FIELD: medicine.
SUBSTANCE: method of controlling electronic devices is carried out using an electromyographic reading device. EMG signal of the user is recorded using an electromyographic reading device. Obtained signal primary processing is performed by non-overlapping EMG signal segmentation. For each EMG signal segment obtained, a set of sign features is formed based on EMG signal dispersion square for classification of gestures. Set of features of EMG-signal of each segment is transmitted along the data transmission channel to the network of the neural network and to the computing part of the device. Based on the obtained set of characteristics, a neuron network hash function in the form of an artificial neural network generates a secondary feature data space which is transmitted to the metric classifier and describes the gesture. Intention of user in part of gesture is determined. Type of gesture is determined based on the generated set of features of the EMG signal by using a neuronetwork hash function and a metric classifier. Control signal is generated based on a certain type of gesture. Generated control signal and additional information are transmitted from gyroscope and accelerometer of electromyographic reading device via data transmission channel to actuator. Actuator action is initiated based on the obtained control signal and additional information from the sensors. Receiving feedback from actuator. Vibration motor is started at electromyographic reading device. Actuator may look in the form of a helmet or glasses with a controller on a virtual reality device, a radio-controlled model, a controlled mobile phone, a computer.
EFFECT: higher accuracy of positioning and decision on hand grip of object, as well as registration of more accurate foot motion, limb position in space or determination of other motor function.
20 cl, 15 dwg
Title | Year | Author | Number |
---|---|---|---|
METHOD AND SYSTEM OF INTELLECTUAL BIONIC LIMB CONTROL | 2016 |
|
RU2635632C1 |
METHOD FOR DECIPHERING ELECTROMYOSIGNALS AND APPARATUS FOR IMPLEMENTATION THEREOF | 2020 |
|
RU2762775C1 |
METHOD FOR FORMING A PHANTOM HAND MAP IN PATIENTS WITH UPPER LIMB AMPUTATION BASED ON NEUROPLASTICITY ACTIVATION | 2021 |
|
RU2766044C1 |
METHOD OF REHABILITATION OF PATIENTS IN DIFFERENT STAGES OF CENTRAL OR PERIPHERAL NERVOUS SYSTEM DISORDERS USING VIRTUAL REALITY | 2016 |
|
RU2655200C1 |
METHOD AND COMPLEX FOR BIONIC CONTROL OF TECHNICAL APPARATUSES | 2020 |
|
RU2756162C1 |
METHOD OF BIONIC CONTROL OF TECHNICAL DEVICES | 2017 |
|
RU2673151C1 |
SYSTEM AND METHOD FOR CAPTURING MOVEMENTS AND POSITIONS OF HUMAN BODY AND PARTS OF HUMAN BODY | 2017 |
|
RU2662399C1 |
MIXED REALITY HUMAN-ROBOT INTERACTION SYSTEM | 2022 |
|
RU2813444C1 |
SYSTEM FOR PROVISION OF SAFETY FOR PORTABLE WEAPONS | 2019 |
|
RU2790188C1 |
PORTABLE ELECTRONIC DEVICE | 2013 |
|
RU2614575C2 |
Authors
Dates
2019-04-02—Published
2017-12-27—Filed