scholarly journals Measurement heart rate based on plastic optical fiber sensor

2019 ◽  
Vol 1170 ◽  
pp. 012074
Author(s):  
A Arifin ◽  
A K Lebang ◽  
M Yunus ◽  
S Dewang ◽  
I Idris ◽  
...  
2021 ◽  
Vol 3 ◽  
Author(s):  
Rongjian Zhao ◽  
Lidong Du ◽  
Zhan Zhao ◽  
Xianxiang Chen ◽  
Jie Sun ◽  
...  

The aim of this work is to present a method for accurately estimating heart and respiration rates under different actual conditions based on a mattress which was integrated with an optical fiber sensor. During the estimation, a ballistocardiogram (BCG) signal, which was obtained from the optical fiber sensor, was used for extracting the heart rate and the respiration rate. However, due to the detrimental effects of the differential detector, self-interference, and variation of installation status of the sensor, the ballistocardiogram (BCG) signal was difficult to detect. In order to resolve the potential concerns of individual differences and body interferences, adaptive regulations and statistical classifications spectrum analysis were used in this paper. Experiments were carried out to quantify heart and respiration rates of healthy volunteers under different breathing and posture conditions. From the experimental results, it could be concluded that (1) the heart rates of 40–150 beats per minute (bpm) and respiration rates of 10–20 breaths per minute (bpm) were measured for individual differences; (2) for the same individuals under four different posture contacts, the mean errors of heart rates were separately 1.60 ± 0.98 bpm, 1.94 ± 0.83 bpm, 1.24 ± 0.59 bpm, and 1.06 ± 0.62 bpm, in contrast, the mean errors of the polar beat device were 1.09 ± 0.96 bpm, 1.44 ± 0.99 bpm, and 1.78 ± 0.94 bpm. Furthermore, the experimental results were validated by conventional counterparts which used skin-contacting electrodes as their measurements. It was reported that the heart rate was 0.26 ± 2.80 bpm in 95% confidence intervals (± 1.96SD) in comparison with Philips sure-signs VM6 medical monitor, and the respiration rate was 0.41 ± 1.49 bpm in 95% confidence intervals (± 1.96SD) in comparison with ECG-derived respiratory (EDR) measurements for respiration rates. It was indicated that the developed system using adaptive regulations and statistical classifications spectrum analysis performed better and could easily be used under complex environments.


1994 ◽  
Author(s):  
Francesco Baldini ◽  
Susanna Bracci ◽  
Franco Cosi

2006 ◽  
Author(s):  
Matteo Foroni ◽  
Michele Bottacini ◽  
Federica Poli ◽  
Annamaria Cucinotta ◽  
Stefano Selleri

1989 ◽  
Vol 28 (11) ◽  
pp. 2022 ◽  
Author(s):  
Quan Zhou ◽  
David Kritz ◽  
Laura Bonnell ◽  
George H. Sigel

2014 ◽  
Author(s):  
M. Esakkimuthu Raju ◽  
Badrinath Vadakkapattu Canthadai ◽  
Kumar Ravi ◽  
Vengalrao Pachava ◽  
Dipankar Sengupta

2015 ◽  
Vol 15 (1) ◽  
pp. 14-18 ◽  
Author(s):  
Cátia Sofia Jorge Leitão ◽  
Paulo Fernando da Costa Antunes ◽  
José Adelino Mesquita Bastos ◽  
João de Lemos Pinto ◽  
Paulo Sérgio de Brito André

2018 ◽  
Vol 18 (4) ◽  
pp. 1513-1519 ◽  
Author(s):  
Crystal Penner ◽  
Cornelia Hoehr ◽  
Sinead O'Keeffe ◽  
Peter Woulfe ◽  
Cheryl Duzenli

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