PREDICTION of the SPATIO-TEMPORAL GAIT PARAMETERS USING INERTIAL SENSOR

Jian Liu, Thurmon Lockhart, Sukwon Kim

Research output: Contribution to journalArticle

Abstract

Monitoring human gait is essential to quantify gait issues associated with fall-prone individuals as well as other gait-related movement disorders. Being portable and cost-effective, ambulatory gait analysis using inertial sensors is considered a promising alternative to traditional laboratory-based approach. The current study aimed to provide a method for predicting the spatio-temporal gait parameters using the wrist-worn inertial sensors. Eight young adults were involved in a laboratory study. Optical motion analysis system and force-plates were used for the assessment of baseline gait parameters. Spatio-temporal features of an Inertial Measurement Unit (IMU) on the wrist were analyzed. Multi-variate correlation analyses were performed to develop gait parameter prediction models. The results indicated that gait stride time was strongly correlated with peak-to-peak duration of wrist gyroscope signal in the anterio-posterior direction. Meanwhile, gait stride length was successfully predicted using a combination model of peak resultant wrist acceleration and peak sagittal wrist angle. In conclusion, current study provided the evidence that the wrist-worn inertial sensors are capable of estimating spatio-temporal gait parameters. This finding paves the foundation for developing a wrist-worn gait monitor with high user compliance.

Original languageEnglish (US)
JournalJournal of Mechanics in Medicine and Biology
DOIs
StateAccepted/In press - Jan 1 2018

Keywords

  • fall-prone
  • gait
  • gyroscope
  • IMUs
  • spatio-temporal gait parameters
  • wearable sensor

ASJC Scopus subject areas

  • Biomedical Engineering

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