New Artificial Intelligence-Integrated Electromyography-Driven Robot Hand for Upper Extremity Rehabilitation of Patients With Stroke: A Randomized, Controlled Trial. (May 2023)
- Record Type:
- Journal Article
- Title:
- New Artificial Intelligence-Integrated Electromyography-Driven Robot Hand for Upper Extremity Rehabilitation of Patients With Stroke: A Randomized, Controlled Trial. (May 2023)
- Main Title:
- New Artificial Intelligence-Integrated Electromyography-Driven Robot Hand for Upper Extremity Rehabilitation of Patients With Stroke: A Randomized, Controlled Trial
- Authors:
- Murakami, Yuhei
Honaga, Kaoru
Kono, Hidemi
Haruyama, Koshiro
Yamaguchi, Tomofumi
Tani, Mami
Isayama, Reina
Takakura, Tomokazu
Tanuma, Akira
Hatori, Kozo
Wada, Futoshi
Fujiwara, Toshiyuki - Abstract:
- Background: An artificial intelligence (AI)-integrated electromyography (EMG)-driven robot hand was devised for upper extremity (UE) rehabilitation. This robot detects patients' intentions to perform finger extension and flexion based on the EMG activities of 3 forearm muscles. Objective: This study aimed to assess the effect of this robot in patients with chronic stroke. Methods: This was a single-blinded, randomized, controlled trial with a 4-week follow-up period. Twenty patients were assigned to the active (n = 11) and control (n = 9) groups. Patients in the active group received 40 minutes of active finger training with this robot twice a week for 4 weeks. Patients in the control group received passive finger training with the same robot. The Fugl-Meyer assessment of UE motor function (FMA), motor activity log-14 amount of use score (MAL-14 AOU), modified Ashworth scale (MAS), H reflex, and reciprocal inhibition were assessed before, post, and post-4 weeks (post-4w) of intervention. Results: FMA was significantly improved at both post ( P = .011) and post-4w ( P = .021) in the active group. The control group did not show significant improvement in FMA at the post. MAL-14 AOU was improved at the post in the active group ( P = .03). In the active group, there were significant improvements in wrist MAS at post ( P = .024) and post-4w ( P = .026). Conclusions: The AI-integrated EMG-driven robot improved UE motor function and spasticity, which persisted for 4 weeks. ThisBackground: An artificial intelligence (AI)-integrated electromyography (EMG)-driven robot hand was devised for upper extremity (UE) rehabilitation. This robot detects patients' intentions to perform finger extension and flexion based on the EMG activities of 3 forearm muscles. Objective: This study aimed to assess the effect of this robot in patients with chronic stroke. Methods: This was a single-blinded, randomized, controlled trial with a 4-week follow-up period. Twenty patients were assigned to the active (n = 11) and control (n = 9) groups. Patients in the active group received 40 minutes of active finger training with this robot twice a week for 4 weeks. Patients in the control group received passive finger training with the same robot. The Fugl-Meyer assessment of UE motor function (FMA), motor activity log-14 amount of use score (MAL-14 AOU), modified Ashworth scale (MAS), H reflex, and reciprocal inhibition were assessed before, post, and post-4 weeks (post-4w) of intervention. Results: FMA was significantly improved at both post ( P = .011) and post-4w ( P = .021) in the active group. The control group did not show significant improvement in FMA at the post. MAL-14 AOU was improved at the post in the active group ( P = .03). In the active group, there were significant improvements in wrist MAS at post ( P = .024) and post-4w ( P = .026). Conclusions: The AI-integrated EMG-driven robot improved UE motor function and spasticity, which persisted for 4 weeks. This robot hand might be useful for UE rehabilitation of patients with stroke. Clinical Trial Registry Name: The effect of robotic rehabilitation using XMM-HR2 for the paretic upper extremity among hemiparetic patients with stroke. Clinical Trial Registration-URL: https://jrct.niph.go.jp/ Unique Identifier: jRCTs032200045. … (more)
- Is Part Of:
- Neurorehabilitation & neural repair. Volume 37:Number 5(2023)
- Journal:
- Neurorehabilitation & neural repair
- Issue:
- Volume 37:Number 5(2023)
- Issue Display:
- Volume 37, Issue 5 (2023)
- Year:
- 2023
- Volume:
- 37
- Issue:
- 5
- Issue Sort Value:
- 2023-0037-0005-0000
- Page Start:
- 298
- Page End:
- 306
- Publication Date:
- 2023-05
- Subjects:
- rehabilitation -- robotics -- upper extremity -- cerebrovascular disease -- hemiparesis
Nervous system -- Diseases -- Patients -- Rehabilitation -- Periodicals
Brain damage -- Patients -- Rehabilitation -- Periodicals
Spinal cord -- Wounds and injuries -- Patients -- Rehabilitation -- Periodicals
Nervous system -- Regeneration -- Periodicals
Neuroplasticity -- Periodicals
616.804305 - Journal URLs:
- http://journals.sagepub.com/home/nnr ↗
http://www.uk.sagepub.com ↗
http://firstsearch.oclc.org ↗ - DOI:
- 10.1177/15459683231166939 ↗
- Languages:
- English
- ISSNs:
- 1545-9683
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 27037.xml