scholarly journals Comparing pulse rate measurement in newborns using conventional and dry‐electrode ECG monitors

2022 ◽  
Author(s):  
Eris Twist ◽  
Hylke H. Salverda ◽  
Arjan B. te Pas
2021 ◽  
Author(s):  
Brian L. Hill ◽  
Xin Liu ◽  
Daniel McDuff

2020 ◽  
Vol 12 (22) ◽  
pp. 9646
Author(s):  
Jian-Chiun Liou ◽  
Chih-Wei Peng ◽  
Philippe Basset ◽  
Zhen-Xi Chen

In this study, a medical grade pulse rate (PR) instrument was used to monitor hemodialysis patients, and the wearable product was applied for the 4 h observation. Electrocardiogram (ECG) and photoplethysmography (PPG) data were simultaneously collected to observe physiological phenomena in patients undergoing hemodialysis. The analyzed results of 38 patients undergoing the treatment (as sympathetic/parasympathetic balance indicators before-hemodialysis (HD), and after-HD) and autonomic nerve activation for the pulse rate (PR) measurement accompanied by squeezing a soft ball were also observed. The results prove the pulse rate measurement while squeezing the soft ball and analyze data, and we show that the analyzed results have a very concentrated normal distribution. This study presents oxygen saturation (SpO2) and continuous pulse rate distribution curves during the 4 h observation of the hemodialysis patients and we show that some patients undergoing kidney dialysis have sleep apnea. They become lethargic during dialysis and experience severe hypoxia due to intermittent respiratory arrest. Studies have confirmed that such monitoring and biofeedback designs can reduce the incidence of hypotension during dialysis.


Photoplethysmography measures vital signs through to extraction of signals from the body. The paper explains the technique for extraction of pulse rate from the videos for three color channels namely; red, green and blue. The DMIMS database is used for experimentation which consists of total 720 videos out of which 25 videos are used for analysis. The results presented in this paper depict that our algorithm works best for blue channel followed by green and then red channel. The main focus of paper is to extract pulse rate from the recorded video and compare the output for different channels and find the best channel for heart rate extraction.


2019 ◽  
Vol 146 (4) ◽  
pp. 2145-2154 ◽  
Author(s):  
Julie Patris ◽  
Franck Malige ◽  
Hervé Glotin ◽  
Mark Asch ◽  
Susannah J. Buchan

2019 ◽  
Vol 9 (20) ◽  
pp. 4364 ◽  
Author(s):  
Frédéric Bousefsaf ◽  
Alain Pruski ◽  
Choubeila Maaoui

Remote pulse rate measurement from facial video has gained particular attention over the last few years. Research exhibits significant advancements and demonstrates that common video cameras correspond to reliable devices that can be employed to measure a large set of biomedical parameters without any contact with the subject. A new framework for measuring and mapping pulse rate from video is presented in this pilot study. The method, which relies on convolutional 3D networks, is fully automatic and does not require any special image preprocessing. In addition, the network ensures concurrent mapping by producing a prediction for each local group of pixels. A particular training procedure that employs only synthetic data is proposed. Preliminary results demonstrate that this convolutional 3D network can effectively extract pulse rate from video without the need for any processing of frames. The trained model was compared with other state-of-the-art methods on public data. Results exhibit significant agreement between estimated and ground-truth measurements: the root mean square error computed from pulse rate values assessed with the convolutional 3D network is equal to 8.64 bpm, which is superior to 10 bpm for the other state-of-the-art methods. The robustness of the method to natural motion and increases in performance correspond to the two main avenues that will be considered in future works.


2019 ◽  
Vol 18 (4) ◽  
pp. 658-666
Author(s):  
Nawang Wahyu Widiatmaka ◽  
Muhammad Ragil Suryoputro ◽  
Muhammad Safri Setiawan
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document