Key result
A Butterworth low pass filter produced a lower error value (7.57) compared to an adaptive LMS filter (maximum error 27.65) for reducing noise artifacts in finger sensor heart rate measurements.
Why the study?
Heart rate measurement using finger sensors is often compromised by motion artifacts, power line interference, low-amplitude PPG, and signal noise.
Do digital filters (Adaptive LMS and Butterworth) improve heart rate measurement accuracy from finger sensors by reducing artifact noise?
Do digital filters (Adaptive LMS and Butterworth) improve heart rate measurement accuracy from finger sensors by reducing artifact noise?
A Butterworth low pass filter effectively reduces noise artifacts in finger sensor heart rate measurements, outperforming an adaptive LMS filter.
Answers are grounded in this paper and cite their sources.
Butterworth may aid noise reduction in finger-sensor HR devices; hypothesis-generating pending clinical validation trials.
Heart rate is an important indicator in the health sector that can be used as an effective and rapid evaluation to determine the health status of the body. Motion or noise artifacts, power line interference, low amplitude PPG, and signal noise are all issues that might arise when measuring heart rate. This study aims to develop a digital filter that reduces noise artifacts on the finger sensor to improve heart rate measurement accuracy. Adaptive LMS and Butterworth are the two types of digital filters used in this research. In this study, data were collected from the patient while he or she was calm and moving around. In this research, the Nellcor finger sensor was employed to assess the blood flow in the fingers. The heart rate sensor will detect any changes in heart rate, and the measurement results will be presented on a personal computer (PC) as signals and heart rate values. The results of this investigation showed that utilizing an adaptive LMS filter and a Butterworth low pass filter with a cut-off frequency of 6Hz, order 4, and a sampling frequency of 1000Hz, with the Butterworth filter producing the least error value of 7.57 and adaptive LMS maximum error value of 27.65 as predicted by the researcher to eliminate noise artifacts. This research could be applied to other healthcare equipment systems that are being monitored to increase patient measurement accuracy.
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Maghfiroh et al. (2022) studied Heart rate measurement noise artifacts. Butterworth low pass filter vs. Adaptive LMS filter was evaluated on Error value. A Butterworth low pass filter produced a lower error value (7.57) compared to an adaptive LMS filter (maximum error 27.65) for reducing noise artifacts in finger sensor heart rate measurements.
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