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May 20, 2013IEEE Journal of Biomedical and Health Informatics227 citations

A Motion-Tolerant Adaptive Algorithm for Wearable Photoplethysmographic Biosensors

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RYR. YousefiMNMehrdad NouraniSOSarah Ostadabbas

Key Result

A novel adaptive algorithm for wearable PPG biosensors demonstrated high correlation with reference sensors for extracting heart rate (>0.98) and SpO2 (>0.7) during various physical activities.

Structured PICO

Does a novel real-time adaptive algorithm improve the accuracy of heart rate and SpO2 extraction from wearable PPG biosensors during motion?

P
Population
Single- and multisubject scenarios evaluated during standing, walking, and running at different conditions
I
Intervention
Novel real-time adaptive algorithm (two-stage normalized least mean square adaptive noise canceler) for wearable photoplethysmographic (PPG) biosensors
C
Comparator
Reference HR from commercial ECG and SpO2 sensors
O
Outcome
Accuracy of heart rate (HR) and pulse oximeter oxygen saturation (SpO2) extraction during motionsurrogate

A novel adaptive algorithm effectively removes motion artifacts from wearable PPG biosensors, enabling highly accurate heart rate and SpO2 monitoring during physical activity.

Main Result

Effect estimate: Correlation >0.98 for HR and >0.7 for SpO2

Abstract

The performance of portable and wearable biosensors is highly influenced by motion artifact. In this paper, a novel real-time adaptive algorithm is proposed for accurate motion-tolerant extraction of heart rate (HR) and pulse oximeter oxygen saturation ( SpO2) from wearable photoplethysmographic (PPG) biosensors. The proposed algorithm removes motion artifact due to various sources including tissue effect and venous blood changes during body movements and provides noise-free PPG waveforms for further feature extraction. A two-stage normalized least mean square adaptive noise canceler is designed and validated using a novel synthetic reference signal at each stage. Evaluation of the proposed algorithm is done by Bland-Altman agreement and correlation analyses against reference HR from commercial ECG and SpO2 sensors during standing, walking, and running at different conditions for a single- and multisubject scenarios. Experimental results indicate high agreement and high correlation (more than 0.98 for HR and 0.7 for SpO2 extraction) between measurements by reference sensors and our algorithm.

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Cite This Study

Yousefi et al. (2013) studied Healthy subjects (implied by standing, walking, running). Two-stage normalized least mean square adaptive noise canceler algorithm vs. Reference HR from commercial ECG and SpO2 sensors was evaluated on Agreement and correlation for HR and SpO2 extraction (Correlation >0.98 for HR and >0.7 for SpO2). A novel adaptive algorithm for wearable PPG biosensors demonstrated high correlation with reference sensors for extracting heart rate (>0.98) and SpO2 (>0.7) during various physical activities.

synapsesocial.com/papers/6a180d7256b3e2ada412e016https://doi.org/10.1109/jbhi.2013.2264358
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