Synchronized wearables for the detection of haemodynamic states via electrocardiography and multispectral photoplethysmography.

Autor: Franklin D; Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada. dan.franklin@utoronto.ca.; Ted Rogers Centre for Heart Research, Peter Munk Cardiac Centre, University Health Network, Toronto, Onatrio, Canada. dan.franklin@utoronto.ca., Tzavelis A; Medical Scientist Training Program, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.; Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, USA.; Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, IL, USA., Lee JY; Sibel Health, Niles, IL, USA., Chung HU; Sibel Health, Niles, IL, USA., Trueb J; Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, IL, USA., Arafa H; Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, USA.; Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, IL, USA., Kwak SS; Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, IL, USA., Huang I; Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, IL, USA.; Department of Materials Science and Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, USA., Liu Y; Department of Electrical and Computer Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, USA., Rathod M; Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.; Ted Rogers Centre for Heart Research, Peter Munk Cardiac Centre, University Health Network, Toronto, Onatrio, Canada., Wu J; Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.; Ted Rogers Centre for Heart Research, Peter Munk Cardiac Centre, University Health Network, Toronto, Onatrio, Canada., Liu H; Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.; Ted Rogers Centre for Heart Research, Peter Munk Cardiac Centre, University Health Network, Toronto, Onatrio, Canada., Wu C; Department of Materials Science and Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, USA., Pandit JA; Scripps Research Translational Institute, San Diego, CA, USA., Ahmad FS; Division of Cardiology, Department of Medicine, Bluhm Cardiovascular Institute, Northwestern University, Chicago, IL, USA., McCarthy PM; Division of Cardiac Surgery, Department of Surgery, Bluhm Cardiovascular Institute, Northwestern University, Chicago, IL, USA., Rogers JA; Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, USA. jrogers@northwestern.edu.; Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, IL, USA. jrogers@northwestern.edu.; Department of Materials Science and Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, USA. jrogers@northwestern.edu.; Department of Neurological Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA. jrogers@northwestern.edu.
Jazyk: angličtina
Zdroj: Nature biomedical engineering [Nat Biomed Eng] 2023 Oct; Vol. 7 (10), pp. 1229-1241. Date of Electronic Publication: 2023 Oct 02.
DOI: 10.1038/s41551-023-01098-y
Abstrakt: Cardiovascular health is typically monitored by measuring blood pressure. Here we describe a wireless on-skin system consisting of synchronized sensors for chest electrocardiography and peripheral multispectral photoplethysmography for the continuous monitoring of metrics related to vascular resistance, cardiac output and blood-pressure regulation. We used data from the sensors to train a support-vector-machine model for the classification of haemodynamic states (resulting from exposure to heat or cold, physical exercise, breath holding, performing the Valsalva manoeuvre or from vasopressor administration during post-operative hypotension) that independently affect blood pressure, cardiac output and vascular resistance. The model classified the haemodynamic states on the basis of an unseen subset of sensor data for 10 healthy individuals, 20 patients with hypertension undergoing haemodynamic stimuli and 15 patients recovering from cardiac surgery, with an average precision of 0.878 and an overall area under the receiver operating characteristic curve of 0.958. The multinodal sensor system may provide clinically actionable insights into haemodynamic states for use in the management of cardiovascular disease.
(© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)
Databáze: MEDLINE
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