Cranial PPG sensor is designed to capture the signal due to blood flow variation in cranial mask for different activity. Various parameters are considered in the designing of optical sensor, those are source wavelength, photodetector and the type of excitation.  The designed PPG sensor is used to capture the cranial PPG signal during the eye blinking activity. The analysis is performed by using wavelet domain method and Mean square spectrum. The result shows that the designed sensor can be used for brain mapping noninvasively. MSS (Mean square spectrum) reflects the power in the signal at a given frequency. The Mean Square Spectrum of a signal is the fourier transform of that signal's autocorrelation. The mean square spectrum based analysis of oxy and deoxyhaemoglobin can be used for brain mapping using optical sensor. During brain functioning as blood flow increases oxyhaemoglobin increases and deoxyhaemoglobin decreases this can be detected using proposed system. A six level wavelet decomposition of CPPG signal is performed using Daubechies 9 and statistical features are calculated. Wavelet analysis shows that D3-D1 scales consists of predominantly the noise part of the signal. The difference between the statistical parameters of CPPG signal for A6 and D6 level differ during rest and activity. The other detail subbands contain the noise part of the signal and hence not considered for calculation. These features can be used for classifying the activated and non activated region in prefrontal lobe.  The system is related with the fMRI the second brain mapping technique.

Keywords: Discrete cosine transform (DCT), CPPG( Cranial Photoplethysmography), Reflectance type, MSS(Mean Square Spectrum), Wavelet analysis.