1. Design of ANC filter using modified cuckoo search technique for ECG signal enhancement
- Author
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Aayushi Tomar, Shivika Goyal, Yashvir Singh, Akanksha Negi, Agya Ram Verma, and Shefali Goswamy
- Subjects
Engineering ,Mean squared error ,0206 medical engineering ,SNR ,02 engineering and technology ,Hilbert–Huang transform ,HHT ,03 medical and health sciences ,MSE ,0302 clinical medicine ,Signal-to-noise ratio ,Electronic engineering ,lcsh:Science ,lcsh:Science (General) ,Cuckoo search ,Computer Science::Information Theory ,ECG ,ME ,business.industry ,Noise (signal processing) ,ANC ,General Medicine ,Filter (signal processing) ,020601 biomedical engineering ,MCS ,Filter design ,lcsh:Q ,business ,Algorithm ,MCS algorithm ,030217 neurology & neurosurgery ,lcsh:Q1-390 - Abstract
Summary In this work, the design of an adaptive noise canceller (ANC) filter is presented using modified cuckoo search (MCS) optimization technique. The proposed scheme is applied for de-noising of ECG signals. Our simulation results reveal that the ANC filter based on MCS algorithm provides superior performance than other optimization techniques used to enhance the ECG signal. The performance of ANC filter is compared with other reported algorithms by evaluating the fidelity parameters such as the signal to noise ratio (SNR), maximum error (ME) and mean square error (MSE). The proposed ANC filter design with MCS scheme gives 18% improvement in output SNR, 87% decrease in ME, and 85% reduction in MSE over the recently reported Hilbert Huang Transform (HHT) technique.
- Published
- 2016
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