Motion-Tracking Machines and Sensors: Advancing Education Technology.
education
motion analysis
segmentation
Journal
Journal of cardiothoracic and vascular anesthesia
ISSN: 1532-8422
Titre abrégé: J Cardiothorac Vasc Anesth
Pays: United States
ID NLM: 9110208
Informations de publication
Date de publication:
01 2022
01 2022
Historique:
received:
17
05
2021
revised:
09
07
2021
accepted:
19
07
2021
pubmed:
24
9
2021
medline:
1
2
2022
entrez:
23
9
2021
Statut:
ppublish
Résumé
Graduate medical education is predominantly based on a time-based apprenticeship model, with implied acquisition of proficiency after a pre-set amount of clinical exposure. While motion metrics have been used previously to measure skill performance indicators, these assessments have largely been performed on a summative scale to describe the performance of complete tasks or procedures. By segmenting performances of interest and assessing the essential elements individually, a more comprehensive understanding of the aspects in need of improvement for a learner can be obtained. The purpose of this review is to discuss technologies applicable to motion tracking, their benefits and limitations, approaches to data processing, and potential applications based on recent improvements in this technology. Objective analysis of motion metrics may improve educational standards of learning and efficiency by both standardizing the feedback process for trainees and reducing the volume of instructors required to facilitate practice sessions. With rigorous validation and standardization, motion metric assessment may also prove useful to demonstrate competency in technical procedures as part of a comprehensive certification process.
Identifiants
pubmed: 34551885
pii: S1053-0770(21)00617-0
doi: 10.1053/j.jvca.2021.07.036
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
303-308Informations de copyright
Copyright © 2021 Elsevier Inc. All rights reserved.