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Measuring Vascular Recovery Rate After Exercise †.
Halil Dijab1, Jordi Alastruey1, Peter H Charlton1
1Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, King's Health Partners, St Thomas' Hospital, London SE1 7EH, UK.
Proceedings (MDPI)
|July 5, 2022
Summary
Vascular recovery rate (VRR), measured using photoplethysmogram (PPG) signals from wearables, shows potential for assessing cardiovascular risk. This novel approach may offer insights beyond traditional heart rate recovery metrics.
Area of Science:
- Cardiovascular physiology
- Biomedical engineering
- Wearable technology
Background:
- Exercise recovery rate is a known indicator of cardiovascular risk.
- Heart rate recovery post-exercise predicts mortality, but vascular recovery has been understudied.
- Photoplethysmogram (PPG) signals from smart wearables offer a non-invasive method for physiological monitoring.
Purpose of the Study:
- To introduce and assess a novel method for quantifying vascular recovery rate (VRR) using PPG signals.
- To explore the potential of VRR indices as indicators of cardiovascular risk.
- To compare VRR with heart rate recovery as a cardiovascular risk marker.
Main Methods:
- Utilized the VORTAL dataset containing PPG signals from 39 healthy subjects before and after exercise.
- Extracted 31 VRR indices from the PPG pulse wave shape.
- Quantified the rate of VRR index return to baseline post-exercise and assessed inter-subject consistency.
Main Results:
- Many VRR indices demonstrated exercise-induced changes consistent across subjects.
- Indices derived from pulse wave timings and second derivative showed promise for future research.
- The rate of VRR index recovery varied between indices and subjects, suggesting potential for risk stratification.
Conclusions:
- Assessing VRR from PPG signals post-exercise is feasible.
- VRR indices may provide additional cardiovascular risk information beyond heart rate recovery.
- Further research is warranted to link VRR indices to cardiovascular fitness and wearable sensor integration.
