Adaptive Control Design for Human Handwriting Process Based on Electromyography Signals

Imane Mahmoud,Ines Chihi,Afef Abdelkrim

doi:10.1155/2020/5142870

Abstract

The most used control approaches of hand prosthesis are based on the forearm muscle activities, named ElectroMyoGraphy signal (EMG). In this sense, researchers modeled the hand writing on the plane only from two EMG signals. Based on this analysis, we can consider the hand as a robot with two arms (two degrees of freedom) moving on (x, y) plane. However, these signals are very sensitive to many disturbances and are generally unpredictable in time, type, and level. Based on forearm EMG signals, this work aims to propose an adaptive hand-robot control design to generate handwriting. As a first step, we develop the application of the classic proportional integral structure (PI). The PI controller was applied to generate different essays of handwritten graphic traces in one-writer case and multiwriter case. Both cases have presented unsatisfactory results in generating cursive letters and forms. Indeed, we propose, as a second approach, an adaptive PI controller with varying Integral Ki gain, according to EMG signals, in order to deal with operation changes.

Highlights

In the last decades, several investigators are interested in improving the quality of hand prosthesis robots to make them functional, more convenient to use. ese improvements concern movements requiring precision, such as typing text on a key board, fluffing an apple, or even handwriting with conserving the individual characteristics of the writer.e increase in functionality of hand prosthesis is mainly based on the progression of the control strategies. e most used control approach is based on the amplifier electrical activity of the muscles, ElectroMyoGraphy signal (EMG) signal, which allows encoding directly the orders generated by the brain [1,2,3,4].e wealth of information of these biological signals leads many researchers to propose approaches based on the muscular activity control
E increase in functionality of hand prosthesis is mainly based on the progression of the control strategies. e most used control approach is based on the amplifier electrical activity of the muscles, EMG signal, which allows encoding directly the orders generated by the brain [1,2,3,4]
Kawanishi et al developed in [6] a fuzzy logic controller for position control of the biomimetic robot finger designed by Hristu et al [7]

Summary

Introduction

Several investigators are interested in improving the quality of hand prosthesis robots to make them functional, more convenient to use. ese improvements concern movements requiring precision, such as typing text on a key board, fluffing an apple, or even handwriting with conserving the individual characteristics of the writer (roundness or sharpness, inclination, regular or irregular spacing between letters, etc.). Some researchers show that the hand writing on the plane (x, y) can be modeled only from two forearm muscle activities, named “Abductor Pollicis Longus” and “Extensor Capri Ulnaris.” e first assures vertical movement, and the second assures horizontal displacement [10, 13, 14] Based on this analysis, we can consider the hand as a robot modeled by two arms. E muscles of the forearm, intervening in the act of handwriting, are located directly under the skin, allowing the use of surface electrodes to record the EMG signals To characterize this biological process, Manabu proposed in [23] an experimental approach for recording, at the same time, the graphic traces’ coordinates in the (x, y) plane and electromyography signals from the front arms involved in the production of handwriting movements.

Characterization of Handwriting Process

Handwriting Assistive Robot Arm Design

Assistive Robot Arm Control

Adaptive Handwriting Control Design