Design and development of the medFit app: A mobile application for cardiovascular disease rehabilitation

Ghanashyama Prabhu; Jogile Kuklyte; Leonardo Gualano; Kaushik Venkataraman; Amin Ahmadi; Orlaith Duff; Deirdre Walsh; Catherine Woods; Noel E. O’Connor; Kieran Moran

doi:10.1007/978-3-319-98551-0_3

Design and development of the medFit app: A mobile application for cardiovascular disease rehabilitation

Ghanashyama Prabhu, Jogile Kuklyte, Leonardo Gualano, Kaushik Venkataraman, Amin Ahmadi, Orlaith Duff, Deirdre Walsh, Catherine Woods, Noel E. O’Connor, Kieran Moran

Dublin City University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Rehabilitation from cardiovascular disease (CVD) usually requires lifestyle changes, especially an increase in exercise and physical activity. However, uptake and adherence to exercise is low for community-based programmes. We propose a mobile application that allows users to choose the type of exercise and compete it at a convenient time in the comfort of their own home. Grounded in a behaviour change framework, the application provides feedback and encouragement to continue exercising and to improve on previous results. The application also utilizes wearable wireless technologies in order to provide highly personalized feedback. The application can accurately detect if a specific exercise is being done, and count the associated number of repetitions utilizing accelerometer or gyroscope signals Machine learning models are employed to recognize individual local muscular endurance (LME) exercises, achieving overall accuracy of more than 98%. This technology allows providing a near real-time personalized feedback which mimics the feedback that the user might expect from an instructor. This is provided to motivate users to continue the recovery process.

Original language	English
Title of host publication	Wireless Mobile Communication and Healthcare - 7th International Conference, MobiHealth 2017, Proceedings
Editors	Amir M. Rahmani, Nima TaheriNejad, Paolo Perego
Publisher	Springer Verlag
Pages	20-28
Number of pages	9
ISBN (Print)	9783319985503
DOIs	https://doi.org/10.1007/978-3-319-98551-0_3
Publication status	Published - 2018
Event	7th International Conference on Wireless Mobile Communication and Healthcare, MobiHealth 2017 - Vienna, Austria Duration: 14 Nov 2017 → 15 Nov 2017

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume	247
ISSN (Print)	1867-8211

Conference

Conference	7th International Conference on Wireless Mobile Communication and Healthcare, MobiHealth 2017
Country/Territory	Austria
City	Vienna
Period	14/11/17 → 15/11/17

Keywords

Cardiovascular disease
Mobile application
Repetition counting
Support vector machine
Wearable sensors

UN SDGs

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

Access to Document

10.1007/978-3-319-98551-0_3

Cite this

Prabhu, G., Kuklyte, J., Gualano, L., Venkataraman, K., Ahmadi, A., Duff, O., Walsh, D., Woods, C., O’Connor, N. E., & Moran, K. (2018). Design and development of the medFit app: A mobile application for cardiovascular disease rehabilitation. In A. M. Rahmani, N. TaheriNejad, & P. Perego (Eds.), Wireless Mobile Communication and Healthcare - 7th International Conference, MobiHealth 2017, Proceedings (pp. 20-28). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 247). Springer Verlag. https://doi.org/10.1007/978-3-319-98551-0_3

Prabhu, Ghanashyama ; Kuklyte, Jogile ; Gualano, Leonardo et al. / Design and development of the medFit app : A mobile application for cardiovascular disease rehabilitation. Wireless Mobile Communication and Healthcare - 7th International Conference, MobiHealth 2017, Proceedings. editor / Amir M. Rahmani ; Nima TaheriNejad ; Paolo Perego. Springer Verlag, 2018. pp. 20-28 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST).

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title = "Design and development of the medFit app: A mobile application for cardiovascular disease rehabilitation",

abstract = "Rehabilitation from cardiovascular disease (CVD) usually requires lifestyle changes, especially an increase in exercise and physical activity. However, uptake and adherence to exercise is low for community-based programmes. We propose a mobile application that allows users to choose the type of exercise and compete it at a convenient time in the comfort of their own home. Grounded in a behaviour change framework, the application provides feedback and encouragement to continue exercising and to improve on previous results. The application also utilizes wearable wireless technologies in order to provide highly personalized feedback. The application can accurately detect if a specific exercise is being done, and count the associated number of repetitions utilizing accelerometer or gyroscope signals Machine learning models are employed to recognize individual local muscular endurance (LME) exercises, achieving overall accuracy of more than 98%. This technology allows providing a near real-time personalized feedback which mimics the feedback that the user might expect from an instructor. This is provided to motivate users to continue the recovery process.",

keywords = "Cardiovascular disease, Mobile application, Repetition counting, Support vector machine, Wearable sensors",

author = "Ghanashyama Prabhu and Jogile Kuklyte and Leonardo Gualano and Kaushik Venkataraman and Amin Ahmadi and Orlaith Duff and Deirdre Walsh and Catherine Woods and O{\textquoteright}Connor, {Noel E.} and Kieran Moran",

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doi = "10.1007/978-3-319-98551-0_3",

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Prabhu, G, Kuklyte, J, Gualano, L, Venkataraman, K, Ahmadi, A, Duff, O, Walsh, D, Woods, C, O’Connor, NE & Moran, K 2018, Design and development of the medFit app: A mobile application for cardiovascular disease rehabilitation. in AM Rahmani, N TaheriNejad & P Perego (eds), Wireless Mobile Communication and Healthcare - 7th International Conference, MobiHealth 2017, Proceedings. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 247, Springer Verlag, pp. 20-28, 7th International Conference on Wireless Mobile Communication and Healthcare, MobiHealth 2017, Vienna, Austria, 14/11/17. https://doi.org/10.1007/978-3-319-98551-0_3

Design and development of the medFit app: A mobile application for cardiovascular disease rehabilitation. / Prabhu, Ghanashyama; Kuklyte, Jogile; Gualano, Leonardo et al.
Wireless Mobile Communication and Healthcare - 7th International Conference, MobiHealth 2017, Proceedings. ed. / Amir M. Rahmani; Nima TaheriNejad; Paolo Perego. Springer Verlag, 2018. p. 20-28 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 247).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Kuklyte, Jogile

AU - Gualano, Leonardo

AU - Venkataraman, Kaushik

AU - Ahmadi, Amin

AU - Duff, Orlaith

AU - Walsh, Deirdre

AU - Woods, Catherine

AU - O’Connor, Noel E.

AU - Moran, Kieran

N1 - Publisher Copyright: © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018.

PY - 2018

Y1 - 2018

N2 - Rehabilitation from cardiovascular disease (CVD) usually requires lifestyle changes, especially an increase in exercise and physical activity. However, uptake and adherence to exercise is low for community-based programmes. We propose a mobile application that allows users to choose the type of exercise and compete it at a convenient time in the comfort of their own home. Grounded in a behaviour change framework, the application provides feedback and encouragement to continue exercising and to improve on previous results. The application also utilizes wearable wireless technologies in order to provide highly personalized feedback. The application can accurately detect if a specific exercise is being done, and count the associated number of repetitions utilizing accelerometer or gyroscope signals Machine learning models are employed to recognize individual local muscular endurance (LME) exercises, achieving overall accuracy of more than 98%. This technology allows providing a near real-time personalized feedback which mimics the feedback that the user might expect from an instructor. This is provided to motivate users to continue the recovery process.

AB - Rehabilitation from cardiovascular disease (CVD) usually requires lifestyle changes, especially an increase in exercise and physical activity. However, uptake and adherence to exercise is low for community-based programmes. We propose a mobile application that allows users to choose the type of exercise and compete it at a convenient time in the comfort of their own home. Grounded in a behaviour change framework, the application provides feedback and encouragement to continue exercising and to improve on previous results. The application also utilizes wearable wireless technologies in order to provide highly personalized feedback. The application can accurately detect if a specific exercise is being done, and count the associated number of repetitions utilizing accelerometer or gyroscope signals Machine learning models are employed to recognize individual local muscular endurance (LME) exercises, achieving overall accuracy of more than 98%. This technology allows providing a near real-time personalized feedback which mimics the feedback that the user might expect from an instructor. This is provided to motivate users to continue the recovery process.

KW - Cardiovascular disease

KW - Mobile application

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Prabhu G, Kuklyte J, Gualano L, Venkataraman K, Ahmadi A, Duff O et al. Design and development of the medFit app: A mobile application for cardiovascular disease rehabilitation. In Rahmani AM, TaheriNejad N, Perego P, editors, Wireless Mobile Communication and Healthcare - 7th International Conference, MobiHealth 2017, Proceedings. Springer Verlag. 2018. p. 20-28. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST). doi: 10.1007/978-3-319-98551-0_3

Design and development of the medFit app: A mobile application for cardiovascular disease rehabilitation

Abstract

Publication series

Conference

Keywords

UN SDGs

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