A method for configuring a myoelectrically controlled prosthetic system with a prosthesis socket and several lead electrodes for recording electric muscle activities, featuring the steps: placement of a surface electrode arrangement comprising several surface electrodes around the circumference of a residual limb, recording of electric muscle activity in muscles of the residual limb as electromyograhic signals, the activity being recorded by the surface electrodes, evaluation of the myoelectric signals with regards to the distinctness of the signals, selection of the control procedure that is to be used to control the prosthesis system, based on the evaluation of the distinctness of the signals, and fixing of the lead electrodes to the prosthesis socket.

Methods and systems implement a pain assessment regularizing system to autonomously observe pained expressions and physiological measurements of a patient, in order to systematically collect data inputs which may be converted to pain assessment factors. The pain assessment regularizing system, by collecting this data, may combine it with clinical appraisals of pain intensity and patient self-reporting of pain intensity, weighing each factor appropriately in a manner sensitive to the progression of a patient care program, so as to lessen confounding effects of subjective pain assessment. The pain assessment regularizing system may generate a time series of regularized pain assessment factors, and further forecast a regularized pain assessment trend. A clinician may further operate the pain assessment regularizing system to review a visualization of both the time series and the forecast, providing the clinician with rigorously sampled and analytically predicted data which cannot be derived through manual and mental efforts.

Disclosed are a multiple physiological data collection device and system that collect, manually mark, sampling—physiological data for machine learning and AI analyses in a single operation background. Physiological data uploaded by sensing devices of different type and function, described in different formation, recorded at different times and/or pertaining to different person can be processed in one system. The invented system comprises a data uploading device, a data storage device and a data edition device and, optionally, an automated data analysis device.

Disclosed are a multiple physiological data collection device and system that collect, manually mark, sampling—physiological data for machine learning and AI analyses in a single operation background. Physiological data uploaded by sensing devices of different type and function, described in different formation, recorded at different times and/or pertaining to different person can be processed in one system. The invented system comprises a data uploading device, a data storage device and a data edition device and, optionally, an automated data analysis device.

The present invention relates to a movement disorder monitor with high sensitivity, and a method of measuring the severity of a subject's movement disorder. The present invention additionally relates to a drug delivery system for dosing a subject in response to the increased severity of a subject's symptoms. The present invention provides for a system and method, which can accurately and repeatably quantify symptoms of movements disorders, accurately quantifies symptoms utilizing both kinetic information and/or electromyography (EMG) data, that can be worn continuously to provide continuous information to be analyzed as needed by the clinician, that can provide analysis in real-time, that allows for home monitoring of symptoms in subject's with these movement disorders to capture the complex fluctuation patterns of the disease over the course of days, weeks or months, that maximizes subject safety, and that provides substantially real-time remote access to data by the clinician or physician.

The present invention relates to a movement disorder monitor with high sensitivity, and a method of measuring the severity of a subject's movement disorder. The present invention additionally relates to a drug delivery system for dosing a subject in response to the increased severity of a subject's symptoms. The present invention provides for a system and method, which can accurately and repeatably quantify symptoms of movements disorders, accurately quantifies symptoms utilizing both kinetic information and/or electromyography (EMG) data, that can be worn continuously to provide continuous information to be analyzed as needed by the clinician, that can provide analysis in real-time, that allows for home monitoring of symptoms in subject's with these movement disorders to capture the complex fluctuation patterns of the disease over the course of days, weeks or months, that maximizes subject safety, and that provides substantially real-time remote access to data by the clinician or physician.

According to a first aspect of the present invention, there is provided a method for objectively determining a frailty score for a subject, the method comprising: deriving an attribute from sensor data including at least one of EMG data and motion data of the subject and obtained from at least one limb of the subject; quantitatively processing the attribute to determine how the subject is responding to the rehabilitation or exercises program; and objectively determining the frailty score based on the quantitative processing.

A method for determining a lowest stimulation threshold current level in a group of channels of a neuromonitoring device. The method includes stimulating tissue at a current level from a predetermined range of current levels as a sequence of pulses delivered at a frequency. The stimulating includes increasing the current level of each pulse in the sequence of pulses from an immediately preceding pulse by a first current increment. The method includes determining that a first evocation pulse from the sequence of pulses evokes a first muscular response. The method includes stimulating the tissue with a second evocation pulse from the sequence of pulses to evoke a second muscular response. The stimulating includes decreasing the frequency of the delivery of each pulse in the sequence of pulses and increasing the current level of each pulse in the sequence of pulses from the immediately preceding pulse by a second current increment. The method includes determining that the second evocation pulse from the sequence of pulses evokes the second muscular response.

A method for determining a lowest stimulation threshold current level in a group of channels of a neuromonitoring device. The method includes stimulating tissue at a current level from a predetermined range of current levels as a sequence of pulses delivered at a frequency. The stimulating includes increasing the current level of each pulse in the sequence of pulses from an immediately preceding pulse by a first current increment. The method includes determining that a first evocation pulse from the sequence of pulses evokes a first muscular response. The method includes stimulating the tissue with a second evocation pulse from the sequence of pulses to evoke a second muscular response. The stimulating includes decreasing the frequency of the delivery of each pulse in the sequence of pulses and increasing the current level of each pulse in the sequence of pulses from the immediately preceding pulse by a second current increment. The method includes determining that the second evocation pulse from the sequence of pulses evokes the second muscular response.

Aspects of the present disclosure provide methods, apparatuses, and systems for closed-loop sleep protection and/or sleep regulation. According to an aspect, sleep disturbing noises are predicted and a biosignal parameter is measured to dynamically mask predicted disturbing environmental noises in the sleeping environment with active attenuation. Environmental noises in a sleeping environment of a subject are detected, input, or predicted based on historical data of the sleeping environment collected over a period of time. The biosignal parameter is used to determine sleep physiology of a subject. Based on the environmental noises in the sleeping environment and the determined sleep physiology, the noises are predicted to be disturbing or non-disturbing noises. For predicted disturbing noises, one or more actions are taken to regulate sleep and avoid sleep disruption by using sound masking prior to or concurrently with the occurrence of the predicted disturbing noises.