Payload estimation using forcemyography sensors for control of upper-body exoskeleton in load carrying assistance

Abstract

In robotic assistive devices, the determination of required assistance is vital for proper functioning of assistive control. This paper presents a novel solution to measure conveniently and accurately carried payload in order to estimate the required assistance level. The payload is estimated using upper arm forcemyography (FMG) through a sensor band made of force sensitive resistors. The sensor band is worn on the upper arm and is able to measure the change of normal force applied due to muscle contraction. The readings of the sensor band are processed using support vector machine (SVM) regression technique to estimate the payload. The developed method was tested on human subjects, carrying a payload. Experiments were further conducted on an upper-body exoskeleton to provide the required assistance. The results show that the developed method is able to estimate the load carrying status, which can be used in exoskeleton control to provide effectively physical assistance needed.

A Review on Design of Upper Limb Exoskeletons

“…References [161][162][163] have used force-sensitive resistors (FSR) to estimate the different arm movements for exoskeleton control. Reference [164] has used FSR sensors for the payload estimation of robotic exoskeleton. Moreover, force sensors including FSRs and load cells are being used to measure the interaction pressure over the whole contact area between the upper limb and exoskeleton [48,50,55,79,165,166].…”

“…Based on muscle contraction and relaxation, the sensor data was processed to identify the joint angles via support vector machine algorithm. This technique was adopted to estimate the payload for an exoskeleton application in Reference [164], where the exoskeleton can provide physical assistance to the human upper limb in carrying the heavy load. Similarly, Zhen et al [162] have investigated the minimum sampling frequency of forearm and wrist FMG for movement monitoring applications.…”

Effective Multi-Mode Grasping Assistance Control of a Soft Hand Exoskeleton Using Force Myography

“…This novel method using FSR sensor bands offers a robust and accurate alternative for human-robot interaction. The works presented in this paper and in previous studies (Islam et al, 2018;Islam and Bai, 2019) have shown that FSR-based sensor bands can be applied for control of upper-body assistive exoskeletons in different ways. Beside these, sensor bands can be applied for other types of applications of upper-limb and lower-limb exoskeletons.…”

“…Proper control of the exoskeleton depends mainly on accurate human intention detection. Several methods to determine human intention that are based on electromyography (EMG) (Anam et al, 2017 ; Meng et al, 2017 ; Pinzón-Arenas et al, 2019 ; Qi et al, 2019 ; Zhang et al, 2019 ; Asif et al, 2020 ) and force myography (FMG) (Islam and Bai, 2019 ; Xiao and Menon, 2019 , 2020 ) have been proposed. Leonardis et al ( 2015 ) used EMG to control a hand exoskeleton for bilateral rehabilitation.…”

A comparative study of motion detection with FMG and sEMG methods for assistive applications

“…23–26 The results indicate that performance continuously downgrades as the time difference between training and testing day increases. On the other hand, FMG as an alternative to detect upper and lower limb muscle activities has been used in different applications with healthy subject 27–37 and with stroke/amputated subjects. 38,39…”