Development of an EMG-based Human-Machine Interface on Open-source Linux Platform for Evaluating the Motor Skill Acquisi
Human-machine interface (HMI) not only assists disabled people to perform tasks and activities, but also helps in acquisition of motor skills for rehabilitation. Therefore, it is critically important to qualitatively assessthe motor skill acquisition proc
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Graduate School of Informatics and Engineering, The University of Electro-Communications, Japan 2
[email protected]
Graduate School of Engineering, Chiba University, Japan [email protected]
Abstract. Human-machine interface (HMI) not only assists disabled people to perform tasks and activities, but also helps in acquisition of motor skills for rehabilitation. Therefore, it is critically important to qualitatively assess the motor skill acquisition process during the operation of HMI. Some of the recent studies observed and analyzed that changes in bio-signals were closely related to the improvement of motor skill. This paper presents a HMI for balancing the control of virtual inverted pendulum using electromyography (EMG) signals. The proposed HMI was developed using an open-source control software RTAI (Real Time Application Interface) on Linux platform. EMG signals from the forearm were recorded using two EMG electrodes placed around the extensor carpi radialis longus and flexor carpi ulnaris muscles. Moreover, the motor skills were evaluated by classifying the EMG signal patterns (i.e., muscle activation patterns), and measuring the motion of inverted pendulum including angular position, speed, and acceleration. An experiment was conducted using the proposed HMI with 8 subjects in laboratory. The results showed that the proposed HMI is useful to examine the motor skill acquisition process, as the EMG signal patterns closely resembled to that of human motor process.
ment of the motor skill acquisition process during its operation. In the conventional approach, the accuracy of motion and time for completing a task is usually used for evaluating scores. However, some of recent studies indicated that observe and analyze the changes of bio-signals were closely related to the improvement of motor skill [5].
Keywords: Human-machine interface, motor skill, EMG, Opensource Linux.
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Introduction
With the advancement of computing and bio-sensing technology, a variety of human-machine interfaces (HMIs) are being intensively studied to augment human abilities [1, 2]. Many bio-signals can be sent to a machine/computer as command signals to control it. For instance, a functional prosthetic hand was developed for improving the daily reaching and grasping activities of disabled people using surface electromyography (EMG) signal [3]. Such assistive HMI not only assists disabled people to perform tasks and activities, but also helps in the acquisition of motor skills for rehabilitation [4]. To develop a userfriendly HMI, it is necessary to make a qualitative assess-
For this study, we developed an EMG-based HMI for evaluating the motor skill acquisition process via analysis of EMG signals. The proposed HMI design phases consisted of signal acquisition, signal processing, feature classification, and performance evaluation. First, we adopted an opensource signal acquisition hardware and signal processing software on a real-time Linux operating system. Next, a simple inverted pendulum simulator was constructe
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