基于多模态数据融合方法的动作识别技术研究

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中图分类号：TP391 文献标志码：A 文章编号：2095-2945（2025）23-0038-04

Abstract：Withthedevelopmentofdeplearningtechnology，electromyographic （EMG）actionrecognitiontechnologyhas achievedmanysignificantachievements.However，singlemodeEMGdataisdficulttofulldescribethemovementintention containedinEMGsignals.ThisresearchfocusesontheEMGgesturerecognitiontechnology，proposesamotionrecognitionmethod basedonmulti-modaldatafusion，focusesontheanalysisoftherecognitionaccuracyandtimeconsumptionofthemethodand comparesitwiththeactionrecognitionmethodbasedonsinglemodetoveriftheefectivenessoftheproposedmetod.Thisstudy will provide useful theoretical references for the developmentof electromyographicactionrecognition technology.

Keywords： electromyographic（EMG）;gesture recognition; multimodal;Deep Learning; exercise posture

肌电信号由于其易采集及可以表达人体运动意图的特性被广泛地应用于假肢、康复机器人及智能家居设备的控制信号。（剩余4210字）