Imperial College London
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DrBennyLo

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

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Contact

 

+44 (0)20 7594 0806benny.lo Website

 
 
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Location

 

Bessemer BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Chen:2019:10.1109/BSN.2019.8771090,
author = {Chen, S and Kang, L and Lu, Y and Wang, N and Lu, Y and Lo, B and Yang, G-Z},
doi = {10.1109/BSN.2019.8771090},
pages = {1--4},
publisher = {IEEE},
title = {Discriminative information added by wearable sensors for early screening - a case study on diabetic peripheral neuropathy},
url = {http://dx.doi.org/10.1109/BSN.2019.8771090},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Wearable inertial sensors have demonstrated their potential to screen for various neuropathies and neurological disorders. Most such research has been based on classification algorithms that differentiate the control group from the pathological group, using biomarkers extracted from wearable data as predictors. However, such methods often lack quantitative evaluation of how much information provided by the wearable biomarkers contributes to the overall prediction. Despite promising results from internal cross validation, their utility in clinical practice remains unclear. In this paper, we highlight in a case study - early screening for diabetic peripheral neuropathy (DPN) - evaluation methods for quantifying the contribution of wearable inertial sensors. Using a quick-to-deploy wearable sensor system, we collected 106 in-hospital diabetic patients' gait data and developed logistic regression models to predict the risk of a diabetic patient having DPN. Adopting various metrics, we evaluated the discriminative information added by gait biomarkers and how much it improved screening. The results show that the proposed wearable system added useful information significantly to the existing clinical standards, and boosted the C-index significantly from 0.75 to 0.84, surpassing the current survey-based screening methods used in clinics.
AU  - Chen,S
AU  - Kang,L
AU  - Lu,Y
AU  - Wang,N
AU  - Lu,Y
AU  - Lo,B
AU  - Yang,G-Z
DO  - 10.1109/BSN.2019.8771090
EP  - 4
PB  - IEEE
PY  - 2019///
SN  - 2376-8886
SP  - 1
TI  - Discriminative information added by wearable sensors for early screening - a case study on diabetic peripheral neuropathy
UR  - http://dx.doi.org/10.1109/BSN.2019.8771090
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000492872400030&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://ieeexplore.ieee.org/document/8771090
UR  - http://hdl.handle.net/10044/1/75185
ER  -
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