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- W2785655557 abstract "Aging population and continuous prevalence of CVD (Cardio-vascular diseases) lead to 30% of total deaths globally. This is due to lack of continuous monitoring and loss of information from vital physiological signals like ECG (Electrocardiogram), EEG (Electroencephalogram) & EMG (Electromyogram) in many patients.To analyze these signals, time-frequency domain is the best suited method. A Discrete Wavelet Transform (DWT) is employed for the better understanding of the ECG signal in Time-Frequency plane with (Haar) as a Mother Wavelet function. Using calculated DWT coefficients and Modulus Maxima Analysis (MMA) with Time – domain refinement, PQRST complex of an ECG signal samples are estimated and extracted. In order to get the best results from the proposed approach, area and power are the performance metrics need to be taken care of. So, an efficient algorithm in view of high performance and low area, is developed and implemented for the extraction of P, Q, R, S and T points of an ECG signal, which overcomes the issues such as QRS fragmentation, detection of P & T waves accurately for a noisy wave.The resulting algorithm is a low complexity arithmetic algorithm which reduces the arithmetic logic thereby improving the performance of the developed environment using ADSP processor which leads to low power and low area." @default.
- W2785655557 created "2018-02-23" @default.
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- W2785655557 date "2017-01-01" @default.
- W2785655557 modified "2023-09-27" @default.
- W2785655557 title "Low Complex Real-Time Automated Cardiac Remote Health Monitoring System" @default.
- W2785655557 hasPublicationYear "2017" @default.
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