The present disclosure describes a system, method and software applications for predicting the KAM of a subject for a plurality of gait cycles of a subject. At least one sensor attachable adjacent to the ankle of at least one leg of the subject provides accelerometer and gyroscopic data for the plurality of gait cycles. A processing means receives subject parameters and accelerometer and gyroscopic data from the at least one sensor for evaluation by a neural network of predicted KAM values for the plurality of gait cycles of the subject. The neural network is configured via determining KAM values for each of the plurality of subjects from measurements during a plurality of gait cycles and other parameters.

An apparatus for energy expenditure estimation includes a heart rate sensor for producing a heart rate value indicative of a heart rate of an individual, a heat-flux sensor for producing a heat-flux value indicative of a heat-flux flowing through a measurement area on the skin of the individual, and a processing system communicatively connected to the heart rate sensor and the heat-flux sensor. The processing system is configured to produce an estimate of the energy expenditure based on the heart rate value and the heat-flux value. The use of the heat-flux value improves the accuracy of the estimation especially during low-intensity exercise and rest, when both heart rate and acceleration values often fail to provide information meaningful enough for energy expenditure estimation.

Disclosed is a natural movement electroencephalogram (EEG) recognition method based on source localization and a brain network, which includes the following steps: (1) performing multi-channel EEG measurement for natural movements; (2) preprocessing acquired EEG signals, and extracting the movement-related cortical potential (MRCP), and θ, α, β, and γ rhythms; (3) determining a lead field matrix of the signals, calculating initial solutions of sources by means of L1 regularization constraint, and then performing iteration by means of successive over-relaxation to obtain a source localization result; (4) by using the sources as nodes, calculating PLV between each pair of sources at each time point by means of short-time sliding window, and establishing brain networks; and (5) calculating a network adjacency matrix at each time point and five brain network indicators, introducing these features into a classifier for training and testing, and conducting a statistical test for the brain network indicators. The present disclosure makes improvements to the conventional source localization method by using the T-wMNE algorithm in combination with successive over-relaxation, and establishes brain networks by using the sources as nodes, thus improving the EEG decoding accuracy for natural movements and revealing the neural mechanism of the human body.

A cardiac health assessment system includes a memory, a circuit board, and a touchscreen controller integrated into a handheld electronic device (HED). The memory stores a classification model, a regression model, and instructions about a cardiac monitoring application. The circuit board includes a microphonic sensor, an Inertial Measurement Unit (IMU) sensor, a camera sensor, and a processor. The microphonic sensor captures cardiac sound wave signals indicative of the cardiac health of a user. The IMU sensor captures seismic signals indicative of the cardiac health of the user. The camera sensor enables visual data collection of tissue and photoplethysmography. The processor is configured to: execute the instructions, display commands to position the HED against the chest of the user, detect abnormal heart activity by deploying the classification model, and estimate intracardiac pressure by deploying the regression model. The touchscreen controller displays cardiac diagnostic information.

Methods systems and apparatus are set forth herein. There is provided in one embodiment determining one or more body physiological parameter of a patient based on one or more input; and controlling a heating system for warming the patient based on a result of the determining.

Described herein are methods and systems for extracting or determining subject motion from multi-channel electrical coupling in imaging of the subject, in particular in magnetic resonance (MR) imaging of the subject. The motion can be of a region of interest of the subject (such as an organ or specific tissue). Changes in the position of the subject and the subjects organs can be monitored by measuring how external coils, such as RF coils, couple to the subject and to one another and change the scattering of the RF coils, for example scattering of RF pulses transmitted by the coils. Changes in position influence this coupling and the scattering and can be detrimental to the quality of the imaging The present methods and systems address and overcome this problem.

An apparatus for estimating bio-information based on pulse wave signals of multiple wavelengths is disclosed. The bio-information estimating apparatus may include: a sensor part comprising a pulse wave sensor configured to measure a multi-wavelength pulse wave signal at a first point in time when a first pressure is applied from an object to the sensor part and at a second point in time when a second pressure is applied from the object to the sensor part; and a processor configured to estimate bio-information based on a difference between the multi-wavelength pulse wave signal measured at the first pressure and the multi-wavelength pulse wave signal measured at the second pressure.

An apparatus for non-invasively estimating bio-information is provided. According to one exemplary embodiment, the apparatus may include a bio-signal acquirer configured to acquire a bio-signal; and a processor configured to extract a plurality of characteristic points from the bio-signal, determine internally dividing points of the plurality of characteristic points, and extract feature values from the bio-signal based on the internally dividing points to perform bio-information estimation.

Systems and methods are provided for determining an acceleration at a location of interest within one of a user's head and neck. At least one of linear acceleration data, angular acceleration data, angular velocity data, and orientation data is produced using at least one sensing device substantially rigidly attached to an ambient-accessible surface of the user's head. The location of interest is represented relative to a position of the at least one sensing device as a time-varying function. An acceleration at the location of interest is calculated as a function of the data produced at the sensing device and the time-varying function representing the location of interest. The calculated acceleration at the location of interest is provided to at least one of the user and an observer in a human-perceptible form.

A method of compressing tissue during a surgical procedure is disclosed. The method comprises obtaining a surgical instrument comprising an end effector, wherein the end effector comprises a first jaw and a second jaw, establishing a communication pathway between the surgical instrument and a surgical hub, and inserting the surgical instrument into a surgical site. The method further comprises compressing tissue between the first jaw and the second jaw, determining a location of the compressed tissue with respect to at least one of the first jaw and the second jaw, communicating the determined location of the compressed tissue to the surgical hub, and displaying the determined location of the compressed tissue on a visual feedback device.