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

Fingerprint

Sensors
Gait analysis
Units of measurement
Gyroscopes
Monitoring
Costs
Motion analysis
Compliance

Keywords

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

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

PREDICTION of the SPATIO-TEMPORAL GAIT PARAMETERS USING INERTIAL SENSOR. / Liu, Jian; Lockhart, Thurmon; Kim, Sukwon.

In: Journal of Mechanics in Medicine and Biology, 01.01.2018.

Research output: Contribution to journalArticle

@article{901bd2f6009c4eb795962cafb926b586,
title = "PREDICTION of the SPATIO-TEMPORAL GAIT PARAMETERS USING INERTIAL SENSOR",
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.",
keywords = "fall-prone, gait, gyroscope, IMUs, spatio-temporal gait parameters, wearable sensor",
author = "Jian Liu and Thurmon Lockhart and Sukwon Kim",
year = "2018",
month = "1",
day = "1",
doi = "10.1142/S021951941840002X",
language = "English (US)",
journal = "Journal of Mechanics in Medicine and Biology",
issn = "0219-5194",
publisher = "World Scientific Publishing Co. Pte Ltd",

}

TY - JOUR

T1 - PREDICTION of the SPATIO-TEMPORAL GAIT PARAMETERS USING INERTIAL SENSOR

AU - Liu, Jian

AU - Lockhart, Thurmon

AU - Kim, Sukwon

PY - 2018/1/1

Y1 - 2018/1/1

N2 - 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.

AB - 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.

KW - fall-prone

KW - gait

KW - gyroscope

KW - IMUs

KW - spatio-temporal gait parameters

KW - wearable sensor

UR - http://www.scopus.com/inward/record.url?scp=85056102462&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85056102462&partnerID=8YFLogxK

U2 - 10.1142/S021951941840002X

DO - 10.1142/S021951941840002X

M3 - Article

AN - SCOPUS:85056102462

JO - Journal of Mechanics in Medicine and Biology

JF - Journal of Mechanics in Medicine and Biology

SN - 0219-5194

ER -