Adaptive signal processing algorithm for remote detection of heart rate (HR) using ultra-wideband waveforms based on...

Area of Science:

• Biomedical Engineering
• Signal Processing
• Remote Sensing Technology

Background:

• Ultra-Wideband (UWB) technology offers non-contact capabilities for biomedical sensing.
• Accurate remote monitoring of vital signs, particularly heart rate (HR), remains a challenge.
• Existing remote HR detection methods often lack adaptability to physiological variations.

Purpose of the Study:

• To propose and evaluate a novel algorithm for enhancing remote heart rate detection using UWB technology.
• To develop an adaptive filtering approach that leverages UWB waveform parameters.
• To improve the accuracy and reliability of non-contact vital signs monitoring.

Main Methods:

• Development of an adaptive filter algorithm integrating UWB signal processing.
• Utilizing respiration and heart rate parameters extracted from UWB waveforms to adjust filter characteristics.
• Real-world data collection using a UWB transceiver for algorithm validation.

Main Results:

• The proposed algorithm demonstrated accurate detection of varying heart rates in remote monitoring scenarios.
• The adaptive filter effectively adjusted to physiological parameters, improving detection capabilities.
• Experimental results confirmed the efficacy of the UWB-based approach for HR monitoring.

Conclusions:

• The novel adaptive filtering algorithm significantly improves remote heart rate detection accuracy using UWB technology.
• This technique provides a robust solution for non-contact vital signs monitoring, adaptable to individual physiological signals.
• UWB technology, combined with advanced signal processing, shows great potential for future healthcare applications.