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A Way of Bionic Control Based on EI, EMG, and FMG Signals

Andrey Briko, Vladislava Kapravchuk, Alexander Kobelev, Ahmad Hammoud, Steffen Leonhardt, Chuong Ngo, Yury Gulyaev, С. И. Щукин

2021Sensors26 citationsDOIOpen Access PDF

Abstract

Creating highly functional prosthetic, orthotic, and rehabilitation devices is a socially relevant scientific and engineering task. Currently, certain constraints hamper the development of such devices. The primary constraint is the lack of an intuitive and reliable control interface working between the organism and the actuator. The critical point in developing these devices and systems is determining the type and parameters of movements based on control signals recorded on an extremity. In the study, we investigate the simultaneous acquisition of electric impedance (EI), electromyography (EMG), and force myography (FMG) signals during basic wrist movements: grasping, flexion/extension, and rotation. For investigation, a laboratory instrumentation and software test setup were made for registering signals and collecting data. The analysis of the acquired signals revealed that the EI signals in conjunction with the analysis of EMG and FMG signals could potentially be highly informative in anthropomorphic control systems. The study results confirm that the comprehensive real-time analysis of EI, EMG, and FMG signals potentially allows implementing the method of anthropomorphic and proportional control with an acceptable delay.

Topics & Concepts

Computer scienceInterface (matter)Instrumentation (computer programming)ElectromyographyData acquisitionTask (project management)SimulationArtificial intelligenceEngineeringPhysical medicine and rehabilitationMedicineParallel computingBubbleSystems engineeringOperating systemMaximum bubble pressure methodMuscle activation and electromyography studiesRobot Manipulation and LearningProsthetics and Rehabilitation Robotics
A Way of Bionic Control Based on EI, EMG, and FMG Signals | Litcius