Abstract: An apparatus for performing an activity based on a sympathetic nervous system (SNS) response to a stimulus includes an electrode configured to contact a person undergoing the stimulus. The apparatus also includes a processing unit having an algorithm programmed by machine-learning and configured to: (i) receive at least one of electrocardiogram (ECG) signals or electrodermal activity (EDA) signals from the electrode; (ii) analyze at least one of skin sympathetic nerve activity (SKNA) signals derived from the ECG signals or the EDA signals to measure the SNS response and provide an SNS response measurement; and (iii) transmit an SNS response measurement signal conveying the SNS response measurement to initiate the activity. The apparatus also includes an activity device configured to perform the activity in response to the SNS response measurement signal.

Abstract: An apparatus for treating a person having cardiac arrest includes a processor and a lead in communication with the processor, the lead being configured to receive a segment of electrocardiogram (ECG) data from the person while undergoing cardiopulmonary resuscitation (CPR).

Abstract: The invention provides, in some aspects, an automated external defibrillator (AED) that includes defibrillation circuitry capable of delivering a therapeutic shock to a patient. The AED also includes an input that receives a patient ECG signal representing real-time electrical activity of a heart of the patient and that may include artifacts resulting from cardiopulmonary resuscitation of the patient. The AED generates a real-time alert from a patient data image that is based on the patient ECG signal to effect application of the therapeutic shock to the patient. The AED generates that alert based at least in part on a shock recommendation of an artificial intelligence (AI) engine that analyzes the patient data image using a machine learning (ML) model trained with training data images. The patient data image comprises pixels whose values are a function of magnitudes of components of representations of respective time-slices of the patient ECG signal in a frequency domain.

Abstract: Methods, systems, non-transitory computer-readable media, and apparatuses are described for predicting a health condition of a subject. An apparatus may be configured to receive a physiological signal associated with the subject. The physiological signal may include artifacts. A modified physiological signal may be generated based on an application of a machine learning model to the physiological signal. The modified physiological signal may include the physiological signal with a reduction of the artifacts. A physiological measurement may be determined based on the modified physiological signal. The health condition may be determined based on a change in the physiological measurement satisfying a threshold. The apparatus may cause an output of an indication associated with the health condition.

Abstract: Disclosed herein are conductive polymer electrodes and wiring elements for use as the conductive element in health monitoring applications, and more specifically to conductive polymer fabric electrodes or conductive polymer fabric wiring elements for use as the conductive element in pads for health monitoring applications and other wearable monitoring systems.

Abstract: Methods, systems, and apparatuses for determining an indication of pain of a user are disclosed. Electrodermal activity (EDA) data from a sensor may be received. The EDA data may be indicative of one or more physiological signals derived from sweat gland activity of the user. Index values may be determined based on the EDA data. The index values may be compared to a threshold to determine if one or more of the values of the index value satisfies the threshold. Satisfying the threshold may indicate a pain in the user, a pain level for the user and/or a source of pain within the user. The indication may be caused to be output so that the user or others may be informed of an objective measurement of the pain in the user.

Abstract: The invention provides, in some aspects, an automated external defibrillator (AED) that includes defibrillation circuitry capable of delivering a therapeutic shock to a patient. The AED also includes an input that receives a patient ECG signal representing real-time electrical activity of a heart of the patient and that may include artifacts resulting from cardiopulmonary resuscitation of the patient. The AED generates a real-time alert from a patient data image that is based on the patient ECG signal to effect application of the therapeutic shock to the patient. The AED generates that alert based at least in part on a shock recommendation of an artificial intelligence (AI) engine that analyzes the patient data image using a machine learning (ML) model trained with training data images. The patient data image comprises pixels whose values are a function of magnitudes of components of representations of respective time-slices of the patient ECG signal in a frequency domain.

Abstract: Disclosed herein are conductive polymer electrodes and wiring elements for use as the conductive element in health monitoring applications, and more specifically to conductive polymer fabric electrodes or conductive polymer fabric wiring elements for use as the conductive element in pads for health monitoring applications and other wearable monitoring systems.

Abstract: An epidermal electrode operable independently of the ambient environment, such as the presence of water, sweat, or dry conditions, and achieve a suitable impedance with the epidermal surface for transmitting electrical signals indicative of bodily physiological process such as ECG signals for heart monitoring. The hydrophobic surface mountable electrode including a flexible, conductive substrate of PDMS (Polydimethylsiloxane) with dispersed carbon black and having a substantially planar sensing area adapted for communication with an electrically sensitive surface such as a patient's skin, and an embedded conductor encapsulated in the substrate for connection to a monitor circuit, the terminal having electrical continuity with the planar sensing area.

Abstract: Disclosed is a method for Atrial Fibrillation detection that includes monitoring consecutive patient heartbeats, analyzing heart beat intervals from the monitored heartbeats, performing a calculation of the randomness the heart beat intervals, performing a calculation of the variability of consecutive heart beat intervals of the heart beat intervals, and performing a calculation of the complexity of the heart beat intervals.

Abstract: An epidermal electrode operable independently of the ambient environment, such as the presence of water, sweat, or dry conditions, and achieve a suitable impedance with the epidermal surface for transmitting electrical signals indicative of bodily physiological process such as ECG signals for heart monitoring. The hydrophobic surface mountable electrode including a flexible, conductive substrate of PDMS (Polydimethylsiloxane) with dispersed carbon black and having a substantially planar sensing area adapted for communication with an electrically sensitive surface such as a patient's skin, and a terminal for connection to a monitor circuit, the terminal having electrical continuity with the planar sensing area.

Abstract: Disclosed is an apparatus and method for ambulatory, real-time detection of Atrial Fibrillation (AF) providing an overall accuracy that refers to detection of AF, irrespective of the duration of AF and beat-to-beat classification.

Abstract: Disclosed is an apparatus and method for ambulatory, real-time detection of Atrial Fibrillation (AF) providing an overall accuracy that refers to detection of AF, irrespective of the duration of AF and beat-to-beat classification.