Using automated, unsupervised sensor based evaluation as a complement to PROMs to assess surgery outcomes

6 pages•Published: December 17, 2024

Julien Lebleu, Andries Pauwels, Ward Servaes, Wanne Wiersinga and Bruno Bonnechère

Abstract

This study explores the use of automated unsupervised evaluations via wearable devices, to assess the success of hip and knee replacements as a complement to traditional PROMs.
A comprehensive analysis was conducted on data from 1144 TKA and THA patients utilizing a mobile application, with activity data collected through the Garmin Vivofit 4 wearable device. Key parameters, including daily Peak 6-Minute Consecutive Cadence (P6MC) and daily Peak 1-Minute Cadence (P1M), were computed pre and post surgery and analyzed to assess the efficacy of these metrics in monitoring the recovery progress and the surgery outcomes.
Cadence measurements, specifically P6MC and P1M, emerged as robust indicators. These metrics exhibited a superior level of responsiveness compared to traditional step- count measurements and showed good complementarity with PRO’s traditionally used in clinical practices. Moreover, the capture of these parameters being daily, unsupervised, and automated gives the potential of offering more granularity and better compliance than PROMs, providing new insights to assess quality of new surgical techniques. Moreover, the growing ubiquity of smartphones and wearables makes the use of such metrics usable in daily practice.

Keyphrases: hip arthroplasty, knee arthroplasty, mobile application, physical activity, prom, wearable

In: Joshua W Giles and Aziliz Guezou-Philippe (editors). Proceedings of The 24th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery, vol 7, pages 129-134.

Links:	https://easychair.org/publications/paper/ZxVn
	https://doi.org/10.29007/gd22

BibTeX entry

@inproceedings{CAOS2024:Using_automated_unsupervised_sensor,
  author    = {Julien Lebleu and Andries Pauwels and Ward Servaes and Wanne Wiersinga and Bruno Bonnechère},
  title     = {Using automated, unsupervised sensor based evaluation as a complement to PROMs to assess surgery outcomes},
  booktitle = {Proceedings of The 24th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery},
  editor    = {Joshua W Giles and Aziliz Guezou-Philippe},
  series    = {EPiC Series in Health Sciences},
  volume    = {7},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-5305},
  url       = {/publications/paper/ZxVn},
  doi       = {10.29007/gd22},
  pages     = {129-134},
  year      = {2024}}

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