Intention Detection for Dexterous Human Arm Motion with FSR Sensor Bands

Islam, Muhammad Raza Ul; Bai, Shaoping

doi:10.1145/3029798.3038377

Cited by 13 publications

(11 citation statements)

References 7 publications

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“…However, the accurate measurement of cognitive or physical interaction depends upon the user's condition and selection of the muscle group. Some of the common challenges involved in measuring these techniques are highlighted in the later section, and for a detailed review, readers are refereed to References [160,161].…”

Section: Human-robot Interactionmentioning

confidence: 99%

“…Many, but not all, exoskeletons use exteroceptive sensors such as force sensitive resistors, load cells, EMG, and EEG. 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.…”

Section: Sensing and Estimationmentioning

confidence: 99%

“…Furthermore, the study is required to improve the controllability by considering the biological signals, e.g., Force myograph (FMG) and electromyography (EMG) signals to estimate the applied torque. Islam et al [161] has developed a FMG-based sensor that was initially used to estimate the upper-limb muscle contraction and relaxation. Later, it was upgraded to estimate the human upper-limb joint angles [163].…”

Section: Adaptive Controlmentioning

confidence: 99%

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A Review on Design of Upper Limb Exoskeletons

2020

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Exoskeleton robotics has ushered in a new era of modern neuromuscular rehabilitation engineering and assistive technology research. The technology promises to improve the upper-limb functionalities required for performing activities of daily living. The exoskeleton technology is evolving quickly but still needs interdisciplinary research to solve technical challenges, e.g., kinematic compatibility and development of effective human–robot interaction. In this paper, the recent development in upper-limb exoskeletons is reviewed. The key challenges involved in the development of assistive exoskeletons are highlighted by comparing available solutions. This paper provides a general classification, comparisons, and overview of the mechatronic designs of upper-limb exoskeletons. In addition, a brief overview of the control modalities for upper-limb exoskeletons is also presented in this paper. A discussion on the future directions of research is included.

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Section: Human-robot Interactionmentioning

confidence: 99%

Section: Sensing and Estimationmentioning

confidence: 99%

Section: Adaptive Controlmentioning

confidence: 99%

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A Review on Design of Upper Limb Exoskeletons

2020

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“…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…”

Section: Introductionmentioning

confidence: 99%

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

Islam

Waris

Kamavuako

et al. 2020

Journal of Rehabilitation and Assistive Technologies Engineerin

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Introduction While surface-electromyography (sEMG) has been widely used in limb motion detection for the control of exoskeleton, there is an increasing interest to use forcemyography (FMG) method to detect motion. In this paper, we review the applications of two types of motion detection methods. Their performances were experimentally compared in day-to-day classification of forearm motions. The objective is to select a detection method suitable for motion assistance on a daily basis. Methods Comparisons of motion detection with FMG and sEMG were carried out considering classification accuracy (CA), repeatability and training scheme. For both methods, classification of motions was achieved through feed-forward neural network. Repeatability was evaluated on the basis of change in CA between days and also training schemes. Results The experiments shows that day-to-day CA with FMG can reach 84.9%, compared with a CA of 77.8% with sEMG, when the classifiers were trained only on the first day. Moreover, the CA with FMG can reach to 86.5%, comparable to CA of 84.1% with sEMG, if classifiers were trained daily. Conclusions Results suggest that data recorded from FMG is more repeatable in day-to-day testing and therefore FMG-based methods can be more useful than sEMG-based methods for motion detection in applications where exoskeletons are used as needed on a daily basis.

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“…In literature, there are some reported works on using FMG to detect upper body and lower body movements Cho et al (2016); Kadkhodayan et al (2016); Xiao and Menon (2017); Sadarangani and Menon (2017); Islam and Bai (2017); Jiang et al (2016); Xiao et al (2014); Islam et al (2018). However, this approach has not been used yet for payload estimation to control upperbody exoskeleton in load carrying tasks.…”

Section: Introductionmentioning

confidence: 99%

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

Islam¹,

Bai²

2019

MIC

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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.

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Intention Detection for Dexterous Human Arm Motion with FSR Sensor Bands

Cited by 13 publications

References 7 publications

A Review on Design of Upper Limb Exoskeletons

A Review on Design of Upper Limb Exoskeletons

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

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

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