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A Systematic Review of EMG Applications for the Characterization of Forearm and Hand Muscle Activity during Activities of Daily Living: Results, Challenges, and Open Issues

Journal

SENSORS
Volume 21, Issue 9, Pages -

Publisher

MDPI
DOI: 10.3390/s21093035

Keywords

ADL; EMG; forearm muscles; muscles role; synergies; muscle coordination

Funding

  1. Spanish Ministry of Science, Innovation and Universities [PGC2018-095606-B-C21]
  2. Spanish MINECO
  3. European Union (FEDER funds) [DPI2014-52095-P]
  4. FPI grant [BES-2015-072480]

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The motion of the hand is crucial for daily activities, and measuring muscle activation signals is important in various scientific fields. EMG can be used for neuromuscular characterization, but complexity of the musculoskeletal system poses challenges.
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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