A Mobile Crowd Sensing Application for Hypertensive Patients
Mobile crowd sensing (MCS) is an application that collects data from a network of conscientious volunteers and implements it for the common or personal benefit. This contribution proposes an implementation that collects the data from hypertensive patients, thus creating an experimental database usin...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-01-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/19/2/400 |
| _version_ | 1818013857612824576 |
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| author | Slađana Jovanović Milan Jovanović Tamara Škorić Stevan Jokić Branislav Milovanović Konstantinos Katzis Dragana Bajić |
| author_facet | Slađana Jovanović Milan Jovanović Tamara Škorić Stevan Jokić Branislav Milovanović Konstantinos Katzis Dragana Bajić |
| author_sort | Slađana Jovanović |
| collection | DOAJ |
| description | Mobile crowd sensing (MCS) is an application that collects data from a network of conscientious volunteers and implements it for the common or personal benefit. This contribution proposes an implementation that collects the data from hypertensive patients, thus creating an experimental database using the cloud service Platform as a Service (PaaS). The challenge is to perform the analysis without the main diagnostic feature for hypertension—the blood pressure. The other problems consider the data reliability in an environment full of artifacts and with limited bandwidth and battery resources. In order to motivate the MCS volunteers, a feedback about the patient’s current status is created, provided by the means of machine-learning (ML) techniques. Two techniques are investigated and the Random Forest algorithm yielded the best results. The proposed platform, with slight modifications, can be adapted to the patients with other cardiovascular problems. |
| first_indexed | 2024-04-14T06:38:26Z |
| format | Article |
| id | doaj.art-6d0203e4b0824757a7837b4d86ef357c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T06:38:26Z |
| publishDate | 2019-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-6d0203e4b0824757a7837b4d86ef357c2022-12-22T02:07:24ZengMDPI AGSensors1424-82202019-01-0119240010.3390/s19020400s19020400A Mobile Crowd Sensing Application for Hypertensive PatientsSlađana Jovanović0Milan Jovanović1Tamara Škorić2Stevan Jokić3Branislav Milovanović4Konstantinos Katzis5Dragana Bajić6Telekom Srbija A.D. Takovska 2, Belgrade 11000, SerbiaEndava, Bulevar Milutina Milankovića 11, Belgrade 11000, SerbiaFaculty of Technical Sciences, University of Novi Sad, Trg. D. Obradovića 6, Novi Sad 21000, SerbiaSvezdrav Rešenja LLC, Đenerala Draže 44, Klenje 15357, SerbiaFaculty of Medicine, University of Belgrade, Dr Subotića 8, Belgrade 11000, SerbiaDepartment of Computer Science and Engineering, European University Cyprus, Diogenis Str 6, Nicosia 1516, CyprusFaculty of Technical Sciences, University of Novi Sad, Trg. D. Obradovića 6, Novi Sad 21000, SerbiaMobile crowd sensing (MCS) is an application that collects data from a network of conscientious volunteers and implements it for the common or personal benefit. This contribution proposes an implementation that collects the data from hypertensive patients, thus creating an experimental database using the cloud service Platform as a Service (PaaS). The challenge is to perform the analysis without the main diagnostic feature for hypertension—the blood pressure. The other problems consider the data reliability in an environment full of artifacts and with limited bandwidth and battery resources. In order to motivate the MCS volunteers, a feedback about the patient’s current status is created, provided by the means of machine-learning (ML) techniques. Two techniques are investigated and the Random Forest algorithm yielded the best results. The proposed platform, with slight modifications, can be adapted to the patients with other cardiovascular problems.http://www.mdpi.com/1424-8220/19/2/400mobile crowd sensingInternet of Everythinghypertensionquality of informationmachine learning |
| spellingShingle | Slađana Jovanović Milan Jovanović Tamara Škorić Stevan Jokić Branislav Milovanović Konstantinos Katzis Dragana Bajić A Mobile Crowd Sensing Application for Hypertensive Patients Sensors mobile crowd sensing Internet of Everything hypertension quality of information machine learning |
| title | A Mobile Crowd Sensing Application for Hypertensive Patients |
| title_full | A Mobile Crowd Sensing Application for Hypertensive Patients |
| title_fullStr | A Mobile Crowd Sensing Application for Hypertensive Patients |
| title_full_unstemmed | A Mobile Crowd Sensing Application for Hypertensive Patients |
| title_short | A Mobile Crowd Sensing Application for Hypertensive Patients |
| title_sort | mobile crowd sensing application for hypertensive patients |
| topic | mobile crowd sensing Internet of Everything hypertension quality of information machine learning |
| url | http://www.mdpi.com/1424-8220/19/2/400 |
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