Lower Limb Activity Recognition Based on sEMG Using Stacked Weighted Random Forest

• Główni autorzy: Cheng Shen (Autor), Zhongcai Pei (Autor), Weihai Chen (Autor), Jianhua Wang (Autor), Xingming Wu (Autor), Jianer Chen (Autor)
• Format: Książka
• Wydane: IEEE, 2024-01-01T00:00:00Z.
• Hasła przedmiotowe: article
• Dostęp online: Connect to this object online.

The existing surface electromyography-based pattern recognition system (sEMG-PRS) exhibits limited generalizability in practical applications. In this paper, we propose a stacked weighted random forest (SWRF) algorithm to enhance the long-term usability and user adaptability of sEMG-PRS. First, the...