Estimation of gait events and kinetic waveforms with wearable sensors and machine learning when running in an unconstrained environment

HIGHLIGHTS

  • who: Seth R. Donahue from the Department University of have published the research: Estimation of gait events and kinetic waveforms with wearable sensors and machine learning when running in an unconstrained environment, in the Journal: Scientific Reports Scientific Reports
  • what: The aim of this study was to test two specific methods for the biomechanical analysis of running in an unconstrained environment: a heuristic algorithm for the estimation of foot contacts from IMU data; a machine_learning algorithm, BD-LSTM, for estimation of normal GRFs between the foot and shoe, specifically foot contact events and discrete GRF . . .

     

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