Literature DB >> 23408381

iPhysioMeter: a new approach for measuring heart rate and normalized pulse volume using only a smartphone.

Kenta Matsumura1, Takehiro Yamakoshi.   

Abstract

Heart rate (HR) and normalized pulse volume (NPV) are physiological indices that have been used in a diversity of psychological studies. However, measuring these indices often requires laborious processes. We therefore developed a new smartphone program, named iPhysioMeter, that makes it possible to measure beat-by-beat HR and ln NPV using only a smartphone. We examined its accuracy against conventional laboratory measures. Mental stress tasks were used to alter HR and ln NPV in 12 participants. Bland-Altman analyses revealed negligible proportional bias for HR and ln NPV or for their change values, expressed as ΔHR and Δln NPV. However, a relatively large fixed bias did emerge for ln NPV, as well as a small one for Δln NPV, although both were within the limits of agreement. These findings suggest that iPhysioMeter can yield valid measures of the absolute level of HR and of relative changes in ln NPV.

Entities:  

Mesh:

Year:  2013        PMID: 23408381     DOI: 10.3758/s13428-012-0312-z

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  21 in total

1.  Comparison of smartphone application-based vital sign monitors without external hardware versus those used in clinical practice: a prospective trial.

Authors:  John C Alexander; Abu Minhajuddin; Girish P Joshi
Journal:  J Clin Monit Comput       Date:  2016-05-12       Impact factor: 2.502

Review 2.  Functional and Technical Aspects of Self-management mHealth Apps: Systematic App Search and Literature Review.

Authors:  Lyan Alwakeel; Kevin Lano
Journal:  JMIR Hum Factors       Date:  2022-05-25

3.  Rational selection of RGB channels for disease classification based on IPPG technology.

Authors:  Ge Xu; Liquan Dong; Jing Yuan; Yuejin Zhao; Ming Liu; Mei Hui; Yuebin Zhao; Lingqin Kong
Journal:  Biomed Opt Express       Date:  2022-03-03       Impact factor: 3.562

4.  Is There a Clinical Role For Smartphone Sleep Apps? Comparison of Sleep Cycle Detection by a Smartphone Application to Polysomnography.

Authors:  Sushanth Bhat; Ambra Ferraris; Divya Gupta; Mona Mozafarian; Vincent A DeBari; Neola Gushway-Henry; Satish P Gowda; Peter G Polos; Mitchell Rubinstein; Huzaifa Seidu; Sudhansu Chokroverty
Journal:  J Clin Sleep Med       Date:  2015-07-15       Impact factor: 4.062

5.  Cardiovascular hemodynamic effects of Red Bull® Energy Drink during prolonged, simulated, monotonous driving.

Authors:  Takehiro Yamakoshi; Kenta Matsumura; Shota Hanaki; Peter Rolfe
Journal:  Springerplus       Date:  2013-05-09

6.  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

7.  Cuffless and Continuous Blood Pressure Estimation from the Heart Sound Signals.

Authors:  Rong-Chao Peng; Wen-Rong Yan; Ning-Ling Zhang; Wan-Hua Lin; Xiao-Lin Zhou; Yuan-Ting Zhang
Journal:  Sensors (Basel)       Date:  2015-09-17       Impact factor: 3.576

8.  iPhone 4s photoplethysmography: which light color yields the most accurate heart rate and normalized pulse volume using the iPhysioMeter Application in the presence of motion artifact?

Authors:  Kenta Matsumura; Peter Rolfe; Jihyoung Lee; Takehiro Yamakoshi
Journal:  PLoS One       Date:  2014-03-11       Impact factor: 3.240

9.  Cuffless blood pressure estimation based on haemodynamic principles: progress towards mobile healthcare.

Authors:  Takehiro Yamakoshi; Peter Rolfe; Ken-Ichi Yamakoshi
Journal:  PeerJ       Date:  2021-05-25       Impact factor: 2.984

Review 10.  Mobile apps in cardiology: review.

Authors:  Borja Martínez-Pérez; Isabel de la Torre-Díez; Miguel López-Coronado; Jesús Herreros-González
Journal:  JMIR Mhealth Uhealth       Date:  2013-07-24       Impact factor: 4.773

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.