Detecting Episodes of Brady- and Tachycardia Using Photo-plethysmography at the Wrist in Free-living Conditions

Abstract

Detecting episodes of bradycardia and tachycardia can help identifying the clinical relevance of common cardiac symptoms. This study aimed at investigating whether an unobtrusive wrist-wearable device equipped with a photoplethysmographic (PPG) and acceleration sensor could be used to detect such rate abnormalities in free-living conditions. Twenty patients (M=55%, age: 67 ± 13 y) reporting cardiac symptoms were monitored for 24 hours in free-living conditions using a portable Holter ECG recorder. Simultaneously, a wrist-wearable device equipped with a PPG and acceleration sensor was used to measure heart rate and the mean inter-pulse-interval (IPI) in 5-sec epochs. ECG-derived inter-beat-intervals (IBI) were used as ground truth for determining episodes of bradycardia (>1200 ms) and tachycardia (<500 ms) during the monitoring period. According to the ECG, the duration of brady-and tachycardia and normal rate lasted a total of 766 min, 64 min, and 27024 min, respectively. Average IPI during bradycardia and tachycardia was 1310 ± 80 ms and 459 ± 37 ms, respectively. IPI data correctly identified episodes of bradycardia (Se: 85.0%, Sp: 99.4%) and tachycardia (Se: 89.1%, Sp: 99.9%). In conclusion, a wrist-wearable device equipped with a PPG sensor can accurately detect rate abnormalities such as brady-and tachycardia in free-living conditions.

Bradycardia and Tachycardia Detection Using a Synthesis-by-Analysis Modeling Approach of Pulsatile Signal

“…The results of the training set for EB were Se = 100% and Sp = 93%, and that of for ET were Se = 100% and Sp = 89%. Bonomi et al [60] extracted PR from PPG signal to detect the episodes of bradycardia (Se = 85.0%, Sp = 99.4%) and tachycardia (Se = 89.1%, Sp = 99.9%). Zong et al [61] proposed using PBIs, pulse waveform amplitude and maximum slope, pulse signal quality, and the pulse rhythm to reduce false alarms.…”

Proposal for a Home Sleep Monitoring Platform Employing a Smart Glove

“…To detect episodes of bradycardia and tachycardia, the method developed by Bonomi et al in [ 64 ] was implemented. The beat time duration has been computed as the time difference between two successive pulses.…”

Smart Wearables for Cardiac Monitoring—Real-World Use beyond Atrial Fibrillation

“…Though most studies on PPG performance have focused on the detection of AF, it may also have a role in screening for other arrhythmias. In a small study of 20 participants comparing the use of a wrist wearable (Philips Cardio and Motion Monitoring Module) equipped with integrated optical PPG and accelerometer sensors against a 12-lead Holter, the former was able to identify episodes of bradycardia and tachycardia with a sensitivity of 85.0% and 99.4%, and specificity of 89.1% and 99.1%, respectively [ 32 ]. Elsewhere, Corino et al used the Empatica E4 wristband and developed a classifier machine learning software that correctly identified arrhythmias, including atrial flutter, atrial tachycardia and premature ventricular contractions, with a sensitivity, specificity and accuracy of 75.8%, 76.8% and 80%, respectively.…”