Personal ECG Devices: How Will Healthcare Systems Cope? A Single Centre Case Study

Rob Brisk; RR Bond; D Finlay; David McEneaney

Personal ECG Devices: How Will Healthcare Systems Cope? A Single Centre Case Study

Rob Brisk
, RR Bond
, D Finlay
, David McEneaney

Cardiovascular Research Unit, Craigavon Area Hospital

Research output: Contribution to conference › Paper › peer-review

97 Downloads (Pure)

Abstract

The uptake of personal ECG devices is poised to
explode in coming years. This review considers the
potential impact of this on the cardiology department of an
NHS teaching trust in the UK. The authors conclude that
such devices may substantially increase the workload of a
service already under significant pressure, with unclear
benefit to patients. Potential solutions to this issue include
novel algorithms (perhaps deep learning) to minimize false
positive results.

Original language	English
Publication status	Published (in print/issue) - 9 Sept 2019
Event	Computing in Cardiology - Matrix, Biopolis, Singapore Duration: 8 Sept 2019 → 11 Sept 2019 Conference number: 46 http://www.cinc.org

Conference

Conference	Computing in Cardiology
Abbreviated title	CinC 2019
Country/Territory	Singapore
City	Biopolis
Period	8/09/19 → 11/09/19
Internet address	http://www.cinc.org

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

ECG
Wearable
health monitoring
Personal devices
ECG monitoring

Access to Document

paperAuthor Accepted Manuscript, 315 KB

Cite this

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title = "Personal ECG Devices: How Will Healthcare Systems Cope? A Single Centre Case Study",

abstract = "The uptake of personal ECG devices is poised to explode in coming years. This review considers the potential impact of this on the cardiology department of an NHS teaching trust in the UK. The authors conclude that such devices may substantially increase the workload of a service already under significant pressure, with unclear benefit to patients. Potential solutions to this issue include novel algorithms (perhaps deep learning) to minimize false positive results.",

keywords = "ECG, Wearable, health monitoring, Personal devices, ECG monitoring",

author = "Rob Brisk and RR Bond and D Finlay and David McEneaney",

year = "2019",

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note = "Computing in Cardiology, CinC 2019 ; Conference date: 08-09-2019 Through 11-09-2019",

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T1 - Personal ECG Devices: How Will Healthcare Systems Cope? A Single Centre Case Study

AU - Brisk, Rob

AU - Bond, RR

AU - Finlay, D

AU - McEneaney, David

N1 - Conference code: 46

PY - 2019/9/9

Y1 - 2019/9/9

N2 - The uptake of personal ECG devices is poised to explode in coming years. This review considers the potential impact of this on the cardiology department of an NHS teaching trust in the UK. The authors conclude that such devices may substantially increase the workload of a service already under significant pressure, with unclear benefit to patients. Potential solutions to this issue include novel algorithms (perhaps deep learning) to minimize false positive results.

AB - The uptake of personal ECG devices is poised to explode in coming years. This review considers the potential impact of this on the cardiology department of an NHS teaching trust in the UK. The authors conclude that such devices may substantially increase the workload of a service already under significant pressure, with unclear benefit to patients. Potential solutions to this issue include novel algorithms (perhaps deep learning) to minimize false positive results.

KW - ECG

KW - Wearable

KW - health monitoring

KW - Personal devices

KW - ECG monitoring

UR - http://www.cinc.org/2019/Program/accepted/335_CinCFinalPDF.pdf

UR - http://cinc2019.org/

UR - http://www.cinc.org/2019/Program/accepted/accepted.html

M3 - Paper

T2 - Computing in Cardiology

Y2 - 8 September 2019 through 11 September 2019

ER -

Personal ECG Devices: How Will Healthcare Systems Cope? A Single Centre Case Study

Abstract

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Towards broader application of deep learning methods to the automated analysis of electrocardiograms

Cite this

Personal ECG Devices: How Will Healthcare Systems Cope? A Single Centre Case Study

Abstract

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Student theses

Towards broader application of deep learning methods to the automated analysis of electrocardiograms

Cite this