Imperial College London
Alternate

Mr Colin D Bicknell BM MD FRCS

Faculty of Medicine, Department of Surgery & Cancer

Clinical Reader in Vascular Surgery
 
 
 
//

Contact

 

+44 (0)20 3312 6428colin.bicknell

 
 
//

Location

 

1020Queen Elizabeth the Queen Mother Wing (QEQM)St Mary's Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Currie:2019:10.1007/s11548-019-01918-0,
author = {Currie, J and Bond, RR and McCullagh, P and Black, P and Finlay, DD and Gallagher, S and Kearney, P and Peace, A and Stoyanov, D and Bicknell, CD and Leslie, S and Gallagher, AG},
doi = {10.1007/s11548-019-01918-0},
journal = {International Journal of Computer Assisted Radiology and Surgery},
pages = {645--657},
title = {Wearable technology-based metrics for predicting operator performance during cardiac catheterisation},
url = {http://dx.doi.org/10.1007/s11548-019-01918-0},
volume = {14},
year = {2019}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - IntroductionUnobtrusive metrics that can auto-assess performance during clinical procedures are of value. Three approaches to deriving wearable technology-based metrics are explored: (1) eye tracking, (2) psychophysiological measurements [e.g. electrodermal activity (EDA)] and (3) arm and hand movement via accelerometry. We also measure attentional capacity by tasking the operator with an additional task to track an unrelated object during the procedure.MethodsTwo aspects of performance are measured: (1) using eye gaze and psychophysiology metrics and (2) measuring attentional capacity via an additional unrelated task (to monitor a visual stimulus/playing cards). The aim was to identify metrics that can be used to automatically discriminate between levels of performance or at least between novices and experts. The study was conducted using two groups: (1) novice operators and (2) expert operators. Both groups made two attempts at a coronary angiography procedure using a full-physics virtual reality simulator. Participants wore eye tracking glasses and an E4 wearable wristband. Areas of interest were defined to track visual attention on display screens, including: (1) X-ray, (2) vital signs, (3) instruments and (4) the stimulus screen (for measuring attentional capacity).ResultsExperts provided greater dwell time (63% vs 42%, p = 0.03) and fixations (50% vs 34%, p = 0.04) on display screens. They also provided greater dwell time (11% vs 5%, p = 0.006) and fixations (9% vs 4%, p = 0.007) when selecting instruments. The experts’ performance for tracking the unrelated object during the visual stimulus task negatively correlated with total errors (r = − 0.95, p = 0.0009). Experts also had a higher standard deviation of EDA (2.52 µS vs 0.89 µS, p = 0.04).ConclusionsEye tracking metrics may help discriminate between a novice and expert operator
AU  - Currie,J
AU  - Bond,RR
AU  - McCullagh,P
AU  - Black,P
AU  - Finlay,DD
AU  - Gallagher,S
AU  - Kearney,P
AU  - Peace,A
AU  - Stoyanov,D
AU  - Bicknell,CD
AU  - Leslie,S
AU  - Gallagher,AG
DO  - 10.1007/s11548-019-01918-0
EP  - 657
PY  - 2019///
SN  - 1861-6410
SP  - 645
TI  - Wearable technology-based metrics for predicting operator performance during cardiac catheterisation
T2  - International Journal of Computer Assisted Radiology and Surgery
UR  - http://dx.doi.org/10.1007/s11548-019-01918-0
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000461349600008&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://link.springer.com/article/10.1007%2Fs11548-019-01918-0
UR  - http://hdl.handle.net/10044/1/85964
VL  - 14
ER  -
Download