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Real-time visualisation and analysis of clinicians’ performance during alpation in physical examinations

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Title: Real-time visualisation and analysis of clinicians’ performance during alpation in physical examinations
Authors: Granados, A
Low-Beer, N
Higham, J
Kneebone, R
Bello, F
Item Type: Journal Article
Abstract: Objective: Motivated by the fact that palpation skills are challenging to learn and teach, particularly during Digital Rectal Examinations (DRE), and the lack of understanding of what constitutes adequate performance, we present a visualization and analysis system that uses small position and pressure sensors located on the examining finger, allowing the quantitative analysis of duration, steps, and pressure applied. Methods: The system is first described, followed by an experimental study of 20 experts from four clinical specialties performing ten DREs each on a benchtop model using the proposed system. Analysis of the constitutive steps was conducted to improve understanding of the examination. A Markov model representing executed tasks and analysis of pressure applied is also introduced. Results: The proposed system successfully allowed the visualization and analysis during the experimental study. General practitioners and nurses were found to execute more tasks compared to urologists and colorectal surgeons. Urologists executed the least number of tasks and were the most consistent group compared to others. Conclusion: The ability to “see through” allowed us to better characterize the performance of experts when conducting a DRE on a benchtop model, comparing the performance of relevant specialties, and studying executed tasks and the pressure applied. The Markov model presented summarizes task execution of experts and could be used to compare the performance of novices against that of experts. Significance: This approach allows for the analysis of performance based on continuous sensor data recording that can be easily extended to real subjects and other types of physical examinations.
Issue Date: 1-Sep-2018
Date of Acceptance: 24-Nov-2017
URI: http://hdl.handle.net/10044/1/54475
DOI: https://dx.doi.org/10.1109/TBME.2017.2780982
ISSN: 0018-9294
Publisher: Institute of Electrical and Electronics Engineers
Start Page: 2042
End Page: 2051
Journal / Book Title: IEEE Transactions on Biomedical Engineering
Volume: 65
Issue: 9
Copyright Statement: © 2018 IEEE. This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/
Sponsor/Funder: Imperial College Healthcare NHS Trust
Imperial College Healthcare NHS Trust
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (E
Health Education North West London
Economic & Social Research Council (ESRC)
Imperial College Healthcare Charity
Funder's Grant Number: H0019097
Funder to provide
Keywords: Science & Technology
Engineering, Biomedical
Digital rectal examination
quantitative analysis
0903 Biomedical Engineering
0906 Electrical And Electronic Engineering
0801 Artificial Intelligence And Image Processing
Biomedical Engineering
Publication Status: Published
Online Publication Date: 2018-03-28
Appears in Collections:Department of Surgery and Cancer