Application of wavelet transform de-noising for neural cell based biosensor

Neural cell based biosensors, with neurons cultured on the semiconductor sensor chip,are suitable for long-term and non-invasive measurement of cell electrophysiological properties. They have broad prospects for biomedical applications. For biological signal is very weak,the collected signal is often difficult to satisfy the needs of the actual detection. In this study, wavelet de-noising was used to deal with extracellular electrophysiological signals of PC12 cells cultured on the surface of Light Addressable Potentiometric Sensors(LAPS). Signal was decomposed into wavelet coefficients at different levels by wavelet transform, obtaining threshold of every level. Based on the characteristics of coefficients in different levels, we dealt with them according to the threshold,acquiring new wavelet coefficients,and finally reconstructed the signal. It is found that the effective frequency is focused in the range of less than 2 kHz by the spectral analysis of the de-noised signal. The signal to noise rato is improved,indicating wavelet transform is an effective way to de-noise the signal for neural cell based biosensors.