The invention provides a device for stimulating peripheral nerves, comprising a memory, at least one electrode attached to the patient's body for generating pulses, and a control unit connected with an electrode for setting at least one electrode pulse parameter. The device further includes a detector of response to neuromodulation connected with a control unit for transmitting information on a frequency of movement of at least a part of the body to the control unit, and a controller connected with the control unit for acquiring a user input. The control unit of the device further sets flow of current of electrode pulses automatically, depending on information on a frequency value of movement of a part of the body. The invention further provides a method for treating the syndromes of an overactive bladder using a neuromodulation device. And method of collecting information of such devices.

A method includes obtaining monitoring data recorded by first and second devices, the first and second devices being attached to the subject at different first and second sties, respectively. The monitoring data comprises signals associated with at least one physiological parameter of the subject. The method also includes extracting one or more features of the signals recorded by the first and second devices during a transitionary period when the first and second devices simultaneously monitor the at least one physiological parameter of the subject. The method further includes generating at least one correlation parameter by analyzing the extracted features of the signals recorded by the first and second devices for at least a portion of the transitionary period, the at least one correlation parameter when applied to signals recorded by the second device at least partially compensating for relative changes in signals recorded by the first and second devices.

A method includes obtaining monitoring data recorded by first and second devices, the first and second devices being attached to the subject at different first and second sties, respectively. The monitoring data comprises signals associated with at least one physiological parameter of the subject. The method also includes extracting one or more features of the signals recorded by the first and second devices during a transitionary period when the first and second devices simultaneously monitor the at least one physiological parameter of the subject. The method further includes generating at least one correlation parameter by analyzing the extracted features of the signals recorded by the first and second devices for at least a portion of the transitionary period, the at least one correlation parameter when applied to signals recorded by the second device at least partially compensating for relative changes in signals recorded by the first and second devices.

A bioelectrical signal controlled exercise machine system for allowing an exerciser to control the state of an exercise machine and exercise environment. The bioelectrical signal controlled exercise machine system generally includes an exercise machine, a bioelectrical sensor device and a control unit in communication with the bioelectrical sensor device and the exercise machine. The control unit is adapted to receive data from the bioelectrical sensor device relating to measured bioelectrical signals of the human exerciser, and wherein the control unit transmits a control signal to the exercise machine to change the state of the exercise machine based on the data from the bioelectrical sensor device.

A bioelectrical signal controlled exercise machine system for allowing an exerciser to control the state of an exercise machine and exercise environment. The bioelectrical signal controlled exercise machine system generally includes an exercise machine, a bioelectrical sensor device and a control unit in communication with the bioelectrical sensor device and the exercise machine. The control unit is adapted to receive data from the bioelectrical sensor device relating to measured bioelectrical signals of the human exerciser, and wherein the control unit transmits a control signal to the exercise machine to change the state of the exercise machine based on the data from the bioelectrical sensor device.

The present disclosure relates to a neuromodulation and/or neurostimulation system comprising at least the following components: at least one sensing unit, at least control unit, at least one stimulation unit, at least one Central Nervous System (CNS) stimulation module, at least one Peripheral Nervous System (PNS) stimulation module, wherein at least one of the components of the neuromodulation and/or neurostimulation system is implantable.

The present disclosure relates to a neuromodulation and/or neurostimulation system comprising at least the following components: at least one sensing unit, at least control unit, at least one stimulation unit, at least one Central Nervous System (CNS) stimulation module, at least one Peripheral Nervous System (PNS) stimulation module, wherein at least one of the components of the neuromodulation and/or neurostimulation system is implantable.

An electronic device is disclosed. The electronic device identifies a user on the basis of: a biological signal input unit for receiving the input of a user's biological signal detected through an electrode; a voice input unit for receiving the input of a voice signal; a biological signal inputted through the biological signal input unit; and a voice signal inputted through a microphone.

An electronic device is disclosed. The electronic device identifies a user on the basis of: a biological signal input unit for receiving the input of a user's biological signal detected through an electrode; a voice input unit for receiving the input of a voice signal; a biological signal inputted through the biological signal input unit; and a voice signal inputted through a microphone.

This disclosure provides a motion speed analysis method and apparatus, and wearable device, and relates to the technical field of intelligent wearable devices. A motion speed analysis method, including: acquiring surface myoelectric signals of a detected user; determining signals of action segment according to the surface myoelectric signals; determining a change rate of potentials of the signals of action segment and determining a motion speed level according to the change rate and a preset change rate threshold.