Literature DB >> 27067432

A Pulse Rate Estimation Algorithm Using PPG and Smartphone Camera.

Sarah Ali Siddiqui1, Yuan Zhang2, Zhiquan Feng1, Anton Kos3.   

Abstract

The ubiquitous use and advancement in built-in smartphone sensors and the development in big data processing have been beneficial in several fields including healthcare. Among the basic vitals monitoring, pulse rate monitoring is the most important healthcare necessity. A multimedia video stream data acquired by built-in smartphone camera can be used to estimate it. In this paper, an algorithm that uses only smartphone camera as a sensor to estimate pulse rate using PhotoPlethysmograph (PPG) signals is proposed. The results obtained by the proposed algorithm are compared with the actual pulse rate and the maximum error found is 3 beats per minute. The standard deviation in percentage error and percentage accuracy is found to be 0.68 % whereas the average percentage error and percentage accuracy is found to be 1.98 % and 98.02 % respectively.

Keywords:  Mobile health; PhotoPlethysmoGraph (PPG); Pulse rate; Smartphone sensor

Mesh:

Year:  2016        PMID: 27067432     DOI: 10.1007/s10916-016-0485-6

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  8 in total

1.  Relations between ac-dc components and optical path length in photoplethysmography.

Authors:  Chungkeun Lee; Hang Sik Shin; Myoungho Lee
Journal:  J Biomed Opt       Date:  2011-07       Impact factor: 3.170

2.  Separate estimation of long- and short-term systolic blood pressure variability from photoplethysmograph.

Authors:  Riho Kondo; Md Shoaib Bhuiyan; Haruki Kawanaka; Koji Oguri
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2014

3.  Estimation of venous oxygenation saturation using the finger Photoplethysmograph (PPG) waveform.

Authors:  K Shafqat; R M Langford; S K Pal; P A Kyriacou
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2012

4.  Validation of heart rate extraction using video imaging on a built-in camera system of a smartphone.

Authors:  Sungjun Kwon; Hyunseok Kim; Kwang Suk Park
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2012

5.  Noninvasive monitoring of blood pressure using optical Ballistocardiography and Photoplethysmograph approaches.

Authors:  Zhihao Chen; Xiufeng Yang; Ju Teng Teo; Soon Huat Ng
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2013

6.  TROIKA: a general framework for heart rate monitoring using wrist-type photoplethysmographic signals during intensive physical exercise.

Authors:  Zhilin Zhang; Zhouyue Pi; Benyuan Liu
Journal:  IEEE Trans Biomed Eng       Date:  2014-09-19       Impact factor: 4.538

7.  Extraction of heart rate variability from smartphone photoplethysmograms.

Authors:  Rong-Chao Peng; Xiao-Lin Zhou; Wan-Hua Lin; Yuan-Ting Zhang
Journal:  Comput Math Methods Med       Date:  2015-01-12       Impact factor: 2.238

Review 8.  On the analysis of fingertip photoplethysmogram signals.

Authors:  Mohamed Elgendi
Journal:  Curr Cardiol Rev       Date:  2012-02
  8 in total
  7 in total

1.  Comparison of short-term heart rate variability indexes evaluated through electrocardiographic and continuous blood pressure monitoring.

Authors:  Riccardo Pernice; Michal Javorka; Jana Krohova; Barbora Czippelova; Zuzana Turianikova; Alessandro Busacca; Luca Faes
Journal:  Med Biol Eng Comput       Date:  2019-02-07       Impact factor: 2.602

2.  Detail-preserving pulse wave extraction from facial videos using consumer-level camera.

Authors:  Dingliang Wang; Xuezhi Yang; Xuenan Liu; Jin Jing; Shuai Fang
Journal:  Biomed Opt Express       Date:  2020-03-11       Impact factor: 3.732

3.  Analysis of a Pulse Rate Variability Measurement Using a Smartphone Camera.

Authors:  András Bánhalmi; János Borbás; Márta Fidrich; Vilmos Bilicki; Zoltán Gingl; László Rudas
Journal:  J Healthc Eng       Date:  2018-02-05       Impact factor: 2.682

Review 4.  Smartphone Sensors for Health Monitoring and Diagnosis.

Authors:  Sumit Majumder; M Jamal Deen
Journal:  Sensors (Basel)       Date:  2019-05-09       Impact factor: 3.576

5.  Passive Sensing of Health Outcomes Through Smartphones: Systematic Review of Current Solutions and Possible Limitations.

Authors:  Alina Trifan; Maryse Oliveira; José Luís Oliveira
Journal:  JMIR Mhealth Uhealth       Date:  2019-08-23       Impact factor: 4.773

6.  Smartphone App (2kmFIT-App) for Measuring Cardiorespiratory Fitness: Validity and Reliability Study.

Authors:  Adria Muntaner-Mas; Antonio Martinez-Nicolas; Alberto Quesada; Cristina Cadenas-Sanchez; Francisco B Ortega
Journal:  JMIR Mhealth Uhealth       Date:  2021-01-08       Impact factor: 4.773

7.  Enhancing the Robustness of Smartphone Photoplethysmography: A Signal Quality Index Approach.

Authors:  Ivan Liu; Shiguang Ni; Kaiping Peng
Journal:  Sensors (Basel)       Date:  2020-03-30       Impact factor: 3.576

  7 in total

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