ArticleCardiovascular engineering and technology2026
Reduction of Motion Artifacts in Cardiorespiratory Vital Signs as Oxygen Saturation and Non-Invasive Blood Pressure Through Redundant Denoising and Adaptive Filtering Methods for Wearable Healthcare Monitoring Systems.
Article in Cardiovascular engineering and technology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
BACKGROUND AND
objectiveChronic cardiovascular diseases have motivated the development of wearable systems capable of continuously monitoring physiological variables such as oxygen saturation (SpO
methodsThe proposed framework combines independent component analysis and recursive least-squares adaptive filtering to separate physiological information from motion-induced interference. Performance was compared with conventional finite impulse response (FIR) filtering and wavelet shrinkage (WS) methods using signal-to-noise ratio (SNR), weighted distortion assessment (WDA), oxygen saturation estimation, and blood pressure estimation metrics.
resultsThe proposed method achieved statistically significant improvements in signal quality and physiological parameter estimation. Average SNR improved from
conclusionsThe proposed framework improves the robustness of wearable PPG and NIBP monitoring under motion conditions through the combined use of sensor redundancy, ECG-guided temporal coupling, inertial measurements, and adaptive multichannel signal processing. The results demonstrate significant improvements in signal quality and physiological parameter estimation compared with conventional denoising approaches, supporting the potential use of the method in ambulatory cardiovascular monitoring applications.
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