A Lightweight Machine Learning Framework for Post-Stroke Gait Abnormality Classification Using Wearable Gyroscope Features
Accurately classifying gait abnormalities is crucial for the effective monitoring and rehabilitation of stroke patients. This study proposed a lightweight machine learning framework for distinguishing healthy from abnormal gait patterns using statistical features extracted from wearable gyroscope da...
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| Asıl Yazarlar: | , , , , , |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
MDPI AG
2026-05-01
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| Seri Bilgileri: | Sensors |
| Konular: | |
| Online Erişim: | https://www.mdpi.com/1424-8220/26/10/3143 |
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