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-A powerful approach to the characterization of cellular electrical activity is electrical recording from cells or living tissues. The human central and / or peripheral nervous system has been a subject of study and fascination of the neuroscience and biomedical engineering communities for many decades. In this paper, we propose a new approach to feed implantable neural recording system, which based on extracting electrical power from human tissue warmth in order to supply a biomedical neural recording system. The major issue to overcome, in the design of a system that is aimed at being implant into the human body, is having a low power consumption, low noise circuit and small dimension to minimize tissue damage.

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In this paper, we use Consensus version of the matching pursuit algorithm (CMP) which fit to the noisy Evoked Potential signal persistent in all responses (trial). The Evoked Potential EP is a specific wave resulted from a stimulus. This research is performed in a highly redundant timefrequency dictionary of Gabor functions.For phase-locked Evoked Potential trials, we conclude that the morphology of EP signal obtained by a reconstructed signal can be very well explained with a good quality of energy ratio factor (QR). However for a noisy and jitter EP, we couldn't optimally reconstruct our original data due to random atoms of CMP dictionary. So our strategy consists to select only the significant atoms to rebuild an EP signal. Using this test, we can reach a good QR ratio.