Key result
The smartphone-based blood pressure monitor using a photoplethysmography-only sensor and artificial neural network model predicted reference blood pressure values with >90% accuracy (r>0.90, p<0.001).
Why the study?
Smartphone-based photoplethysmography blood pressure monitoring is promising for hypertension self-monitoring, but user-friendly systems for continuous monitoring in elderly people are needed.
Does a mobile personal health care system using a wearable PPG-only sensor and smartphone app accurately estimate blood pressure in older adults?
Population
Three older adults (mean age 61.3 years, 66% women)
Comparison
Wearable PPG-only sensor and smartphone app for BP monitoring
Design
Development and usability study
Authors
Loading...
May support cuffless BP monitoring in older adults; leaves open prospective validation before clinical adoption.
Does a mobile personal health care system using a wearable PPG-only sensor and smartphone app accurately estimate blood pressure in older adults?
Effect estimate: r >0.90
p-value: p=<0.001
A novel cuffless PPG-based smartphone system showed high correlation for blood pressure estimation, though only diastolic BP met clinical accuracy standards, highlighting potential for continuous noninvasive monitoring with further refinement.
Mena et al. (2020) studied Blood pressure monitoring (n=3). Smartphone-based BP monitor using PPG-only sensor and ANN model vs. Validated semiautomated upper-arm cuff oscillometric device was evaluated on Prediction of reference blood pressure values (r >0.90, p=<0.001). The smartphone-based blood pressure monitor using a photoplethysmography-only sensor and artificial neural network model predicted reference blood pressure values with >90% accuracy (r>0.90, p<0.001).
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: