Signal Quality Index Based on Template Cross-Correlation in Multimodal Biosignal Chair for Smart Healthcare

Area of Science:

• Biomedical Engineering
• Smart Healthcare Technology
• Physiological Signal Processing

Background:

• Unconstrained sensors in smart healthcare systems face challenges with signal quality due to weaker body connections compared to traditional methods.
• Assessing the reliability of physiological signals (ECG, PPG, BCG) from such systems is crucial for practical healthcare applications.
• Motion artifacts are known to impact the stability and accuracy of collected biosignals.

Purpose of the Study:

• To develop and evaluate a quality screening method for unconstrained physiological signals (ECG, PPG, BCG) collected via a biosignal chair.
• To determine the suitability of the biosignal chair for real-life measurements in smart healthcare.
• To assess the impact of various activities and body motions on signal quality and heart rate estimation.

Main Methods:

• Utilized a collective chair system equipped with unconstrained sensors to measure electrocardiogram (ECG), photoplethysmogram (PPG), and ballistocardiogram (BCG) signals.
• Defined a signal quality index based on cross-correlations between observed and noise-free signals using individual templates.
• Collected physiological data during virtual driving, powered wheelchair use, and diverse body motions.

Main Results:

• A novel signal quality index was developed to evaluate biosignals without requiring a reference signal.
• Motion artifacts adversely affected signal stability, but a supplementary sensor relationship was observed.
• Except for extreme movements, signal quality and estimated heart rate (HR) remained within acceptable limits for status monitoring.

Conclusions:

• The developed quality screening method is effective for assessing unconstrained physiological signals.
• The biosignal chair system demonstrates suitability for collecting reliable real-life measurements for healthcare.
• This technology has the potential to enhance safety and healthcare through improved monitoring.