Imperial College London
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DrBennyLo

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

Visiting Reader
 
 
 
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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{Singh:2019:10.1007/978-3-030-01845-0_91,
author = {Singh, RK and Varghese, RJ and Liu, J and Zhang, Z and Lo, B},
doi = {10.1007/978-3-030-01845-0_91},
pages = {454--458},
publisher = {SPRINGER INTERNATIONAL PUBLISHING AG},
title = {A multi-sensor fusion approach for intention detection},
url = {http://dx.doi.org/10.1007/978-3-030-01845-0_91},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - For assistive devices to seamlessly and promptly assist users with activities of daily living (ADL), it is important to understand the user’s intention. Current assistive systems are mostly driven by unimodal sensory input which hinders their accuracy and responses. In this paper, we propose a context-aware sensor fusion framework to detect intention for assistive robotic devices which fuses information from a wearable video camera and wearable inertial measurement unit (IMU) sensors. A Naive Bayes classifier is used to predict the intent to move from IMU data and the object classification results from the video data. The proposed approach can achieve an accuracy of 85.2% in detecting movement intention.
AU  - Singh,RK
AU  - Varghese,RJ
AU  - Liu,J
AU  - Zhang,Z
AU  - Lo,B
DO  - 10.1007/978-3-030-01845-0_91
EP  - 458
PB  - SPRINGER INTERNATIONAL PUBLISHING AG
PY  - 2019///
SN  - 2195-3562
SP  - 454
TI  - A multi-sensor fusion approach for intention detection
UR  - http://dx.doi.org/10.1007/978-3-030-01845-0_91
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000614735000091&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://link.springer.com/chapter/10.1007%2F978-3-030-01845-0_91
UR  - http://hdl.handle.net/10044/1/90509
ER  -
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