A self-inflating personal flotation device (SIPFD) configured to be worn by a wearer and aid the wearer automatically. The SIPFD may communicate with a global communication network and pressurized gas cartridge assembly based on a triggering event. The SIPFD may have a wearable data transmitter of a heartbeat device; a water depth device; and a geolocation device. The SIPFD may have a neck inflation device and a torso inflation device both connected to the pressurized gas cartridge assembly to enable the pressurized gas cartridge to inflate the neck and torso inflation devices when prompted. The prompt may be automatic or on request and be performed using an actuator mechanically communicating with the pressurized gas cartridge assembly to: (i) inflate the neck and torso inflation devices; and (ii) deflate the neck and torso inflation devices associated with a wearer.

A heartrate monitor detects heartbeats in a test signal. A local heartrate and an energy of acceleration are associated with the detected heartbeats. Detected heartbeats are included or excluded from a test set of heartbeats based on the local heartrate and energy of acceleration associated with the respective heartbeats. Anomalous heartbeats in the test set of heartbeats are detected using a sparse approximation model. The heartrate monitor may detect heartbeats in a training heartbeat signal. A reference heart rate and an energy of acceleration are associated with detected beats of the training heartbeat signal and selectively included in a set of training data based on the heart rate and energy of acceleration associated with the detected beat in the training heartbeat signal. A dictionary of the sparse representation model may be generated using the set of training data.

A computer-implemented method for processing ECG data may include: receiving, over an electronic network, ECG data, wherein the ECG data represents a plurality of heartbeats; analyzing the ECG data, by at least one processor, to determine whether each of the plurality of heartbeats is a normal heartbeat or an abnormal heartbeat; associating, by the at least one processor, each of the abnormal heartbeats with either only one of a plurality of existing templates or a new template; receiving, from a user, input related to each new template, wherein the input includes either: a) a confirmation that the new template represents an abnormal heartbeat, or b) a reclassification of the new template as representing a normal heartbeat or a different abnormal heartbeat; and in response to the user input, updating, by the at least one processor, a label of each of the heartbeats associated with each confirmed new template and each of the heartbeats associated with each reclassified new template. The ECG data may be received from a portable monitor configured to be carried on a patient's body.

A self-inflating personal flotation device (SIPFD) configured to be worn by a wearer and aid the wearer automatically. The SIPFD may communicate with a global communication network and pressurized gas cartridge assembly based on a triggering event. The SIPFD may have a wearable data transmitter of a heartbeat device; a water depth device; and a geolocation device. The SIPFD may have a neck inflation device and a torso inflation device both connected to the pressurized gas cartridge assembly to enable the pressurized gas cartridge to inflate the neck and torso inflation devices when prompted. The prompt may be automatic or on request and be performed using an actuator mechanically communicating with the pressurized gas cartridge assembly to: (i) inflate the neck and torso inflation devices; and (ii) deflate the neck and torso inflation devices associated with a wearer.

A system for acquiring an electrical signal comprises: a plurality of electrodes, a plurality of signal quality detectors, each detector, being configured to detect a signal from a pair of electrodes and each detector comprising an analog-to-digital converter for providing a digital representation of a first resolution of the detected signal; a signal selection logic for determining at least one quality measure of each of the digital representations for selecting a pair of electrodes for signal acquisition; a multiplexer for selecting a pair of electrodes for signal acquisition based on a control signal from the signal selection logic; and a signal processing unit for performing analog-to-digital conversion on the selected signal and providing a digital representation having a second resolution, which is higher than the first resolution.

A wearable cardioverter defibrillator (WCD) comprises a plurality of electrocardiography (ECG) electrodes and a plurality of defibrillator electrodes to contact the patient's skin when the WCD is delivering therapy to the patient, a preamplifier coupled to the ECG electrodes to obtain ECG data from the patient. a processor to receive the ECG data from the preamplifier, and a high voltage subsystem to provide a defibrillation voltage to the patient through the plurality of defibrillator electrodes in response to a shock signal received from the processor. In a first power mode of a range of power modes the preamplifier is configured to perform low-fidelity ECG acquisition and the processor is configured to perform simple arrythmia detection analysis, and in a second mode of the range of power modes the preamplifier is configured to perform high-fidelity ECG acquisition and the processor is configured to perform complex arrythmia detection analysis.

An example method includes analyzing morphology and/or amplitude of each of a plurality of electrophysiological signals across a surface of a patient's body to identify candidate segments of each signal satisfying predetermined conduction pattern criteria. The method also includes determining a conduction timing parameter for each candidate segment in each of the electrophysiological signals.

Disclosed are a method and a system for comprehensive evaluation of organic compound and heavy metal pollution in water based on fish electro-cardio, and fish electro-cardio signals are acquired by a real-time and miniaturized fish electro-cardio acquisition system which includes a real-time and miniaturized fish electro-cardio acquisition device, then a change of the electro-cardio index in a QT interval is obtained for assessing the corresponding organic compound in water to be tested, and a change of the electro-cardio index in a QRS interval is obtained for assessing the corresponding heavy metal in water to be tested. Based on fish electro-cardio acquired continuously on-line in real-time while keeping fish swims in a normal state and the water quality parameters acquired by various water quality sensors, water quality is online analyzed and water sudden pollution is online monitored and assessed.

The disclosure relates to a method for determining a plurality of action potentials in the heart having the following steps:

a) Recording a surface ECG signal synchronously with at least 64 channels,

b) Recording at least one IEGM signal,

c) Processing the surface ECG signal by means of ICA analysis and determining the sum and position of a plurality of action potentials in the heart based on the ICA analysis, and,

d) Comparing the at least one IEGM signal to the plurality of action potentials and correcting the sum and/or position of at least one of the plurality of action potentials in the heart based on this comparison.

The disclosure further relates to a corresponding device, a corresponding computer program product, and a corresponding system.

Systems to identify and risk stratify disease states, cardiac structural defects, functional cardiac deficiencies induced by teratogens and other toxic agents, pathological substrates, conduction delays and defects, and ejection fraction using single channel biological data obtained from the subject. A modified Matching Pursuit (MP) algorithm may be used to find a noiseless model of the data that is sparse and does not assume periodicity of the signal. After the model is derived, various metrics and subspaces are extracted to characterize the cardiac system. In another system, space-time domain is divided into a number of regions (which is largely determined by the signal length), the density of the signal is computed in each region and input to a learning algorithm to associate them to the desired cardiac dysfunction indicator target.