Key result
The VSS-CLLMS algorithm achieved superior Signal to Noise Ratio Improvement compared to other algorithms, reaching 13.56 dB for baseline wander and 13.76 dB for muscle artifact removal.
Why the study?
Does the VSS-CLLMS algorithm improve signal-to-noise ratio and reduce artifacts in ECG signals compared to other adaptive filters?
Does the VSS-CLLMS algorithm improve signal-to-noise ratio and reduce artifacts in ECG signals compared to other adaptive filters?
The VSS-CLLMS adaptive filtering algorithm effectively removes baseline wander and muscle artifacts from ECG signals, improving signal quality for remote telecardiology monitoring.
May enhance ECG quality for telecardiology monitoring; leaves open prospective clinical validation.
An increasing number of elderly and disabled people urge the need for a health care monitoring system which has the capabilities for analyzing patient health care data to avoid preventable deaths. Medical Telemetry is becoming a key tool in assisting patients living remotely where a “Real-time Remote Critical Health Care Monitoring System” (RRCHCMS) can be utilized for the same. The RRCHCMS is capable of receiving and transmitting data from a remote location to a location that has the capability to diagnose the data and affect decision making and further providing assistance to the patient. During the cardiac analysis, several artifacts solidly affect the ST segment, humiliate the signal quality, frequency resolution, and results in large amplitude signals in ECG that simulate PQRST waveform and cover up the miniature features that are useful for clinical monitoring and diagnosis. In this paper, several leaky based adaptive filter structures for cardiac signal improvement are discussed. The Circular Leaky Least Mean Square (CLLMS) algorithm being the steepest drop strategy for dropping the mean squared error gives a better result in comparison with the Least Mean Square (LMS) algorithm. To enlarge the filtering ability some variants of LMS, Normalized Least Mean Square (NLMS), CLLMS, Variable Step Size CLLMS (VSS-CLLMS) algorithms are used in both time domain (TD) and frequency domain (FD). At last, we applied this algorithm on cardiac signals occurred due to MIT-BIH database. The performance of CLLMS algorithm is better compared to LLMS counterparts in conditions of Signal to Noise Ratio Improvement (SNRI), Excess Mean Square Error (EMSE) and Misadjustment (MSD). When compared to all other algorithms VSS-CLLMS gives superior SNRI. These values are 13.5616dB and 13.7592dB for Baseline Wander (BW) and Muscle Artifact (MA) removal.
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Sulthana et al. (2018) studied ECG artifacts (Baseline Wander and Muscle Artifact). Variable Step Size Circular Leaky Least Mean Square (VSS-CLLMS) algorithm vs. LMS, NLMS, and CLLMS algorithms was evaluated on Signal to Noise Ratio Improvement (SNRI). The VSS-CLLMS algorithm achieved superior Signal to Noise Ratio Improvement compared to other algorithms, reaching 13.56 dB for baseline wander and 13.76 dB for muscle artifact removal.
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