Analysis Infinite Impulse Response Filter for Reducing Motion Artifacts in Heart Rate Signals Based on Photoplethysmography
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The increasing prevalence of motion artifacts (MA) in photoplethysmography (PPG) signals poses significant
challenges for accurate heart rate monitoring, particularly in dynamic environments. This study addresses the problem of MA
interference in PPG signals, which can lead to erroneous heart rate readings and compromised patient monitoring. To mitigate
this issue, we employed an Infinite Impulse Response (IIR) filter to enhance the quality of PPG signals by effectively reducing
the impact of motion artifacts. The methodology involved collecting PPG signals from a sample of participants during various
physical activities. The raw signals were subjected to both filtering and non-filtering processes using MATLAB, allowing for
a comparative analysis of the signal quality. The filtering process was designed to suppress unwanted frequencies associated
with motion while preserving the physiological signals of interest. The performance of the IIR filter was evaluated based on
the Signal-to-Noise Ratio (SNR) and the accuracy of heart rate extraction. Results indicated a significant improvement in
signal quality post-filtering, with the SNR increasing from an average of 5.2 dB to 15.8 dB, demonstrating a substantial
enhancement in the clarity of the PPG signals. Furthermore, the heart rate extraction accuracy improved from 78% to 95%
after applying the IIR filter, showcasing the effectiveness of the proposed method in real-time applications. In conclusion, the
application of the IIR filter in processing PPG signals effectively reduces motion artifacts, leading to more accurate heart rate
monitoring. This research highlights the potential for improved patient outcomes in clinical settings and suggests further
exploration of advanced filtering techniques to enhance the reliability of wearable health monitoring devices. The findings
underscore the importance of addressing motion artifacts in the development of robust biomedical sensing technologies.
Copyright (c) 2024 Wa Ode Nurul Fadillah, Her Gumiwang Ariswati, and Wahyu Caesarendra
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