Ankle foot motion recognition based on wireless wearable sEMG and acceleration sensors for smart AFO

• Published in: Sensors and actuators. A. Physical. Vol. 331; p. 113025
• Main Authors: Zhou, Congcong, Yang, Lilin, Liao, Heng, Liang, Bo, Ye, Xuesong
• Format: Journal Article
• Language: English
• Published: Lausanne Elsevier B.V 01.11.2021; Elsevier BV
• Subjects: Acceleration; Algorithms; Ankle foot; Artificial neural networks; Classification; Data fusion; Data integration; Human motion; Motion perception; Motion recognition; Multisensor fusion; Neural networks; Principal components analysis; Recognition; Sensors; Smart sensors; Studies; Support vector machines; Three axis; Wearable computers; Wireless signal acquisition system (WAS); Wireless signal acquisition system (WAS); Data fusion; Motion recognition; Ankle foot

[Display omitted] •A wireless signal acquisition system (WAS) was designed specifically, high precision sEMG signal and three-axis ACC data were acquired simultaneously.•TKEO based signal preprocessing algorithm was proposed to detect the onset of the raw data.•Features from sEMG and ACC data of fou...