Implementation of Fast Fourier Transform on Body Sensor Networks

Body Sensor Networks (BSN) is a low-power wireless sensing technology for healthcare applications. Low-power wireless sensing is achieved by the integration of various miniaturized low-power on-chip devices, and is termed Body Sensor Node. The heart of the Body Sensor Node is an ultra low power mixed signal microcontroller. These mixed signal microcontrollers are typically resource-constrained - limited computational speed and memory is available. As a result, complex signal processing algorithms are unlikely to be implemented on these resource-constrained platforms. In this paper, we benchmarked a Fast Fourier Transform (FFT) algorithm, on a Texas Instruments MSP430F1612. The benchmarking results are reported and discussed.