Inertial measurement unit-based pose estimation: analyzing and reducing sensitivity to sensor placement and body measures

Rezvan Kianifar, Vladimir Joukov, Alexander Lee, Sachin Raina, Dana Kulic

Research output: Contribution to journalArticleResearchpeer-review


Inertial measurement units have been proposed for automated pose estimation and exercise monitoring in clinical settings. However, many existing methods assume an extensive calibration procedure, which may not be realizable in clinical practice. In this study, an inertial measurement unit-based pose estimation method using extended Kalman filter and kinematic chain modeling is adapted for lower body pose estimation during clinical mobility tests such as the single leg squat, and the sensitivity to parameter calibration is investigated.

The sensitivity of pose estimation accuracy to each of the kinematic model and sensor placement parameters was analyzed. Sensitivity analysis results suggested that accurate extraction of inertial measurement unit orientation on the body is a key factor in improving the accuracy. Hence, a simple calibration protocol was proposed to reach a better approximation for inertial measurement unit orientation.

After applying the protocol, the ankle, knee, and hip joint angle errors improved to 4.2∘,6.3∘, and 8.3∘, without the need for any other calibration.

Only a small subset of kinematic and sensor parameters contribute significantly to pose estimation accuracy when using body worn inertial sensors. A simple calibration procedure identifying the inertial measurement unit orientation on the body can provide good pose estimation performance.
Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalJournal of Rehabilitation and Assistive Technologies Engineering
Publication statusPublished - 2019
Externally publishedYes

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