<![CDATA[The increasing prevalence of motion artifacts (MA) in photoplethysmography (PPG) signals poses significantchallenges for accurate heart rate monitoring, particularly in dynamic environments. This study addresses the problem of MAinterference in PPG signals, which can lead to erroneous heart rate readings and compromised patient monitoring. To mitigatethis issue, we employed an Infinite Impulse Response (IIR) filter to enhance the quality of PPG signals by effectively reducingthe impact of motion artifacts. The methodology involved collecting PPG signals from a sample of participants during variousphysical activities. The raw signals were subjected to both filtering and non-filtering processes using MATLAB, allowing fora comparative analysis of the signal quality. The filtering process was designed to suppress unwanted frequencies associatedwith motion while preserving the physiological signals of interest. The performance of the IIR filter was evaluated based onthe Signal-to-Noise Ratio (SNR) and the accuracy of heart rate extraction. Results indicated a significant improvement insignal quality post-filtering, with the SNR increasing from an average of 5.2 dB to 15.8 dB, demonstrating a substantialenhancement 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, theapplication of the IIR filter in processing PPG signals effectively reduces motion artifacts, leading to more accurate heart ratemonitoring. This research highlights the potential for improved patient outcomes in clinical settings and suggests furtherexploration of advanced filtering techniques to enhance the reliability of wearable health monitoring devices. The findingsunderscore the importance of addressing motion artifacts in the development of robust biomedical sensing technologies.]]>
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