Reliability and agreement between two wearable inertial sensor devices for measurement of arm activity during walking and running gait. Academic Article uri icon

Overview

abstract

  • STUDY DESIGN: This is a validation study. BACKGROUND: Tracking limb movement with body worn sensors allows clinicians to measure limb dynamics to guide treatment for patients with movement disorders. The current gold standard, 3-dimensional optical motion capture, is costly, time-consuming, requires specific training, and is conducted in specialized laboratories. PURPOSE: The purpose of our study was to a compare consumer-grade inertial sensor to a laboratory-grade sensor to provide additional methods for capturing limb dynamics. METHODS: The participants wore an Apple Watch and a laboratory-grade Xsens sensor on each wrist during 3 conditions: walk, fast-walk, and run. Acceleration data were collected simultaneously on each device per wrist for all conditions. Intraclass correlation coefficients and Bland-Altman plots were calculated to measure intra-/interdevice reliability, evaluate bias, and limits of agreement. RESULTS: Intradevice ICCs showed good reliability during walk and fast-walk (0.79-0.87) and excellent reliability during run (0.94-0.97) conditions. Inter-device ICCs yielded moderate reliability during walk (0.52 ± 0.22) and excellent reliability in fast-walk and run (0.93 ± 0.02, 1.00 ± 0.01) conditions. Bland-Altman plots showed small biases with 90% or more of the data contained within the limits of agreement. DISCUSSION: Our study demonstrates reliability and agreement between the two devices, suggesting that both can reliably capture upper extremity motion data during gait trials. CONCLUSION: Our findings support further study of consumer-grade motion trackers to measure arm activity for clinical use. These devices are inexpensive, user-friendly, and allow for data collection outside of the laboratory.

publication date

  • August 20, 2020

Research

keywords

  • Arm
  • Running
  • Walking
  • Wearable Electronic Devices

Identity

Scopus Document Identifier

  • 85095770088

Digital Object Identifier (DOI)

  • 10.1016/j.jht.2020.08.001

PubMed ID

  • 33187807

Additional Document Info

volume

  • 35

issue

  • 1