A Wireless Photoplethysmography Chest Patch for Continuous Vital Sign Monitoring: A Clinical Validation Study in Intensive Care Patients

BACKGROUND: Continuous vital sign monitoring with wearable biosensors enables earlier detection of clinical deterioration and improves patient safety. This study validated an integrated wireless photoplethysmography-based chest patch biosensor (Biobeat technology Ltd) capable of measuring five vital signs relevant for Early Warning Score calculation, by comparison with standard continuous bedside monitoring in the intensive care unit. METHODS: Agreement between the wearable biosensor and the reference monitor was assessed using Bland-Altman analysis for repeated measurements. Bias and limits of agreement were calculated for all vital signs. Measurement differences were compared with predefined accuracy limits. Data were aligned at 5- and 15-min intervals using median reference values. Deming regression, Pearson correlation, and Clarke Error Grid analyses were performed. RESULTS-: A total of 1931.8 monitoring hours were collected from 32 intensive care patients (mean 60.4 ± 28.5 h). Heart rate showed a bias of 0.16 beats per minute (LoA -17.06 to 17.38), with 18.8% exceeding the 10% threshold and 0.42% in Clarke Error Grid zones D-E. Respiratory rate showed a bias of 3.77 breaths per minute (LoA -6.78 to 14.31), with 61.4% exceeding the 10% threshold and 18.6% in zones D-E. Systolic blood pressure, oxygen saturation, and temperature showed biases of -4.69 mmHg, -1.34%, and -0.29°C, respectively. CONCLUSION: Agreement between a wearable chest-patch biosensor and standard bedside monitoring was evaluated in intensive care patients. Overall agreement was variable, with wide limits of agreement and a substantial proportion of measurements outside predefined thresholds. Further optimisation and validation are required before broader clinical application. EDITORIAL COMMENT: In this article, limitations in agreement between signals from wearable wireless sensors for vital signs and usual vital signs monitor values in intensive care cases are described for data collected from a practical and pragmatic setting where the study participants were in early phase of their illness with some expected clinical deterioration. There were enough test device values outside of predefined limits of agreement based on clinically relevant differences, that the authors interpret this as a need for further improvement in device performance.

Authors

Institutions

Publication Details

Journal
Acta Anaesthesiologica Scandinavica
Published
2026-04-26
DOI
https://doi.org/10.1111/aas.70242
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Wireless Photoplethysmography Chest Patch for Continuous Vital Sign Monitoring: A Clinical Validation Study in Intensive Care Patients

Celine Vens, Louis Van Slambrouck, Lucy Van Kleunen, Wouter De Corte et al.
Acta Anaesthesiologica Scandinavica
Non-Invasive Vital Sign Monitoring
article

A Wireless Photoplethysmography Chest Patch for Continuous Vital Sign Monitoring: A Clinical Validation Study in Intensive Care Patients

Celine Vens, Louis Van Slambrouck, Lucy Van Kleunen, Wouter De Corte, Charlotte Van den Storme
article en

Abstract

BACKGROUND: Continuous vital sign monitoring with wearable biosensors enables earlier detection of clinical deterioration and improves patient safety. This study validated an integrated wireless photoplethysmography-based chest patch biosensor (Biobeat technology Ltd) capable of measuring five vital signs relevant for Early Warning Score calculation, by comparison with standard continuous bedside monitoring in the intensive care unit. METHODS: Agreement between the wearable biosensor and the reference monitor was assessed using Bland-Altman analysis for repeated measurements. Bias and limits of agreement were calculated for all vital signs. Measurement differences were compared with predefined accuracy limits. Data were aligned at 5- and 15-min intervals using median reference values. Deming regression, Pearson correlation, and Clarke Error Grid analyses were performed. RESULTS-: A total of 1931.8 monitoring hours were collected from 32 intensive care patients (mean 60.4 ± 28.5 h). Heart rate showed a bias of 0.16 beats per minute (LoA -17.06 to 17.38), with 18.8% exceeding the 10% threshold and 0.42% in Clarke Error Grid zones D-E. Respiratory rate showed a bias of 3.77 breaths per minute (LoA -6.78 to 14.31), with 61.4% exceeding the 10% threshold and 18.6% in zones D-E. Systolic blood pressure, oxygen saturation, and temperature showed biases of -4.69 mmHg, -1.34%, and -0.29°C, respectively. CONCLUSION: Agreement between a wearable chest-patch biosensor and standard bedside monitoring was evaluated in intensive care patients. Overall agreement was variable, with wide limits of agreement and a substantial proportion of measurements outside predefined thresholds. Further optimisation and validation are required before broader clinical application. EDITORIAL COMMENT: In this article, limitations in agreement between signals from wearable wireless sensors for vital signs and usual vital signs monitor values in intensive care cases are described for data collected from a practical and pragmatic setting where the study participants were in early phase of their illness with some expected clinical deterioration. There were enough test device values outside of predefined limits of agreement based on clinically relevant differences, that the authors interpret this as a need for further improvement in device performance.

Acta Anaesthesiologica ScandinavicaVol. 70(6)
Imec the Netherlands (NL), AZ Groeninge (BE), IMEC (BE), Department of Public Health (MM)
Good health and well-being
Openalex Percentile: Top 13%
Non-Invasive Vital Sign Monitoring
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.