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

• Hauptverfasser: Cheng Shen (Verfasst von), Zhongcai Pei (Verfasst von), Weihai Chen (Verfasst von), Jianhua Wang (Verfasst von), Xingming Wu (Verfasst von), Jianer Chen (Verfasst von)
• Format: Buch
• Veröffentlicht: IEEE, 2024-01-01T00:00:00Z.
• Schlagworte: article
• Online-Zugang: 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...