ECG monitoring techniques using advanced signal recovery and arm worn sensors

WD Lynn, OJ Escalona, DJ McEneaney

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)
145 Downloads (Pure)

Abstract

Techniques for monitoring ambulatory patients have advanced greatly over the past 10 years. The advent of pocket computing, in the form of cellular phone technology, being one of the prime drivers. Until recently there was a great functional deficit in the performance of the average portable microprocessor and that which was used in the personal desktop computer. Today, smart phones have 1GHz processors and use multicore configurations. Memory has accelerated at a similar rate, with 128Gb flash memory being common place. The following paper discusses the viability of an arm worn `smart' device for monitoring cardiac dysrhythmia and or electrocardiographic dysmorphia. As there is particular interest from the medical community in the field of monitoring of paroxysmal atrial fibrillation; the proposed technology will be a front line diagnostic tool for primary care clinicians, allowing them to offer a non-surgical, long term monitor. Alternatively, the commercial possibilities of marketing a clinical quality, `smart band' cardiac monitor into the consumer space are immense. This paper deals with emerging digital signal processing techniques as well as discussing the underlying hardware requirements that may allow the full realisation of this new technology.
Original languageEnglish
Title of host publicationUnknown Host Publication
PublisherIEEE
Pages51-55
Number of pages5
DOIs
Publication statusPublished (in print/issue) - 15 Dec 2014
Event2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). - Belfast, UK
Duration: 15 Dec 2014 → …

Conference

Conference2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).
Period15/12/14 → …

Keywords

  • DSP
  • ECG
  • dry electrodes
  • dysrhythmia
  • long QT
  • long term monitor
  • body sensor networks
  • heart disease
  • electrocardiography
  • medical signal processing
  • patient monitoring
  • portable computers
  • portable instruments.

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