There is provided a method for the treatment of a patient suffering or recovering from a critical illness using a device comprising a generator configured to produce an electrical stimulation signal and a controller. The controller is connected to the generator and configured to determine the form of the electrical stimulation signal. The method includes producing an electrical stimulation signal from the generator, and determining the form of the electrical stimulation signal using the controller connected to the generator; and transmitting the electrical stimulation signal to an electrode in contact with a tragus of the patient.

This document presents a system for managing treatment for an emergency cardiac event. The system includes memory, one or more electronic ports for receiving ECG signals, and a treatment module executable on one or more processing devices. The module is configured to generate transform values for a time segment of ECG, obtain one or more previous values derived from one or more earlier time segments of the ECG, and determine, based on the generated transform values, and the one or more previous values, at least one of: a) a future therapeutic action for treating the emergency cardiac event, or b) a phase of the cardiac event. The module is further configured to cause one or more output devices to present an indication of at least one of the therapeutic action or the phase of the cardiac event.

This document presents a system for managing treatment for an emergency cardiac event. The system includes memory, one or more electronic ports for receiving ECG signals, and a treatment module executable on one or more processing devices. The module is configured to generate transform values for a time segment of ECG, obtain one or more previous values derived from one or more earlier time segments of the ECG, and determine, based on the generated transform values, and the one or more previous values, at least one of: a) a future therapeutic action for treating the emergency cardiac event, or b) a phase of the cardiac event. The module is further configured to cause one or more output devices to present an indication of at least one of the therapeutic action or the phase of the cardiac event.

The present invention provides a method, a device, an electronic apparatus, and a storage medium for processing multi-modal physiological signals, which relates to the field of health engineering. The method comprises: acquiring continuous target multi-modal physiological signals, the target multi-modal physiological signals comprise at least three target physiological signals of a target temperature signal, a target impedance plethysmogram (IPG) signal, a target electrocardiogram (ECG) signal, a target photoplethysmogram (PPG) signal and a target ultrasound signal; determining a continuous physiological information of a target subject, especially a continuous blood pressure information, according to the continuous target multi-modal physiological signals. The present invention determines the continuous physiological information by acquiring the continuous multi-modal physiological signals, so that the physiological information acquired is more accurate, and is more beneficial to the timely detection of abnormal physiological information, so that patients can be treated in time.

The present invention provides a method, a device, an electronic apparatus, and a storage medium for processing multi-modal physiological signals, which relates to the field of health engineering. The method comprises: acquiring continuous target multi-modal physiological signals, the target multi-modal physiological signals comprise at least three target physiological signals of a target temperature signal, a target impedance plethysmogram (IPG) signal, a target electrocardiogram (ECG) signal, a target photoplethysmogram (PPG) signal and a target ultrasound signal; determining a continuous physiological information of a target subject, especially a continuous blood pressure information, according to the continuous target multi-modal physiological signals. The present invention determines the continuous physiological information by acquiring the continuous multi-modal physiological signals, so that the physiological information acquired is more accurate, and is more beneficial to the timely detection of abnormal physiological information, so that patients can be treated in time.

Disclosed includes a body surface device for diagnosing locations associated with electrical rhythm disorders to guide therapy. The device can sense electrical signals and determine multiple sites that may be operative in that patient. The patch may encompass the heart regions from where the heart rhythm disorder originates. The patch comprises an array of electrodes configured to detect electrical signals generated by a heart. A controller may determine the locations of interest based on detected electrical signals. The controller is configured to locate these regions relative to the surface patch. The system may be coupled to a sensor or therapy device inside the heart, to guide this device to a region of interest. The controller is further configured to instruct the operator to use the trigger or source information to treat the heart rhythm disorder in an individual using additional clinical data and methods for personalization such as machine learning.

Disclosed includes a body surface device for diagnosing locations associated with electrical rhythm disorders to guide therapy. The device can sense electrical signals and determine multiple sites that may be operative in that patient. The patch may encompass the heart regions from where the heart rhythm disorder originates. The patch comprises an array of electrodes configured to detect electrical signals generated by a heart. A controller may determine the locations of interest based on detected electrical signals. The controller is configured to locate these regions relative to the surface patch. The system may be coupled to a sensor or therapy device inside the heart, to guide this device to a region of interest. The controller is further configured to instruct the operator to use the trigger or source information to treat the heart rhythm disorder in an individual using additional clinical data and methods for personalization such as machine learning.

Disclosed includes a body surface device for diagnosing locations associated with electrical rhythm disorders to guide therapy. The device can sense electrical signals and determine multiple sites that may be operative in that patient. The patch may encompass the heart regions from where the heart rhythm disorder originates. The patch comprises an array of electrodes configured to detect electrical signals generated by a heart. A controller may determine the locations of interest based on detected electrical signals. The controller is configured to locate these regions relative to the surface patch. The system may be coupled to a sensor or therapy device inside the heart, to guide this device to a region of interest. The controller is further configured to instruct the operator to use the trigger or source information to treat the heart rhythm disorder in an individual using additional clinical data and methods for personalization such as machine learning.

A method for evaluating heart function, comprising receiving a digitized cardiac signal, computing a power spectral density (PSD) or multiscale entropy (MSE) of the digitized cardiac signal, and evaluating heart function based on the PSD or MSE is provided. Systems and computer program products for doing same are also provided.

A method enables analysis of (e.g. bioelectric) signals acquired by measurement. The method provides N signals U for an observation space and each has a time- and space-dependent signal characteristic U. Digitized signals for a time period T have M time points and define an M×N matrix with M tuples of N signal values each. Signal values acquired at time t form an N-tuple Ū.sub.t=(U.sub.1, . . . , U.sub.N).sub.t in a signal space. The method acquires all combinations of k tuples from the M tuples, and calculates distances between all tuples. Distance values are calculated and define edge lengths of a (k−1) simplex (SIM) with one simplex assigned to each combination of k time points. Quantity characteristics of the simplex (SIM) are encoded into color values (COL), and displays the colors in a combinatorial time lattice (CTL). Each lattice point (GP) is displayed with the color encoded for the assigned simplex.