Effectiveness of Mobile Electrocardiogram in Healthcare: From Mobile Application and Development to Community Reaction

Ahmad Kassem, Umut Ozan Yıldırım, Kadir Anıl Turğut, Uffe Kock Wiil, Tansel Özyer, Reda Alhajj

Publikation: Bidrag til bog/antologi/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

Resumé

Chronic diseases such as heart and blood vessels are considered among the most common and serious reasons of mortality in the world. In Europe alone, over four million deaths a year (45% of all deaths) are caused by heart diseases [1]. In addition, chronic diseases are responsible for 70 % of United States deaths, and account for more than 75% of annual United States medical care cost [2]. For instance, Cardio Vascular Diseases (CVD) are considered the main cause for around 14.3% of total deaths in Denmark 5 , and it is the main cause for over 45% of the total death in Lebanon 6 . It is too costly to keep CVD patients under control locally within the vicinity of a healthcare unit. Thus, researchers recently started to realize the need for automated monitoring in health systems that are expected to reduce the overall death rate and cost associated with monitoring of patients. However, a general monitoring health system will not cover all diseases at once. Therefore, there is a pushing necessity for monitoring health systems which are dedicated to specific health cases. To contribute to the ongoing efforts, this work develops an automated system which could be customized for various chronic diseases. A mobile application based solution is proposed. Further, the work concentrates on CVD by conducting a survey in Lebanon to investigate the acceptance and awareness of ECG for remote monitoring of patients. The results are promising and reflect how specialists are aware of the need to utilize the rapid development in technology combined with the widespread usage of mobile phone which may be used as the main device to guarantee 24/7 communication link for ECG. Adopting ECG in the healthcare system will allow for capturing some valuable data which could guide the development of a recommendation system. This will issue necessary alerts to specialists and guidance to patients and their careers so that specialists could attend to the case on timely basis and patients with their careers could follow the recommendations to keep the case under control until the specialist becomes available. Finally, a secure forum based communication system will be developed to allow patients to share their experience and specialists to provide consultancy and guidance on demand.

OriginalsprogEngelsk
TitelProceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017
RedaktørerJana Diesner, Elena Ferrari, Guandong Xu
ForlagAssociation for Computing Machinery
Publikationsdato31. jul. 2017
Sider896-903
ISBN (Trykt)978-1-4503-4993-2
ISBN (Elektronisk)9781450349932
DOI
StatusUdgivet - 31. jul. 2017
Begivenhed2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining - Sydney, Australien
Varighed: 31. jul. 20173. aug. 2017

Konference

Konference2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
LandAustralien
BySydney
Periode31/07/201703/08/2017

Fingeraftryk

Electrocardiography
Health
Monitoring
Recommender systems
Blood vessels
Mobile phones
Health care
Telecommunication links
Costs
Communication systems

Citer dette

Kassem, A., Yıldırım, U. O., Turğut, K. A., Wiil, U. K., Özyer, T., & Alhajj, R. (2017). Effectiveness of Mobile Electrocardiogram in Healthcare: From Mobile Application and Development to Community Reaction. I J. Diesner, E. Ferrari, & G. Xu (red.), Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017 (s. 896-903). Association for Computing Machinery. https://doi.org/10.1145/3110025.3120985
Kassem, Ahmad ; Yıldırım, Umut Ozan ; Turğut, Kadir Anıl ; Wiil, Uffe Kock ; Özyer, Tansel ; Alhajj, Reda. / Effectiveness of Mobile Electrocardiogram in Healthcare : From Mobile Application and Development to Community Reaction. Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017. red. / Jana Diesner ; Elena Ferrari ; Guandong Xu. Association for Computing Machinery, 2017. s. 896-903
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abstract = "Chronic diseases such as heart and blood vessels are considered among the most common and serious reasons of mortality in the world. In Europe alone, over four million deaths a year (45{\%} of all deaths) are caused by heart diseases [1]. In addition, chronic diseases are responsible for 70 {\%} of United States deaths, and account for more than 75{\%} of annual United States medical care cost [2]. For instance, Cardio Vascular Diseases (CVD) are considered the main cause for around 14.3{\%} of total deaths in Denmark 5 , and it is the main cause for over 45{\%} of the total death in Lebanon 6 . It is too costly to keep CVD patients under control locally within the vicinity of a healthcare unit. Thus, researchers recently started to realize the need for automated monitoring in health systems that are expected to reduce the overall death rate and cost associated with monitoring of patients. However, a general monitoring health system will not cover all diseases at once. Therefore, there is a pushing necessity for monitoring health systems which are dedicated to specific health cases. To contribute to the ongoing efforts, this work develops an automated system which could be customized for various chronic diseases. A mobile application based solution is proposed. Further, the work concentrates on CVD by conducting a survey in Lebanon to investigate the acceptance and awareness of ECG for remote monitoring of patients. The results are promising and reflect how specialists are aware of the need to utilize the rapid development in technology combined with the widespread usage of mobile phone which may be used as the main device to guarantee 24/7 communication link for ECG. Adopting ECG in the healthcare system will allow for capturing some valuable data which could guide the development of a recommendation system. This will issue necessary alerts to specialists and guidance to patients and their careers so that specialists could attend to the case on timely basis and patients with their careers could follow the recommendations to keep the case under control until the specialist becomes available. Finally, a secure forum based communication system will be developed to allow patients to share their experience and specialists to provide consultancy and guidance on demand.",
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Kassem, A, Yıldırım, UO, Turğut, KA, Wiil, UK, Özyer, T & Alhajj, R 2017, Effectiveness of Mobile Electrocardiogram in Healthcare: From Mobile Application and Development to Community Reaction. i J Diesner, E Ferrari & G Xu (red), Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017. Association for Computing Machinery, s. 896-903, 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Sydney, Australien, 31/07/2017. https://doi.org/10.1145/3110025.3120985

Effectiveness of Mobile Electrocardiogram in Healthcare : From Mobile Application and Development to Community Reaction. / Kassem, Ahmad; Yıldırım, Umut Ozan; Turğut, Kadir Anıl; Wiil, Uffe Kock; Özyer, Tansel; Alhajj, Reda.

Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017. red. / Jana Diesner; Elena Ferrari; Guandong Xu. Association for Computing Machinery, 2017. s. 896-903.

Publikation: Bidrag til bog/antologi/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

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Kassem A, Yıldırım UO, Turğut KA, Wiil UK, Özyer T, Alhajj R. Effectiveness of Mobile Electrocardiogram in Healthcare: From Mobile Application and Development to Community Reaction. I Diesner J, Ferrari E, Xu G, red., Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017. Association for Computing Machinery. 2017. s. 896-903 https://doi.org/10.1145/3110025.3120985