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

Muhammad Raza Ul Islam, Shaoping Bai

Year
2019
Citations
31
Access
Open access

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.

Keywords

Payload (computing)ExoskeletonEstimationComputer scienceControl theory (sociology)Control (management)EngineeringSimulationArtificial intelligenceComputer security

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