Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This work describes a Virtex-II implementation of a custom DSP for QRS-Complex detection, ECG signal analysis and data compression for optimum transmission and storage. For QRS-Complex detection  introduce a custom architecture based on a modification of the Hamilton-Tompkins (HT) algorithm oriented to area saving.  also use biorthogonal wavelet transform for ECG signal compression and main ECG parameters estimation. In contrast with previously published works, our modified version of the HT algorithm offers best performance (a 99% of QRS-detection over normalized noisy ECGs). Moreover, a compression ratio of 20:1 is obtained when the wavelet-based engine is running. Results have been successfully verified by using a combination of MATLAB with SystemGen, Modelsim and a FPGA PCI-based Card (AlphaData ADM-XRC-II). The QRS-complex detector and compressor requires minimum area resources in term of LUT and registers, allowing a custom DSP as coprocessor in a SoC for biomedical applications.
['Marcos M. Peiro', 'Francisco Sánchez Ballester', 'Guillermo Paya', 'Jorge Belenguer', 'Ricardo J. Colom', 'Rafael Gadea']
I am writing a research paper on a idea FPGA custom DSP for ECG signal analysis and compression
[{"from": "human", "value": "I am writing a research paper on a idea FPGA custom DSP for ECG signal analysis and compression"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This work describes a Virtex-II implementation of a custom DSP for QRS-Complex detection, ECG signal analysis and data compression for optimum transmission and storage. For QRS-Complex detection  introduce a custom architecture based on a modification of the Hamilton-Tompkins (HT) algorithm oriented to area saving.  also use biorthogonal wavelet transform for ECG signal compression and main ECG parameters estimation. In contrast with previously published works, our modified version of the HT algorithm offers best performance (a 99% of QRS-detection over normalized noisy ECGs). Moreover, a compression ratio of 20:1 is obtained when the wavelet-based engine is running. Results have been successfully verified by using a combination of MATLAB with SystemGen, Modelsim and a FPGA PCI-based Card (AlphaData ADM-XRC-II). The QRS-complex detector and compressor requires minimum area resources in term of LUT and registers, allowing a custom DSP as coprocessor in a SoC for biomedical applications."}]