This information processing device is provided with: a receiving unit which receives a detected value detected by means of a head-mounted device which is worn on the head of a user and detects the blood flow rate in the head; a calculating unit which extracts a first signal by passing the detected value through a first filter which extracts a signal in a first frequency band, extracts a second signal by passing the detected value through a second filter which extracts a signal in a second frequency band, which is a frequency band that is higher than the first frequency band, and extracts a third signal, which is the envelope of the second signal, from the second signal; and an output unit which outputs the first signal and the third signal in association with one another.

The invention relates to an active implantable medical device comprising a processing unit able to be alternately operated during a predetermined period of activity and on standby during a standby period in a cyclical manner, and means for acquiring data relating to physiological and/or physical activity. The device also comprises means for calculating a frequency analysis of the data acquired, said calculating means being capable of successively perform part of the frequency analysis during periods of activity of the processing unit.

A monitoring system may include a processor and display system for displaying results from the monitoring. A user may be in a sterile field away from the processor and display system and selected input devices. A controller may be physically connected to the monitoring system from the sterile field to allow the user to control the monitoring system.

A system for integrating a plurality of biosensor devices includes one or more communication interfaces adapted to communicate with each of the plurality of biosensor devices connected to a subject, and a processor executing software on a non-transitory memory to: establish a communication link with each of the plurality of biosensor devices, receive biodata from each of the plurality of biosensor devices through the one or more communication interfaces at a sampling rate, assign a timestamp to the received biodata such that the received data from the plurality of biosensor devices are synchronized, receive environmental data via one or more environmental sensors, store received biodata along with the assigned timestamp into a database and the environmental data, analyze stored data along with the assigned timestamp to predict an evoked response to one or more stimuli and the environmental data and provide a feedback based on the analysis.

A method of therapeutically treating a subject includes the steps of: sensing sympathetic nerve activity; communicating the sensed sympathetic nerve activity to a processor; using machine learning in the processor to identify input data sets correlated to a physiological end point in the subject by processing the input data input sets to experientially optimize an algorithmically defined physiological goal defined in output data sets by the machine learning; and dynamically controlling a therapeutic device in real time with the processor using the output data sets to treat the subject mediated by the therapeutic device by establishing or tending to establish the physiological end point in the subject.

An electrocardiac signal analysis device measures an electrocardiac signal of a subject in a daily environment such as an office. The electrocardiac signal is analyzed by a plurality of methods, contributing to accurate evaluation of a health condition of the subject. A measurement unit includes a pair of detection electrodes of a capacitive coupling type that detect a heart rate of a subject in a non-contact state and output the heart rate as primary signals. A pair of active guard circuits reduce noise in the primary signals and output secondary signals. A potential difference of the secondary signals is amplified and output as an electrocardiac signal. A feedback electrode is configured to remove an influence of an in-phase signal of the secondary signals. An analysis unit linearly analyzes the electrocardiac signal to calculate an autonomic nerve index, and nonlinearly analyzes the electrocardiac signal to calculate a Lyapunov exponent.

A cardiovascular health assessment score, representing a working tissue flow and indicating the dependence on central and peripheral control mechanisms, is generated by an evaluation system and used to support a variety of individualized medicine and health applications. One or more of the individualized medicine and health applications may be implemented as part of the evaluation system and incorporate the cardiovascular health assessment.

Systems and methods for performing, assessing, and adjusting neuromodulation therapy are disclosed herein. One method for assessing the likely efficacy of neuromodulation therapy includes positioning a neuromodulation catheter at a target site within a renal blood vessel of a human patient and obtaining a measurement related to a diameter of the renal blood vessel via the neuromodulation catheter. The method can further include determining a diameter of the renal blood vessel at or near the target site based on the measurement. In some embodiments, (i) one or more parameters of neuromodulation energy to be delivered to the renal blood vessel can be adjusted based on the determined diameter and/or (ii) the neuromodulation catheter may be repositioned within the renal blood vessel.

In a method and a device for quantification of a respiratory sinus arrhythmia, a heart-rate curve is measured first and then the time elapsed between two heartbeats is determined and quantified by an analysis in the phase domain. A more informative quantification is obtained when suitable coefficients are used or the heart-rate curve is interpolated and/or detrended for the quantification.

A method of monitoring and/or diagnosing an autoregulation mechanism of blood pressure of a living being using an ECG signal includes recording the ECG signal of the living being, and the recording a pulse wave curve synchronously with the recording of the ECG signal. Heart rate intervals are determined from the ECG signal. A pulse wave transit time is determined for each heart rate interval from the pulse wave curve. A plurality of significant changes in the pulse wave transit times are determined according to a specified criterion. One respective heart rate interval correlated in time with each significant change in the pulse wave transit times is selected as an anchor point. A determined limited number of temporally successive heart rate intervals temporally before and/or after each anchor point are selected to thus generate a limited sequence of heart rate intervals for each anchor point. The method further includes averaging the corresponding heart rate intervals of each sequence of a respective anchor point over all sequences of the anchor points.