Towards accurate wearable data for clinical decision making

Overview: Wearable devices can now measure a wealth of physiological information and could potentially be used to inform clinical decision making. In this talk, Dr Peter Charlton will provide an introduction to wearable technology, including the sensors, signal processing algorithms, and potential clinical applications. He will present work on benchmarking open-source algorithms to extract physiological information accurately from wearables. He will present results on the accuracy of algorithms across different patient groups and settings, and discuss the potential utility of the data for clinical decision making.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-08-20
DOI
https://doi.org/10.5281/zenodo.13347570
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
0.00
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article

Towards accurate wearable data for clinical decision making

Zenodo (CERN European Organization for Nuclear Research)
Non-Invasive Vital Sign Monitoring
article

Towards accurate wearable data for clinical decision making

article en

Abstract

Overview: Wearable devices can now measure a wealth of physiological information and could potentially be used to inform clinical decision making. In this talk, Dr Peter Charlton will provide an introduction to wearable technology, including the sensors, signal processing algorithms, and potential clinical applications. He will present work on benchmarking open-source algorithms to extract physiological information accurately from wearables. He will present results on the accuracy of algorithms across different patient groups and settings, and discuss the potential utility of the data for clinical decision making.

Zenodo (CERN European Organization for Nuclear Research)
University of Cambridge (GB)
Peace, Justice and strong institutions
Openalex Percentile: Top 66%
Non-Invasive Vital Sign Monitoring
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