An information processing apparatus includes: a preparation device configured to prepare information on a posture of a body; a myoelectric potential meter configured to measure a myoelectric potential from a surface of the body; and a processor configured to acquire the information on the posture prepared by the preparation device, acquire information on the myoelectric potential measured by the myoelectric potential meter, specify a movement of the body based on the acquired information on the posture, estimate a muscle activity state required for a muscle to implement the specified movement, and output information indicating a difference between (i) a muscle activity state determined based on the myoelectric potential and (ii) the estimated muscle activity state.

An information processing apparatus includes: a preparation device configured to prepare information on a posture of a body; a myoelectric potential meter configured to measure a myoelectric potential from a surface of the body; and a processor configured to acquire the information on the posture prepared by the preparation device, acquire information on the myoelectric potential measured by the myoelectric potential meter, specify a movement of the body based on the acquired information on the posture, estimate a muscle activity state required for a muscle to implement the specified movement, and output information indicating a difference between (i) a muscle activity state determined based on the myoelectric potential and (ii) the estimated muscle activity state.

This disclosure is directed to devices and techniques for classifying of pacing captures to evaluate effectiveness of pacing by a pacing device, such as an implantable medical device (IMD). An example system includes stimulation circuitry to generate a pacing stimulus, sensing circuitry to sense an evoked response after the pacing stimulus, and processing circuitry. The processing circuitry determines classification features from the evoked response and applies the classification features to a classification model, the classification model generated by a machine learning algorithm using one or more test sets comprising a plurality of sample evoked responses for each of a plurality of classifications. Based on the output of the model, the processing circuitry classifies the evoke response as one of the plurality of classifications.

A functional electrical stimulation (FES) device includes electrodes arranged to apply functional electrical stimulation to a body part of the user. FES stimulation is performed by: receiving values of a set of user metrics for the user; receiving a target position of the body part represented as values for a set of body part position measurements; determining a user-specific energization pattern for producing the target position based on the received target position and the received values of the set of user metrics for the user; and energizing the electrodes of the FES device in accordance with the determined user-specific energization pattern. The determination may utilize an FES calibration database with records having fields containing: values of the set of user metrics for reference users; energization patterns; and values of the set of body part position metrics for positions assumed by the body part in response to applying the energization patterns.

A method of providing vagus nerve stimulation (VNS) to a user is provided. The method includes the steps of: (1) collecting, by one or more sensors monitoring a user, one or more sets of physiological data; (2) determining, by a controller, an occurrence of a physiological event based on the one or more sets of physiological data; (3) stimulating, by a first earpiece worn by a user, a vagus nerve of the user with a VNS signal generated based on the controller determining the occurrence of the physiological event, wherein the VNS signal has an amplitude. The physiological condition may be an anxiety attack. The physiological condition may be a migraine headache.

A flexible sheet for neurostimulation is described having a flexible non-conductive substrate matrix in which electrodes are embedded along a lower surface. Electrically conductive wires extend from the electrodes through the flexible substrate to another exterior surface of the substrate. Methods of making the flexible sheet and making a device using the flexible sheet are also disclosed.

A device is disclosed that can detect and treat disordered breathing in a patient. The device can include at least one contact adapted to make contact with a portion of an oral cavity of a patient, and a control circuit configured to: in a first mode, detect a presence of disordered breathing in the patient based, at least in part, on a first signal received from the at least one contact; and in a second mode, provide electrical stimulation via the at least one contact to a portion of the patient's upper airway based on a detection of the presence of disordered breathing.

Methods and devices for improving pelvic floor dysfunction in a patient suffering therefrom by electrically modulating neural tissue in a minimally invasive fashion using an electrical micro stimulator are provided.

Surface electromyography signals of a nervous system are obtained; a separation matrix is generated based on electromyography signals obtained over a first time period using a training module; one or more motor neuron action potentials for single motor neurones are detected based on said electromyography signals and said separation matrix, wherein said electromyography signals are provided over a second time period shorter than said first time period; and an output is generated in the form of a time-series indicative of motor neuron activity.

Surface electromyography signals of a nervous system are obtained; a separation matrix is generated based on electromyography signals obtained over a first time period using a training module; one or more motor neuron action potentials for single motor neurones are detected based on said electromyography signals and said separation matrix, wherein said electromyography signals are provided over a second time period shorter than said first time period; and an output is generated in the form of a time-series indicative of motor neuron activity.