DocumentCode
3715871
Title
Opportunities and challenges for ultra low power signal processing in wearable healthcare
Author
Alexander J. Casson
Author_Institution
School of Electrical and Electronic Engineering, The University of Manchester, UK
fYear
2015
Firstpage
424
Lastpage
428
Abstract
Wearable devices are starting to revolutionise healthcare by allowing the unobtrusive and long term monitoring of a range of body parameters. Embedding more advanced signal processing algorithms into the wearable itself can: reduce system power consumption; increase device functionality; and enable closed-loop recording-stimulation with minimal latency; amongst other benefits. The design challenge is in realising algorithms within the very limited power budgets available. Wearable algorithms are now emerging to answer this challenge. Using a new review, and examples from a case study on EEG analysis, this article overviews the state-of-the-art in wearable algorithms. It demonstrates the opportunities and challenges, highlighting the open challenge of performance assessment and measuring variability.
Keywords
"Signal processing algorithms","Algorithm design and analysis","Signal processing","Electrocardiography","Biomedical monitoring","Power demand","Electroencephalography"
Publisher
ieee
Conference_Titel
Signal Processing Conference (EUSIPCO), 2015 23rd European
Electronic_ISBN
2076-1465
Type
conf
DOI
10.1109/EUSIPCO.2015.7362418
Filename
7362418
Link To Document