TY  - JOUR
PB  - Springer
SN  - 21945357
EP  - 143
AV  - none
TI  - Atrial Fibrillation for Stroke Detection
SP  - 136
N1  - cited By 0; Conference of 3rd Computational Methods in Systems and Software, CoMeSySo 2019 ; Conference Date: 10 September 2019 Through 12 September 2019; Conference Code:232339
Y1  - 2019///
VL  - 1047
A1  - Foong, O.-M.
A1  - Sulaiman, S.
A1  - Khairuddin, A.A.
JF  - Advances in Intelligent Systems and Computing
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075614847&doi=10.1007%2f978-3-030-31362-3_14&partnerID=40&md5=f99a0854a7cb3a883504c36e7f47d688
ID  - scholars11999
KW  - Acceptance tests; Computational methods; Diseases; Intelligent systems; Monitoring; Patient monitoring
KW  -  Atrial fibrillation; Heart beats; Heart rates; Monitoring device; Risk factors; Stroke; Stroke detection; User acceptance testing
KW  -  Heart
N2  - This paper presents Atrial Fibrillation Detection for Stroke Prevention. Stroke is the third leading cause of death in Malaysia after cancer. Furthermore, one of the risk factors for stroke is Atrial Fibrillation. The objective of this paper is to develop an IoT device that helps to perform early detection of irregular heart beat at affordable cost. However, the devices or gadgets are expensive and a doctor will not be always available to monitor patientâ??s pulse regularly. Therefore, a real-time heart rate and rhythm monitoring device are presented in this paper. Experimental results show that the proposed device has achieved satisfactory performance in terms of user acceptance testing. © 2019, Springer Nature Switzerland AG.
ER  -