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Photoplethysmography-Based Machine Learning Approaches for Atrial Fibrillation Burden: Algorithm Development and Validation

Photoplethysmography-Based Machine Learning Approaches for Atrial Fibrillation Burden: Algorithm Development and Validation

AF: atrial fibrillation; ECG: electrocardiogram; PPG: photoplethysmography; SR: sinus rhythm. Metric M2 is the proportion of AF episodes detected through PPG monitoring relative to the total number of monitoring epochs, assessing frequency-based AF variations (Figure 2). A schematic diagram of metric M2. AF: atrial fibrillation; ECG: electrocardiogram; PPG: photoplethysmography; SR: sinus rhythm.

Hong Wang, Binbin Liu, Hui Zhang, Zheqi Zhang, Zhigeng Jin, Hao Wang, Yu-Tao Guo

JMIR Cardio 2025;9:e78075


Noninvasive Multiparameter Monitoring for the Detection of Decompensated Heart Failure: Exploratory Study

Noninvasive Multiparameter Monitoring for the Detection of Decompensated Heart Failure: Exploratory Study

The PDL is a wrist-worn, research-grade monitoring device measuring photoplethysmography (PPG)- and accelerometry-derived data (Figure 1 A). Participants were blinded to their recorded parameters and did not receive feedback based on the measurements. The PDL is rain and splash resistant, but cannot be worn during showering or swimming. Data were offloaded from the PDL via Bluetooth as soon as the device was within reach of a gateway (Monitoring Study bo X [MSX]; Figure 1 B).

Cyrille Herkert, Mayke van Leunen, Ignace Luc Johan De Lathauwer, Valerie Albertina Antonetta van Es, Jialu Tang, Aaqib Saeed, Rudolph Ferdinand Spee, Yuan Lu, Hareld Marijn Clemens Kemps

JMIR Form Res 2025;9:e59116


Evaluating Diversity in Open Photoplethysmography Datasets: Protocol for a Systematic Review

Evaluating Diversity in Open Photoplethysmography Datasets: Protocol for a Systematic Review

Photoplethysmography (PPG) is an optical method for measuring blood volume changes in microcirculation, through noninvasive photodetection. It has become a widespread and essential tool, providing the sensing technology for pulse oximeters in clinical use and being widely used in consumer wearables such as smartwatches for heart rate monitoring. However, technical aspects of PPG make it susceptible to intrinsic bias, with the potential to adversely affect particular patient and consumer populations.

Vedha Penmetcha, Lekaashree Rambabu, Brandon G Smith, Orla Mantle, Thomas Edmiston, Laura Hobbs, Shobhana Nagraj, Peter H Charlton, Tom Bashford

JMIR Res Protoc 2025;14:e73040


Estimation of Brachial-Ankle Pulse Wave Velocity With Hierarchical Regression Model From Wrist Photoplethysmography and Electrocardiographic Signals: Method Design

Estimation of Brachial-Ankle Pulse Wave Velocity With Hierarchical Regression Model From Wrist Photoplethysmography and Electrocardiographic Signals: Method Design

Photoplethysmography (PPG) [3,4], ballistocardiography [5,6], electrical bioimpedance [7], or tonometry [8] has been widely studied for these purposes. Due to the ease of implementation, the optical PPG module is more often integrated into the wearable devices. The potential of estimation of BP [9,10] and PWV [11-13] from PPG signals attracts much attention. Various approaches have been investigated to estimate PWV from PPG signals of different measurement sites [14].

Chih-I Ho, Chia-Hsiang Yen, Yu-Chuan Li, Chiu-Hua Huang, Jia-Wei Guo, Pei-Yun Tsai, Hung-Ju Lin, Tzung-Dau Wang

JMIR Biomed Eng 2025;10:e58756


Toward Ambulatory Baroreflex Sensitivity: Comparison Between Indices of Arterial Line and Photoplethysmography in Male Volunteers

Toward Ambulatory Baroreflex Sensitivity: Comparison Between Indices of Arterial Line and Photoplethysmography in Male Volunteers

This method uses a 2-sensor system that combines photoplethysmography (PPG) and a pressure sensor [12,13]. Previous investigations have revealed that, depending on the device, the variability of the systolic pressure has been overestimated by 78% and 103% in the low-frequency band [13]. In addition, the same investigation demonstrated an underestimation of the baroreflex sensitivity by −24% or −31%.

Jolanda Witteveen, Fabian Beutel, Evelien Hermeling

JMIR Cardio 2025;9:e54771


Wrist-Worn and Arm-Worn Wearables for Monitoring Heart Rate During Sedentary and Light-to-Vigorous Physical Activities: Device Validation Study

Wrist-Worn and Arm-Worn Wearables for Monitoring Heart Rate During Sedentary and Light-to-Vigorous Physical Activities: Device Validation Study

Consequently, there is growing interest in wrist-, upper arm-, or forearm-wearable devices, which use photoplethysmography (PPG) [13]. PPG is a noninvasive measurement technique that detects blood volume changes in the microvascular bed of tissue by illuminating the skin and measuring the reflected light [14].

Theresa Schweizer, Rahel Gilgen-Ammann

JMIR Cardio 2025;9:e67110


The Measurement of Vital Signs in Pediatric Patients by Lifelight Software in Comparison to the Standard of Care: Protocol for the VISION-Junior Observational Study

The Measurement of Vital Signs in Pediatric Patients by Lifelight Software in Comparison to the Standard of Care: Protocol for the VISION-Junior Observational Study

Photoplethysmography (PPG) is an optical measurement technique that records changes in the light reflected from the skin surface due to volumetric changes in the facial blood vessels; small variations in perfusion provide valuable information about the cardiovascular system [9]. PPG has been used to measure PR [10,11], oxygen saturation [12], BP [13,14], and RR [10,15] and to detect atrial fibrillation [16].

Gauri Misra, Simon Wegerif, Louise Fairlie, Melissa Kapoor, James Fok, Gemma Salt, Jay Halbert, Ian Maconochie, Niall Mullen

JMIR Res Protoc 2025;14:e58334


Effects of Missing Data on Heart Rate Variability Measured From A Smartwatch: Exploratory Observational Study

Effects of Missing Data on Heart Rate Variability Measured From A Smartwatch: Exploratory Observational Study

Wrist-worn devices most often use embedded photoplethysmography sensors that detect changes in light intensity on the skin surface due to changes in blood volume during the cardiac cycle to estimate heart rate [9]. While not all smartwatches are certified as medical devices currently, they offer a way of assessing the viability of photoplethysmography sensors, which are used in some cleared medical devices [9-11].

Hope Davis-Wilson, Meghan Hegarty-Craver, Pooja Gaur, Matthew Boyce, Jonathan R Holt, Edward Preble, Randall Eckhoff, Lei Li, Howard Walls, David Dausch, Dorota Temple

JMIR Form Res 2025;9:e53645


A Dynamic Adaptive Ensemble Learning Framework for Noninvasive Mild Cognitive Impairment Detection: Development and Validation Study

A Dynamic Adaptive Ensemble Learning Framework for Noninvasive Mild Cognitive Impairment Detection: Development and Validation Study

The Empatica 4 is a watch-like multisensor device that measures physiological data such as electrodermal activity (EDA), photoplethysmography, skin temperature, and accelerometer readings. It is compact, lightweight, and comfortable to wear, making it suitable for unobtrusive continuous monitoring during cognitive screening of older adults.

Aoyu Li, Jingwen Li, Yishan Hu, Yan Geng, Yan Qiang, Juanjuan Zhao

JMIR Med Inform 2025;13:e60250


Comparative Evaluation of Consumer Wearable Devices for Atrial Fibrillation Detection: Validation Study

Comparative Evaluation of Consumer Wearable Devices for Atrial Fibrillation Detection: Validation Study

The underlying CWD technology is mainly based on electrocardiography or photoplethysmography (PPG). While an ECG measures electrical signals from the heart using surface electrodes on the skin, PPG analyzes the heart rhythm through an optical technique that measures the peripheral pulse [10]. This PPG technology has been adopted by smartwatches and smartphones, using light-emitting diodes and sensors or smartphone flashlights and cameras to generate PPG waveforms.

Femke Wouters, Henri Gruwez, Christophe Smeets, Anessa Pijalovic, Wouter Wilms, Julie Vranken, Zoë Pieters, Hugo Van Herendael, Dieter Nuyens, Maximo Rivero-Ayerza, Pieter Vandervoort, Peter Haemers, Laurent Pison

JMIR Form Res 2025;9:e65139