An exercise feedback system determines muscle fatigue measurements using physiological data generated by a sensor-equipped athletic garment. The muscle fatigue measurement is determined by analyzing the frequency spread of the physiological data. The exercise feedback system may customize exercise programs, determine risks of injury, or generate biofeedback for presentation on graphical user interfaces using the muscle fatigue measurements. The exercise feedback system accesses pre-determined muscle fatigue measurement models that define criteria for the aforementioned features. For instance, if an athlete is becoming fatigued and exercising with improper form based on a muscle fatigue measurement, the exercise feedback system modifies the athlete's exercise program to help target and improve the athlete's weaknesses as well as to prevent injury.

Methods, systems, and devices for signal analysis in an implanted cardiac monitoring and treatment device such as an implantable cardioverter defibrillator. In some examples, captured data including detected events is analyzed to identify likely overdetection of cardiac events. In some illustrative examples, when overdetection is identified, data may be modified to correct for overdetection, to reduce the impact of overdetection, or to ignore overdetected data. Several examples emphasize the use of morphology analysis using correlation to static templates and/or inter-event correlation analysis.

Embodiments of the present systems and methods may provide a non-invasive system to measure and integrate behavioral and cognitive features enabling early detection and progression tracking of degenerative disease. For example, a method of detecting neurodegenerative disease may comprise measuring functioning of at least one of the motor system, cognitive function, and brain activity of a subject during everyday life and analyzing the gathered at least one motor system data, cognitive function data, and brain activity data of the subject.

A functional optical coherent imaging (fOCI) platform includes at least one active camera unit (ACU) having a coherent and/or a partially coherent light source, and means for spectral filtering and imaging a selected body area of interest; an image processing unit (IPU) for pre-processing data received from an ACU; at least one stimulation unit (STU) transmitting a stimulation to a subject; at least one body function reference measurement unit (BFMU); a central clock and processing unit (CCU), with interconnections to the ACU, the IPU, the STU, for collecting pre-processed data from the IPU, stimuli from the STU body function reference data from the BFMU in a synchronized manner; a post-processing unit (statistical analysis unit, SAU); and an operator interface (HOD. A process for acquiring stimuli activated subject data includes aligning a body function unit at a subject and monitoring pre-selected body function; selecting a stimulus or stimuli; imaging a body area of interest; exerting one or a series of stimuli on the subject; imaging the body area of interest synchronous with said stimuli and the preselected body functions; and transferring said synchronized image, stimuli and body function data to a statistical analysis unit (SAU) and performing calculations to generate results pertaining to body functions.

A method and device for reducing the computational complexity of a processing algorithm, of a discrete signal, in particular of the spectral estimation and analysis of bio-signals, with minimum or no quality loss, which comprises steps of (a) choosing a domain, such that transforming the signal to the chosen domain results to an approximately sparse representation, wherein at least part of the output data vector has zero or low magnitude elements; (b) converting the original signal in the domain chosen in step (a) through a mathematical transform consisting of arithmetic operations resulting in a vector of output data; (c) reformulating the processing algorithm of the original signal in the original domain into a modified algorithm consisting of equivalent arithmetic operations in the domain chosen in step (a) to yield the expected result with the expected quality quantified in terms of a suitable application metric; (d) combining the mathematical transform of step (b) and the equivalent mathematical operations introduced in step (c) for obtaining the expected result within the original domain with the expected quality; (e) selecting a threshold value based on the difference in the mean magnitude value of the elements of the output data vector of the transform said in step (b) and the preferred complexity reduction and degree of output quality loss that can be tolerated in the expected result within the target application; (f) pruning a number of elements the magnitude of which is less than the threshold value selected in step (e); and/or eliminating arithmetic operations associated with the pruned elements of step (f) either in the mathematical transform of step (b) and/or in the equivalent algorithm of step (c).

A realtime evaluation method and system for a virtual reality (VR) immersion effect are provided. An electroencephalogram signal is collected while a VR video is played, a degree of emotional arousal and a degree of cognitive absorption are calculated in real time based on energy of frequency bands α, β, and θ that is obtained after wavelet transform, and finally, an immersion effect index is dynamically monitored for objective evaluation on an immersion effect. The method and the system realize realtime measurement and analysis, dynamically monitors a VR video immersion effect, adopts a multi-dimensional comprehensive calculation strategy and takes individual differences into account when calculating an index, effectively resolves problems such as after-fact reporting, social desirability biases, and strong subjectivity in questionnaire measurement and other measurement means, and has a broad market application prospect.

The invention provides an IV system for monitoring a patient that is positioned on the patient's body. The IV system includes: 1) a catheter that inserts into the patient's venous system; 2) a pressure sensor connected to the catheter that measures physiological signals indicating a pressure in the patient's venous system; 3) a motion sensor that measures motion signals; and 4) a processing system that: i) receives the physiological signals from the pressure sensor; ii) receives the motion signals from the motion sensor; iii) processes the motion signals by comparing them to a pre-determined threshold value to determine when the patient has a relatively low degree of motion; and iv) process the physiological signals to determine a physiological parameter when the processing system determines that the motion signals are below the pre-determined threshold value.

The present disclosure provides a system and method for analyzing a physiological parameter of a vital sign signal. The method may include acquiring a vital sign signal, storing data, computing and analyzing, processing, and outputting a result. The system may compute and analyze the physiological parameter of the vital sign signal, especially a blood oxygen saturation, via a plurality of algorithms, judge or process the computation result, and output the judgment result.

A biological data obtaining device includes a storage unit, a first generation unit, and a second generation unit. The storage unit is configured to store time-series data in which first to N.sup.th distance-based fluctuation data are arranged. The first to N.sup.th distance-based fluctuation data are obtained based on reflected waves which are reflected from a living body at different times, wherein n.sup.th distance-based fluctuation data indicates changes in signal strength with respect to distance. The first generation unit is configured to generate time-based fluctuation data by performing strength obtaining process. The strength obtaining process includes obtaining one corresponding strength information, wherein the one corresponding strength information is a signal strength based on reflected waves from a predetermined detection part of the living body. The second generation unit is configured to generate biological data of the detection part of the living body based on the time-based fluctuation data.

A method and a system for analyzing electrocardiographic segments previously derived from a cardiac device so as to help to discriminate true positives episodes, including abnormal heart rhythms, from false positives episodes, including normal heart rhythms. Each episode received includes at least one segment of electrocardiographic signal, and each segment is segmented into sub-segments. Score vectors are obtained for each sub-segment to classify the episode so as to discriminate true positive episodes from false positive episodes, and the classification results, which include at least the true positive episodes, are output.