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

Daniel Franklin*, Andreas Tzavelis, Jong Yoon Lee, Ha Uk Chung, Jacob Trueb, Hany Arafa, Sung Soo Kwak, Ivy Huang, Yiming Liu, Megh Rathod, Jonathan Wu, Haolin Liu, Changsheng Wu, Jay A Pandit, Faraz S. Ahmad, Patrick M. McCarthy, John A. Rogers*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1229-1241
Number of pages13
JournalNature Biomedical Engineering
Issue number10
StatePublished - Oct 2023

ASJC Scopus subject areas

  • Bioengineering
  • Biotechnology
  • Biomedical Engineering
  • Medicine (miscellaneous)
  • Computer Science Applications


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