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Okita S, Yakunin R, Korrapati J, Ibrahim M, Schwerz de Lucena D, Chan V, Reinkensmeyer DJ. Counting Finger and Wrist Movements Using Only a Wrist-Worn, Inertial Measurement Unit: Toward Practical Wearable Sensing for Hand-Related Healthcare Applications. Sensors (Basel) 2023; 23:5690. [PMID: 37420857 DOI: 10.3390/s23125690] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 06/08/2023] [Accepted: 06/15/2023] [Indexed: 07/09/2023]
Abstract
The ability to count finger and wrist movements throughout the day with a nonobtrusive, wearable sensor could be useful for hand-related healthcare applications, including rehabilitation after a stroke, carpal tunnel syndrome, or hand surgery. Previous approaches have required the user to wear a ring with an embedded magnet or inertial measurement unit (IMU). Here, we demonstrate that it is possible to identify the occurrence of finger and wrist flexion/extension movements based on vibrations detected by a wrist-worn IMU. We developed an approach we call "Hand Activity Recognition through using a Convolutional neural network with Spectrograms" (HARCS) that trains a CNN based on the velocity/acceleration spectrograms that finger/wrist movements create. We validated HARCS with the wrist-worn IMU recordings obtained from twenty stroke survivors during their daily life, where the occurrence of finger/wrist movements was labeled using a previously validated algorithm called HAND using magnetic sensing. The daily number of finger/wrist movements identified by HARCS had a strong positive correlation to the daily number identified by HAND (R2 = 0.76, p < 0.001). HARCS was also 75% accurate when we labeled the finger/wrist movements performed by unimpaired participants using optical motion capture. Overall, the ringless sensing of finger/wrist movement occurrence is feasible, although real-world applications may require further accuracy improvements.
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Affiliation(s)
- Shusuke Okita
- Department of Mechanical and Aerospace Engineering, University of California Irvine, Irvine, CA 92697, USA
- Department of Anatomy and Neurobiology, University of California Irvine, Irvine, CA 92697, USA
| | - Roman Yakunin
- College of Computing, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Jathin Korrapati
- Department of Electrical Engineering and Computer Science, University of California Berkeley, Berkeley, CA 94720, USA
| | - Mina Ibrahim
- Department of Biomedical Engineering, University of California Irvine, Irvine, CA 92697, USA
| | - Diogo Schwerz de Lucena
- AE Studio, Venice, CA 90291, USA
- CAPES Foundation, Ministry of Education of Brazil, Brasilia 70040-020, Brazil
| | - Vicky Chan
- Rehabilitation Services, University of California Irvine, Irvine, CA 92697, USA
| | - David J Reinkensmeyer
- Department of Mechanical and Aerospace Engineering, University of California Irvine, Irvine, CA 92697, USA
- Department of Anatomy and Neurobiology, University of California Irvine, Irvine, CA 92697, USA
- Department of Biomedical Engineering, University of California Irvine, Irvine, CA 92697, USA
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