Systems and methods are described for detecting and characterizing seizures or seizure-related events. The methods herein may include determining magnitude and/or scaled magnitude data for each of at least one high and low frequency group of signals. Based on the determined magnitudes and/or scaled magnitude data, seizures or seizure-related events may be characterized.

A monitoring device for monitoring of vital signs of a living organism comprises at least two electrode pins for receiving an electrical activity of the living organism and an optical sensor for sensing a pulse of the living organism, wherein the monitoring device has a compact form and the at least two electrode pins and the optical sensor are integrated in the monitoring device.

An actigraphy method includes receiving a physiological parameter signal as a function of time for a physiological parameter other than body motion (such as electrocardiography or a respiration monitor), computing a body motion artifact (BMA) signal as a function of time from the physiological parameter signal (for example, using a local signal power signal, a local variance signal, a short-time Fourier transform, or a wavelet transform over epochs of duration on order a few minutes or less), and computing an actigraphy signal as a function of time from the BMA signal, for example by applying a linear transform to the BMA signal and optionally applying filtering such as median removal and/or high-pass filtering.

The invention relates to registering changes in vascular tone during and after a functional load, and processing data using spectral analysis methods within the frequency ranges of endothelial (0.0095-0.02 Hz), neurogenic (0.02-0.05 Hz), and myogenic (0.05-0.14 Hz) regulation mechanisms. Furthermore, the temperature of an area of a patient's skin is continuously registered. During the first 1-2 minutes, the temperature of the examined skin surface is increased to 38-42° C., and the heating power is fixed. Temperature fluctuations are registered over the course of 10 minutes The heater is shut-off. Over the course of 10 minutes following the shut-off and a decrease in temperature to 30-32° C., temperature fluctuations continue to be registered, and the obtained values are compared, with coefficients being calculated for the relative change in the amplitudes of the temperature fluctuations, which are then used for determining the existence of a disorder in a vascular tone regulation mechanism.

A platform is provided for generating 3D models of a tumor segmented from a series of 2D medical images and for identifying from these 3D models, radiomic features that may be used for diagnostic, prognostic, and treatment response assessment of the tumor. The radiomic features may be shape-based features, intensity-based features, textural features, and filter-based features. The radiomic features are compared to remove sufficiently redundant features, thereby producing a reduced set of radiomic features, which is then compared to separate genomic data and/or outcome data to identify clinically and biologically significant radiomic features for diagnostic, prognostic, and treatment response assessment, other applications.

Provided are a heart physiological parameter measurement method, device and terminal, and a computer storage medium. The method comprises: respectively obtaining back vibration information and shoulder vibration information of an object to be measured in a supine state by means of one or more shoulder vibration sensitive sensors and back vibration sensitive sensors; respectively generating first hemodynamic related information and second hemodynamic related information on the basis of the back vibration information and the shoulder vibration information, the second hemodynamic related information comprising right shoulder second hemodynamic related information generated from right shoulder vibration information; determining a reference AVC time point of an AVC event on the basis of the first hemodynamic related information; and determining an AVC feature point of the AVC event on the basis of the reference AVC time point and the right shoulder second hemodynamic related information.

Provided is a system for measuring biological signals of a user, which includes a sensor module configured to acquire ballistocardiogram (BCG) signals of a user via a present channel, where the present channel is at least one channel of the sensor module, a decomposition module configured to decompose the BCG signals to decomposed signals, a reconstruction module configured to reconstruct at least a portion of the decomposed signals to reconstructed signals, a processing module configured to process the reconstructed signals to at least one of a heart rate, respiration rate, phases of respiration, and blood pressure, and a display module configured to display at least one output corresponding to the at least one of the heart rate, the respiration rate, phases of respiration, and the blood pressure on a display device.

Embodiments described herein include sensors and sensor systems having probe-off detection features. For example, sensors and physiological monitors described herein include hardware and/or software capable of providing an indication of the integrity of the connection between the sensor and the patient. In various embodiments, the physiological monitor is configured to output an indication of a probe-off condition for an acoustic sensor (or other type of sensor). For example, in an embodiment, a signal from an acoustic sensor is compared with a signal from a second sensor to determine a probe-off condition.

A system for monitoring nutritional intake is described. The system includes a wearable housing configured for releasable attachment to a user; a biosensor supported by the wearable housing for disposition adjacent to a blood vessel; the biosensor configured to collect pulse profile data; an output device; and a processing circuit connected to the biosensor and the output device. The processing circuit is configured to: receive the pulse profile data from the biosensor; generate a nutritional intake value from the received pulse profile data; and control an output device to output the nutritional intake value.

The present invention discloses a depression assessment system based on physiological information, comprising an information acquisition module, a signal processing module, a parameters calculation module, a feature selection module, a machine learning module and an output result module. The present invention further discloses a depression assessment method based on various physiological information, comprising the following steps: 1, processing electrocardiogram (ECG) signal and one or more of photoplethysmography (PPG) signal, electroencephalogram (EEG) signal, galvanic skin response (GSR)signal, electrogastrography (EGG) signal, electromyogram (EMG) signal, electrooculogram (EOG) signal, polysomnogram (PSG) signal and temperature signal, and calculating signal parameters; 2, normalizing the obtained signal parameters, and performing the feature selection on parameters set formed by the normalized signal parameters to obtain feature parameters set; and 3, performing machine learning by utilizing the obtained feature parameters set, and establishing a depression assessment mathematic model to assess the depression level by utilizing a relationship between the feature parameters set and the depression level. The present invention has the advantage that the subjectivity of the assessment by utilizing the depression rating scale can be avoided.