On-Field Deployment and Validation for Wearable Devices

Calvin Kuo, Declan Patton, Tyler Rooks, Gregory Tierney, Andrew McIntosh, Robert Lynall, Amanda Esquivel, Ray Daniel, Thomas Kaminski, Jason Mihalik, Nate Dau, Jillian Urban

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)
50 Downloads (Pure)

Abstract

Wearable sensors are an important tool in the study of head acceleration events and head impact injuries in sporting and military activities. Recent advances in sensor technology have improved our understanding of head kinematics during on-field activities; however, proper utilization and interpretation of data from wearable devices requires careful implementation of best practices. The objective of this paper is to summarize minimum requirements and best practices for on-field deployment of wearable devices for the measurement of head acceleration events in vivo to ensure data evaluated are representative of real events and limitations are accurately defined. Best practices covered in this document include the definition of a verified head acceleration event, data windowing, video verification, advanced post-processing techniques, and on-field logistics, as determined through review of the literature and expert opinion. Careful use of best practices, with accurate acknowledgement of limitations, will allow research teams to ensure data evaluated is representative of real events, will improve the robustness of head acceleration event exposure studies, and generally improve the quality and validity of research into head impact injuries. [Abstract copyright: © 2022. The Author(s).]
Original languageEnglish
Pages (from-to)1372-1388
Number of pages17
JournalAnnals of Biomedical Engineering
Volume50
Issue number11
Early online date12 Aug 2022
DOIs
Publication statusPublished (in print/issue) - 1 Nov 2022

Bibliographical note

Funding Information:
Support for the CHAMP consensus conference was obtained from the National Football League and Football Research Inc.

Publisher Copyright:
© 2022, The Author(s).

Keywords

  • Best practices
  • Concussion
  • Head acceleration events
  • Machine learning
  • On field validation
  • Time windowing
  • Video verification
  • Wearable devices
  • Concussions

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