Intention detection for dexterous human arm motion with FSR sensor bands

Muhammad Raza Ul Islam; Shaoping Bai

doi:10.1145/3029798.3038377

Intention detection for dexterous human arm motion with FSR sensor bands

Muhammad Raza Ul Islam, Shaoping Bai

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

9 Citations (Scopus)

Abstract

Accurate detection of human intention is always challenging for the effective control of assistive and rehabilitation exoskeletons. In this paper, a human arm motion detection system is presented to recognize movements including elbow flexion, elbow extension, pronation and supination. Force sensing resistors (FSR) based sensor bands are developed to monitor the upper arm and forearm muscles activity. The bands are able to read the muscle deformation for different motions. Support Vector Machine (SVM) is implemented to recognize the motions in real time. The results have shown that the sensing method can detect the intended motions with high accuracy.

Original language	English
Title of host publication	HRI 2017 - Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction
Number of pages	2
Publisher	Association for Computing Machinery
Publication date	6 Mar 2017
Pages	139-140
ISBN (Electronic)	9781450348850
DOIs	https://doi.org/10.1145/3029798.3038377
Publication status	Published - 6 Mar 2017
Event	12th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2017 - Vienna, Austria Duration: 6 Mar 2017 → 9 Mar 2017

Conference

Conference	12th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2017
Country/Territory	Austria
City	Vienna
Period	06/03/2017 → 09/03/2017
Sponsor	ACM SIGAI, ACM SIGCHI, IEEE Robotics and Automation Society (IEEE RAS)

Keywords

exoskeleton
FSR
motion intention detection

Access to Document

10.1145/3029798.3038377

Cite this

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title = "Intention detection for dexterous human arm motion with FSR sensor bands",

abstract = "Accurate detection of human intention is always challenging for the effective control of assistive and rehabilitation exoskeletons. In this paper, a human arm motion detection system is presented to recognize movements including elbow flexion, elbow extension, pronation and supination. Force sensing resistors (FSR) based sensor bands are developed to monitor the upper arm and forearm muscles activity. The bands are able to read the muscle deformation for different motions. Support Vector Machine (SVM) is implemented to recognize the motions in real time. The results have shown that the sensing method can detect the intended motions with high accuracy.",

keywords = "exoskeleton, FSR, motion intention detection",

author = "Islam, {Muhammad Raza Ul} and Shaoping Bai",

year = "2017",

month = mar,

day = "6",

doi = "10.1145/3029798.3038377",

language = "English",

pages = "139--140",

booktitle = "HRI 2017 - Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction",

publisher = "Association for Computing Machinery",

address = "United States",

note = "12th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2017 ; Conference date: 06-03-2017 Through 09-03-2017",

}

Islam, MRU & Bai, S 2017, Intention detection for dexterous human arm motion with FSR sensor bands. in HRI 2017 - Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction. Association for Computing Machinery, pp. 139-140, 12th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2017, Vienna, Austria, 06/03/2017. https://doi.org/10.1145/3029798.3038377

Intention detection for dexterous human arm motion with FSR sensor bands. / Islam, Muhammad Raza Ul; Bai, Shaoping.

HRI 2017 - Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction. Association for Computing Machinery, 2017. p. 139-140.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - Intention detection for dexterous human arm motion with FSR sensor bands

AU - Islam, Muhammad Raza Ul

AU - Bai, Shaoping

PY - 2017/3/6

Y1 - 2017/3/6

N2 - Accurate detection of human intention is always challenging for the effective control of assistive and rehabilitation exoskeletons. In this paper, a human arm motion detection system is presented to recognize movements including elbow flexion, elbow extension, pronation and supination. Force sensing resistors (FSR) based sensor bands are developed to monitor the upper arm and forearm muscles activity. The bands are able to read the muscle deformation for different motions. Support Vector Machine (SVM) is implemented to recognize the motions in real time. The results have shown that the sensing method can detect the intended motions with high accuracy.

AB - Accurate detection of human intention is always challenging for the effective control of assistive and rehabilitation exoskeletons. In this paper, a human arm motion detection system is presented to recognize movements including elbow flexion, elbow extension, pronation and supination. Force sensing resistors (FSR) based sensor bands are developed to monitor the upper arm and forearm muscles activity. The bands are able to read the muscle deformation for different motions. Support Vector Machine (SVM) is implemented to recognize the motions in real time. The results have shown that the sensing method can detect the intended motions with high accuracy.

KW - exoskeleton

KW - FSR

KW - motion intention detection

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U2 - 10.1145/3029798.3038377

DO - 10.1145/3029798.3038377

M3 - Article in proceeding

AN - SCOPUS:85016418045

SP - 139

EP - 140

BT - HRI 2017 - Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction

PB - Association for Computing Machinery

T2 - 12th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2017

Y2 - 6 March 2017 through 9 March 2017

ER -

Intention detection for dexterous human arm motion with FSR sensor bands

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Keywords

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