A system for hepatic nerve denervation includes a medical device and a generator in communication with the medical device. The medical device includes an elongate body having a proximal portion and a distal portion opposite the proximal portion, and a plurality of treatment electrodes coupled to the distal portion. The distal portion is configured to be in contact with an area of target tissue. The area of target tissue is an area of tissue within the hepatic artery. The generator is configured to generate and deliver at least one pulse train of energy to the plurality of treatment electrodes to ablate the area of target tissue.

A cadence measurement device includes a myoelectric potential sensor attachable to a leg portion of a living body, a waveform processor that performs waveform processing to obtain a myoelectric potential waveform from an output signal from the myoelectric potential sensor, and a cadence deriving unit that derives cadence according to the myoelectric potential waveform obtained by the waveform processing.

A system for determining a treatment regimen for chronic pelvic pain (CPP) includes an electromyography (EMG) probe including electrodes. Each electrode detects pelvic floor muscle activity. An EMG sensor array includes bipolar EMG sensors configured to detect muscle activity of muscles associated with or supporting the pelvic floor muscles. An EMG amplifier is in communication with the EMG probe or the EMG sensor array. The EMG amplifier includes a plurality of input channels. Each input channel receives data of muscle activity in the pelvic floor muscles or the muscles associated with or supporting the pelvic floor muscles from the EMG probe or the EMG sensor array. A processor of a computer performs muscle network analysis using the data of muscle activity in the pelvic floor muscles or the muscles associated with or supporting the pelvic floor muscles. A treatment regimen for CPP is recommended based on the muscle network analysis.

A system for determining a treatment regimen for chronic pelvic pain (CPP) includes an electromyography (EMG) probe including electrodes. Each electrode detects pelvic floor muscle activity. An EMG sensor array includes bipolar EMG sensors configured to detect muscle activity of muscles associated with or supporting the pelvic floor muscles. An EMG amplifier is in communication with the EMG probe or the EMG sensor array. The EMG amplifier includes a plurality of input channels. Each input channel receives data of muscle activity in the pelvic floor muscles or the muscles associated with or supporting the pelvic floor muscles from the EMG probe or the EMG sensor array. A processor of a computer performs muscle network analysis using the data of muscle activity in the pelvic floor muscles or the muscles associated with or supporting the pelvic floor muscles. A treatment regimen for CPP is recommended based on the muscle network analysis.

Systems and methods for the treatment of gastroesophageal reflux disease (GERD) include at least one electrically stimulating electrode coupled to a pulse generator. Individuals with GERD are treated by implanting a stimulation device within and/or proximate the patient's lower esophageal sphincter, gastric fundus, or other nearby gastrointestinal structures and applying electrical stimulation to the patient's lower esophageal sphincter and/or fundus, in accordance with certain predefined protocols. Electrical stimulation provided by the disclosed systems results in an increase in the length of the high pressure zone of the LES and/or modulation of the receptive relaxation response of the fundus to decrease gastric pressure, creating a longer barrier to the reflux of gastric contents or increasing functional lower esophageal pressure respectively, thereby treating GERD.

Systems and methods for providing algorithmic equipment and/or accessory recommendations are disclosed herein. In one embodiment, a method providing an equipment or accessory recommendation to an athlete includes: monitoring a first amplitude of a first muscle of the athlete by a first wearable muscle response sensor carried by the athlete; monitoring a second amplitude of a second muscle of the athlete by a second wearable muscle response sensor carried by the athlete; determining a difference between the first amplitude and the second amplitude; comparing the difference to a predetermined amplitude threshold; and based on the comparing, providing an equipment or accessory recommendation to the athlete.

Systems and methods for providing algorithmic equipment and/or accessory recommendations are disclosed herein. In one embodiment, a method providing an equipment or accessory recommendation to an athlete includes: monitoring a first amplitude of a first muscle of the athlete by a first wearable muscle response sensor carried by the athlete; monitoring a second amplitude of a second muscle of the athlete by a second wearable muscle response sensor carried by the athlete; determining a difference between the first amplitude and the second amplitude; comparing the difference to a predetermined amplitude threshold; and based on the comparing, providing an equipment or accessory recommendation to the athlete.

The method can include a muscle deforming a fiber path and activating a joint of the mammal, circulating electricity along the fiber, along the length of the fiber path, generating a movement signal including monitoring a change of impedance of the fiber stemming from the deformation of the muscle path during said deformation of the fiber path, determining a coefficient of correlation value of successive portions of the movement signal associated to corresponding, successive, time windows, including ascertaining a degree of similitude between the corresponding portion and a corresponding movement template, and generating an indication of muscle fatigue based on said coefficient of correlation values.

The method can include a muscle deforming a fiber path and activating a joint of the mammal, circulating electricity along the fiber, along the length of the fiber path, generating a movement signal including monitoring a change of impedance of the fiber stemming from the deformation of the muscle path during said deformation of the fiber path, determining a coefficient of correlation value of successive portions of the movement signal associated to corresponding, successive, time windows, including ascertaining a degree of similitude between the corresponding portion and a corresponding movement template, and generating an indication of muscle fatigue based on said coefficient of correlation values.

A motion monitoring method (500) is provided, which includes: obtaining a movement signal of a user during motion, wherein the movement signal includes at least an electromyographic signal or an attitude signal (510); and monitoring a movement of the user during motion based at least on feature information corresponding to the electromyographic signal or the feature information corresponding to the attitude signal (520).