Imperial College London

Dr Guangwei Chen

Faculty of EngineeringDepartment of Computing

Research Associate
 
 
 
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Contact

 

+44 (0)20 7594 0991sorsby Website

 
 
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Location

 

William Penney LaboratorySouth Kensington Campus

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Summary

 

Summary

Dr Guangwei Chen is a research associate in the Data Science Institute at Imperial College London. Dr Chen is one of the main inventors of the AcuPebble wearable respiratory monitoring system. His research interests are in the area of biomedical signal processing, algorithms and low power wearable system design. Typical applications are in respiration monitoring, brainwave monitoring, heart monitoring and mHealth self-diagnosis tools. After the success of the AcuPebble development, Dr Chen's research focuses on transfer learning on physiological data which converts the generic machine learned models to the more accurate personalised models with the use of individual personal data.

Dr Chen received his undergraduate degree (BEng) in Electronic Systems Engineering from University of Manchester in 2006 and master degree (MSc) in Analogue and Digital Integrated Circuit Design from Imperial College in 2007. Dr Chen worked as a research assistant in the Electrical and Electronic Engineering at Imperial College since 2007 and later become research associate after the completion of his PhD from Imperial College London in 2016 with the thesis title "Towards a Truly Wearable, Non-invasive Respiration Monitoring System".

Publications

Journals

Chen G, Imtiaz SA, Aguilar-Pelaez E, et al., 2015, Algorithm for heart rate extraction in a novel wearable acoustic sensor, Healthcare Technology Letters, Vol:2, ISSN:2053-3713, Pages:28-33

Conference

Chen G, Rodriguez Villegas E, System-level design trade-offs for truly wearable wireless medical devices, The Engineering in Medicine and Biology Conference (EMBC)

Chen G, de la Cruz I, Rodriguez Villegas E, Automatic lung tidal volumes estimation from tracheal sounds, Engineering in Medicine and Biology Society (EMBC)

Chen G, Bowyer SA, Rodriguez-Villegas E, 2016, Low-Complexity Prediction of Frequency-Rich Biosignals for Lossless Compression in Wearable Technologies, 38th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), IEEE, Pages:3535-3538, ISSN:1557-170X

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