New Artificial Intelligence-Integrated Electromyography-Driven Robot Hand for Upper Extremity Rehabilitation of Patients With Stroke: A Randomized, Controlled Trial.
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引用次数: 1
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. 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.
期刊介绍：
Neurorehabilitation & Neural Repair (NNR) offers innovative and reliable reports relevant to functional recovery from neural injury and long term neurologic care. The journal''s unique focus is evidence-based basic and clinical practice and research. NNR deals with the management and fundamental mechanisms of functional recovery from conditions such as stroke, multiple sclerosis, Alzheimer''s disease, brain and spinal cord injuries, and peripheral nerve injuries.
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