Development of a Hybrid Surface EMG and MMG Acquisition System for Human Hand Motion Analysis

The role of the hand is crucial for the performance of activities of daily living, thereby ensuring a full and autonomous life. Its motion is controlled by a complex musculoskeletal system of approximately 38 muscles. Therefore, measuring and interpreting the muscle activation signals that drive hand motion is of great importance in many scientific domains, such as neuroscience, rehabilitation, physiotherapy, robotics, prosthetics, and biomechanics. Electromyography (EMG) can be used to carry out the neuromuscular characterization, but it is cumbersome because of the complexity of the musculoskeletal system of the forearm and hand. This paper reviews the main studies in which EMG has been applied to characterize the muscle activity of the forearm and hand during activities of daily living, with special attention to muscle synergies, which are thought to be used by the nervous system to simplify the control of the numerous muscles by actuating them in task-relevant subgroups. The state of the art of the current results are presented, which may help to guide and foster progress in many scientific domains. Furthermore, the most important challenges and open issues are identified in order to achieve a better understanding of human hand behavior, improve rehabilitation protocols, more intuitive control of prostheses, and more realistic biomechanical models.

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Hand motion analysis of the pianist

The Japanese Journal of Ergonomics ◽

10.5100/jje.31.supplement_74 ◽

1995 ◽

Vol 31 (Supplement) ◽

pp. 74-77

Author(s):

Naotaka Sakai ◽

Tomihisa Koshino ◽

Fong-Chin Su ◽

Michael C Liu ◽

Allen T Bishop ◽

...

Keyword(s):

Motion Analysis ◽

Hand Motion

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Human hand motion retargeting for dexterous robotic hand

2021 18th International Conference on Ubiquitous Robots (UR) ◽

10.1109/ur52253.2021.9494665 ◽

2021 ◽

Author(s):

Jedrzej Orbik ◽

Shile Li ◽

Dongheui Lee

Keyword(s):

Human Hand ◽

Robotic Hand ◽

Hand Motion ◽

Motion Retargeting

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Surface EMG and Upper-Limb Rehabilitation

Early Detection and Rehabilitation Technologies for Dementia ◽

10.4018/978-1-60960-559-9.ch041 ◽

2011 ◽

pp. 335-343

Author(s):

Kazuya Funada ◽

Jinglong Wu ◽

Satoshi Takahashi

Keyword(s):

Experimental System ◽

Surface Emg ◽

Passive Movement ◽

Measuring Device ◽

Upper Limb Rehabilitation ◽

Hand Motion ◽

Characteristic Points ◽

Opening And Closing ◽

Limb Rehabilitation ◽

Simple Measuring

In rehabilitating hemiplegic patients, purposeful movements such as the opening and closing of hands are reported to be more effective than passive movement with an instrument. The authors of this chapter used surface electromyogram (surface EMG) signals as a way to convey the patient’s conscious ability to open and close their hands. The muscles in the forearm contract when the hand is closed or opened, which creates a simple signal that is comparatively easy to measure with surface EMG, a simple measuring device. The action potentials of the muscles involved in the opening-and-closing motions of hands were measured from several points in the forearm when those muscles contracted, and their distribution was analyzed. The purpose of this study is to develop a simple system to recognize the movement of a patient’s hand using measurements of EMG signals from only the most characteristic points on the forearm to replace similar, but more complex, research such as multi-channel measurement and wave analysis by FFT. The authors specified the optimum measuring points on the palm and dorsal sides of the forearm for the recognition of hand motion by the experimental system. This system successfully recognized hand motion through the analysis of the surface EMG signals measured from only two optimum points to allow arbitrary control of the rehabilitation device based on the recognition results.

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