Slip detection and prediction in human walking using only wearable inertial measurement units (IMUs)

Mitja Trkov, Kuo Chen, Jingang Yi, Tao Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

Slip and fall is one of the major causes for human injuries for elders and professional workers. Real-time detection and prediction of the foot slip is critical for developing effective assistive and rehabilitation devices to prevent falls and train balance disorder patients. This paper presents a novel real-time slip detection and prediction scheme with wearable inertial measurement units (IMUs). The slip-detection algorithm is built on a new dynamic model for bipedal walking with slips. An extended Kalman filter is designed to reliably predict the foot slip displacement using the wearable IMU measurements and kinematic constraints. The proposed slip detection and prediction scheme has been demonstrated by extensive experiments.

Original languageEnglish (US)
Title of host publicationAIM 2015 - 2015 IEEE/ASME International Conference on Advanced Intelligent Mechatronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages854-859
Number of pages6
ISBN (Electronic)9781467391078
DOIs
StatePublished - Aug 25 2015
Externally publishedYes
EventIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2015 - Busan, Korea, Republic of
Duration: Jul 7 2015Jul 11 2015

Publication series

NameIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
Volume2015-August

Conference

ConferenceIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2015
Country/TerritoryKorea, Republic of
CityBusan
Period7/7/157/11/15

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Computer Science Applications
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Slip detection and prediction in human walking using only wearable inertial measurement units (IMUs)'. Together they form a unique fingerprint.

Cite this