@inproceedings{61893d6236f94a7b8fbcab2bf4ec5112,
title = "Affordable low complexity heart/brain monitoring methodology for remote health care",
abstract = "![CDATA[This paper introduces a dual-mode low complex on-chip methodology for processing of ECG (Electrocardiogram) and EEG (Electroencephalography) signals, wherein based on the input switch the architecture can be dynamically configured to operate either as an ECG bio-marker or EEG signal de-noising system. In both the modes the signal processing technique depends on the output of the DWT (Discrete Wavelet Transform), hence a low complex methodology has been developed in which both ECG and EEG processing blocks sharing the same DWT block resulting in low area and low power consumption. The integrated ECG and EEG methodology has been implemented in Matlab, for verifying the ECG processing block the ECG database is taken from MIT-BIH PTBDB and IITH DB, similarly for EEG processing block the EEG signals are taken from PhysioNet database. The outcome of methodology in Matlab is equal to the results obtained from individual ECG and EEG blocks.]]",
keywords = "electrocardiography, electroencephalography, signal processing",
author = "Naresh Vemishetty and Pranit Jadhav and Bhagyaraja Adapa and Amit Acharyya and Rajalakshmi Pachamuthu and Naik, {Ganesh R.}",
year = "2015",
doi = "10.1109/EMBC.2015.7319534",
language = "English",
isbn = "9781424492718",
publisher = "IEEE",
pages = "5082--5085",
booktitle = "Biomedical Engineering: A Bridge to Improve the Quality of Health Care and the Quality of Life: Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2015), Milano, Italy, 25-29 August 2015",
note = "IEEE Engineering in Medicine and Biology Society. Annual Conference ; Conference date: 25-08-2015",
}