measure a second baseline measurement at a second tissue site proximate to the second skin surface; and One or more hardware processors communicatively connected to the first and second wearable devices and configured to: Outputting a first stimulation signal to the first stimulation source to start applying the first stimulation; receiving a first post-stimulus response from the first sensor after applying the first stimulus; outputting a second stimulation signal to the second stimulation source to start applying the second stimulation; receiving a second post-stimulus response from a second sensor after applying the second stimulus; Calculate the left-sided difference between the first post-stimulus response and the first baseline measurement, Calculate the right-sided difference between the second post-stimulus response and the second baseline measurement, and A stroke event is determined based on a comparison of the left side difference and the right side difference.

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