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James M. May

Researcher at City University London

Publications -  25
Citations -  251

James M. May is an academic researcher from City University London. The author has contributed to research in topics: Photoplethysmogram & Anterior fontanelle. The author has an hindex of 5, co-authored 21 publications receiving 99 citations. Previous affiliations of James M. May include University of London.

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Journal ArticleDOI

Heart Rate Variability (HRV) and Pulse Rate Variability (PRV) for the Assessment of Autonomic Responses

TL;DR: Investigating the differences between HRV and PRV found that PRV responds to cold exposure differently to HRV, especially in peripheral sites such as the finger and the toe, and may have different information not available in HRV due to its non-localized nature.
Journal ArticleDOI

Pulse rate variability in cardiovascular health: a review on its applications and relationship with heart rate variability

TL;DR: It was found that the relationship between heart rate variability and pulse rate variability is not entirely understood yet, and that pulse rates variability might be influenced not only due to technical aspects but also by physiological factors that might affect the measurements obtained from pulse-to-pulse time series extracted from pulse waves.
Proceedings ArticleDOI

Design and development of a novel multi-channel photoplethysmographic research system

TL;DR: The design, development and validation of such a modular PPG system with the capability to operate with commercial sensors was developed and calibrated using a FLUKE Index 2 SpO2 simulator and results showed close correlation between commercial and custom made system.
Journal ArticleDOI

Differential effects of the blood pressure state on pulse rate variability and heart rate variability in critically ill patients.

TL;DR: In this paper, the relationship between PRV and HRV under different BP states: hypotension, normotension, and hypertension was assessed using the MIMIC III database, and several time-domain, frequency-domain and nonlinear indices were obtained from these signals.
Journal ArticleDOI

Classification of blood pressure in critically ill patients using photoplethysmography and machine learning.

TL;DR: In this paper, the authors evaluated the capability of features extracted from photoplethysmography (PPG) based Pulse Rate Variability (PRV) to classify hypertensive, normotensive and hypotensive events, and to estimate mean arterial, systolic and diastolic blood pressure in critically ill patients.