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Validation of an inertial sensor algorithm to quantify head and trunk movement in healthy young adults and individuals with mild traumatic brain injury

  • Lucy Parrington(corresponding author)
    ,
  • ,
  • Peter C. Fino
    ,
  • Sean Pearson
    ,
  • Mahmoud El-Gohary
    ,
  • Laurie A. King
*Corresponding author for this work
  • Portland VA Medical Center
    ,
  • Oregon Health and Science University
    ,
  • University of Utah
    ,
  • APDM Wearable Technologies
Scholary Output:
Contribution to journal
Article
Research
Peer-review

Open access

Abstract

Wearable inertial measurement units (IMUs) may provide useful, objective information to clinicians interested in quantifying head movements as patients’ progress through vestibular rehabilitation. The purpose of this study was to validate an IMU-based algorithm against criterion data (motion capture) to estimate average head and trunk range of motion (ROM) and average peak velocity. Ten participants completed two trials of standing and walking tasks while moving the head with and without moving the trunk. Validity was assessed using a combination of Intra-class Correlation Coefficients (ICC), root mean square error (RMSE), and percent error. Bland-Altman plots were used to assess bias. Excellent agreement was found between the IMU and criterion data for head ROM and peak rotational velocity (average ICC > 0.9). The trunk showed good agreement for most conditions (average ICC > 0.8). Average RMSE for both ROM (head = 2.64 ◦ ; trunk = 2.48 ◦ ) and peak rotational velocity (head = 11.76 ◦ /s; trunk = 7.37 ◦ /s) was low. The average percent error was below 5% for head and trunk ROM and peak rotational velocity. No clear pattern of bias was found for any measure across conditions. Findings suggest IMUs may provide a promising solution for estimating head and trunk movement, and a practical solution for tracking progression throughout rehabilitation or home exercise monitoring.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Research
Peer-review

Original language

English (US)

Article number

4501

Journal (Volume, Issue Number)

Sensors (Volume 18, Issue 12)

Publication milestones

  • Published - 12/01/2018

Publication status

Published - 12/01/2018

ISSN

1424-8220

Publication IDs

  • Scopus: 85058915804
  • PubMed: 30572640

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Funding Details

FunderFunding number
NCATS
UL1TR002369