Multi-modal sensing techniques for interfacing hand prostheses: a review

Yinfeng Fang; Nalinda Hettiarachchi; Dalin Zhou; Honghai Liu

doi:10.1109/JSEN.2015.2450211

Multi-modal sensing techniques for interfacing hand prostheses: a review

Yinfeng Fang, Nalinda Hettiarachchi, Dalin Zhou, Honghai Liu

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Abstract

This paper provides a comprehensive survey of current state of the bio-sensing technologies focusing on hand motion capturing and its application to interfacing hand prostheses. These sensing techniques include electromyography, sonomyography, mechnomyography, electroneurography, electroencephalograhy, electrocorticography, intracortical neural interfaces, near infrared spectroscopy, magnetoencephalography, and functional magnetic resonance imaging. Relevant approaches that interpret bio-signals in the view of prosthetic hand manipulation are discussed as well. Multi-modal sensory fusion provides a new strategy in this area, and the latest multi-modal sensing techniques are surveyed. This paper also outlines the new challenges and directions: 1) exploration of robust sensing technology; 2) multi-modal sensory fusion; 3) online signal processing and learning algorithms; and 4) bio-feedbacks.

Original language	English
Pages (from-to)	6065-6076
Journal	IEEE Sensors Journal
Volume	15
Issue number	11
DOIs	https://doi.org/10.1109/JSEN.2015.2450211
Publication status	Published - 29 Jul 2015

Keywords

Bio-sensing technology
electromyography,
sonomyography
mechnomyography
electroencephalograhy,
hand prostheses
multi-modal sensing

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10.1109/JSEN.2015.2450211

Sensors-12229-2015.R2
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Accepted author manuscript (Post-print), 3.86 MB

Cite this

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title = "Multi-modal sensing techniques for interfacing hand prostheses: a review",

abstract = "This paper provides a comprehensive survey of current state of the bio-sensing technologies focusing on hand motion capturing and its application to interfacing hand prostheses. These sensing techniques include electromyography, sonomyography, mechnomyography, electroneurography, electroencephalograhy, electrocorticography, intracortical neural interfaces, near infrared spectroscopy, magnetoencephalography, and functional magnetic resonance imaging. Relevant approaches that interpret bio-signals in the view of prosthetic hand manipulation are discussed as well. Multi-modal sensory fusion provides a new strategy in this area, and the latest multi-modal sensing techniques are surveyed. This paper also outlines the new challenges and directions: 1) exploration of robust sensing technology; 2) multi-modal sensory fusion; 3) online signal processing and learning algorithms; and 4) bio-feedbacks.",

keywords = "Bio-sensing technology, electromyography,, sonomyography, mechnomyography, electroencephalograhy,, hand prostheses, multi-modal sensing",

author = "Yinfeng Fang and Nalinda Hettiarachchi and Dalin Zhou and Honghai Liu",

note = "Fang, Yinfeng, et al. {"}Multi-Modal Sensing Techniques for Interfacing Hand Prostheses: A Review.{"} Sensors Journal, IEEE 15.11 (2015): 6065-6076.",

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AU - Fang, Yinfeng

AU - Hettiarachchi, Nalinda

AU - Zhou, Dalin

AU - Liu, Honghai

N1 - Fang, Yinfeng, et al. "Multi-Modal Sensing Techniques for Interfacing Hand Prostheses: A Review." Sensors Journal, IEEE 15.11 (2015): 6065-6076.

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AB - This paper provides a comprehensive survey of current state of the bio-sensing technologies focusing on hand motion capturing and its application to interfacing hand prostheses. These sensing techniques include electromyography, sonomyography, mechnomyography, electroneurography, electroencephalograhy, electrocorticography, intracortical neural interfaces, near infrared spectroscopy, magnetoencephalography, and functional magnetic resonance imaging. Relevant approaches that interpret bio-signals in the view of prosthetic hand manipulation are discussed as well. Multi-modal sensory fusion provides a new strategy in this area, and the latest multi-modal sensing techniques are surveyed. This paper also outlines the new challenges and directions: 1) exploration of robust sensing technology; 2) multi-modal sensory fusion; 3) online signal processing and learning algorithms; and 4) bio-feedbacks.

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KW - sonomyography

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KW - electroencephalograhy,

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EP - 6076

JO - IEEE Sensors Journal

JF - IEEE Sensors Journal

IS - 11

ER -

Multi-modal sensing techniques for interfacing hand prostheses: a review

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Keywords

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