Estimation of the knee adduction moment and joint contact force during daily living activities using inertial motion capture

Jason Konrath, Angelos Karatsidis, Martin Schepers, Giovanni Bellusci, Mark de Zee, Michael Skipper Andersen

Research output: Contribution to journalJournal articleResearchpeer-review

2 Citations (Scopus)
115 Downloads (Pure)

Abstract

Knee osteoarthritis is a major cause of pain and disability in the elderly population with many daily living activities being difficult to perform as a result of this disease. The present study aimed to estimate the knee adduction moment and tibiofemoral joint contact force during daily living activities using a musculoskeletal model with inertial motion capture derived kinematics in an elderly population. Eight elderly participants were instrumented with 17 inertial measurement units, as well as 53 opto-reflective markers affixed to anatomical landmarks. Participants performed stair ascent, stair descent, and sit-to-stand movements while both motion capture methods were synchronously recorded. A musculoskeletal model containing 39 degrees-of-freedom was used to estimate the knee adduction moment and tibiofemoral joint contact force. Strong to excellent Pearson correlation coefficients were found for the IMC-derived kinematics across the daily living tasks with root mean square errors (RMSE) between 3 and 7 . Furthermore, moderate to strong Pearson correlation coefficients were found in the knee adduction moment and tibiofemoral joint contact forces with RMSE between 0.006–0.014 body weight × body height and 0.4 to 1 body weights, respectively. These findings demonstrate that inertial motion capture may be used to estimate knee adduction moments and tibiofemoral contact forces with comparable accuracy to optical motion capture.

Original languageEnglish
Article number1681
JournalSensors
Volume19
Issue number7
ISSN1424-8220
DOIs
Publication statusPublished - 9 Apr 2019

Keywords

  • IMU
  • Knee osteoarthritis
  • Motion capture
  • Musculoskeletal model
  • Wearable technology

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