  FFT algorithm is one of the most applied algorithmsin digital signal
processing. Digital signal processing hasgradually become important in
biomedical application. Herehardware implementation of FFTs have found useful
appli-cations for bio-wearable devices. However, for these devices, low-power
and low-area are of utmost importance.In this report, we investigate a
sub-structure of decimation-in-frequency (DIF) FFT where a number of sub-bands
areof interest to us. Specifically, we divide the range of frequencies into 8
sub-bands (0-7) and calculate 4 of them( 1,2,5,6). We show that using concepts
likepushingandradix22, the number of complex multiplications can be
dras-tically reduced for 16-point, 32-point and 64-point FFTswhile computing
those specific bands. Later, we also extendit toN= 2n-point FFT based on
optimized 64-point FFTstructure. The number of complex multiplications is
furtherreduced usingmerge-FFT. Our results show that the numberof
multiplications (and hence power) can be reduced greatlyusing our optimized
structure compared to an unoptimizedstructure. This can find application in
biomedical signal processing specifically while computingp ower spectral
density of a physiological time series where reducing computational power is of
utmost importance
