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Wearable multimodal skin sensing for the diabetic foot

Wearable multimodal skin sensing for the diabetic foot
Wearable multimodal skin sensing for the diabetic foot
Ulceration of the diabetic foot is currently difficult to detect reliably in a timely manner causing undue suffering and cost. Current best practice is for daily monitoring by those living with diabetes coupled to scheduled monitoring by the incumbent care provider. Although some metrics have proven useful in the detection or prediction of ulceration, no single metric can currently be relied upon for diagnosis. We have developed a prototype multivariate extensible sensor platform with which we demonstrate the ability to gather acceleration, rotation, galvanic skin response, environmental temperature, humidity, force, skin temperature and bioimpedance signals in real time, for later analysis, utilising low cost Raspberry Pi and Arduino devices. We demonstrate the utility of the Raspberry Pi computer in research which is of particular interest to this issue of electronics - Raspberry Pi edition. We conclude that the hardware presented shows potential as an adaptable research tool capable of gathering synchronous data over multiple sensor modalities. This research tool will be utilised to optimise sensor selection, placement and algorithm development prior to translation into a sock, insole or platform diagnostic device at a later date. The combination of a number of clinically relevant parameters is expected to provide greater understanding of tissue state in the foot but requires further volunteer testing and analysis beyond the scope of this paper which will be reported in due course.
diabetes, skin, monitoring, multi-sensor, remote sensing, shoe, wearable, evaluation, test, raspberry pi, arduino
1-14
Coates, Jim
064f3710-e235-4a8a-b4bc-e4effd2b36f0
Chipperfield, Andrew
524269cd-5f30-4356-92d4-891c14c09340
Clough, Geraldine
9f19639e-a929-4976-ac35-259f9011c494
Coates, Jim
064f3710-e235-4a8a-b4bc-e4effd2b36f0
Chipperfield, Andrew
524269cd-5f30-4356-92d4-891c14c09340
Clough, Geraldine
9f19639e-a929-4976-ac35-259f9011c494

Coates, Jim, Chipperfield, Andrew and Clough, Geraldine (2016) Wearable multimodal skin sensing for the diabetic foot. [in special issue: Raspberry Pi Technology] Electronics, 5 (3), 1-14. (doi:10.3390/electronics5030045).

Record type: Article

Abstract

Ulceration of the diabetic foot is currently difficult to detect reliably in a timely manner causing undue suffering and cost. Current best practice is for daily monitoring by those living with diabetes coupled to scheduled monitoring by the incumbent care provider. Although some metrics have proven useful in the detection or prediction of ulceration, no single metric can currently be relied upon for diagnosis. We have developed a prototype multivariate extensible sensor platform with which we demonstrate the ability to gather acceleration, rotation, galvanic skin response, environmental temperature, humidity, force, skin temperature and bioimpedance signals in real time, for later analysis, utilising low cost Raspberry Pi and Arduino devices. We demonstrate the utility of the Raspberry Pi computer in research which is of particular interest to this issue of electronics - Raspberry Pi edition. We conclude that the hardware presented shows potential as an adaptable research tool capable of gathering synchronous data over multiple sensor modalities. This research tool will be utilised to optimise sensor selection, placement and algorithm development prior to translation into a sock, insole or platform diagnostic device at a later date. The combination of a number of clinically relevant parameters is expected to provide greater understanding of tissue state in the foot but requires further volunteer testing and analysis beyond the scope of this paper which will be reported in due course.

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More information

Accepted/In Press date: 4 July 2016
e-pub ahead of print date: 28 July 2016
Published date: 28 July 2016
Keywords: diabetes, skin, monitoring, multi-sensor, remote sensing, shoe, wearable, evaluation, test, raspberry pi, arduino
Organisations: Faculty of Medicine, Bioengineering Group

Identifiers

Local EPrints ID: 397879
URI: http://eprints.soton.ac.uk/id/eprint/397879
PURE UUID: a8aeca4c-fa92-4cce-af7e-61dccf264ca1
ORCID for Andrew Chipperfield: ORCID iD orcid.org/0000-0002-3026-9890
ORCID for Geraldine Clough: ORCID iD orcid.org/0000-0002-6226-8964

Catalogue record

Date deposited: 11 Jul 2016 10:29
Last modified: 07 Oct 2020 01:48

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Author: Jim Coates

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