On using compressed sensing for efficient transmission & storage of electric organ discharge

In this paper, we present a compressed sensing based framework for a wireless sensor based biological sensing system for recording the frequency of fish electric organ discharge. We investigate the trade-offs between the parameters of compressed sensing, such as sampling matrix, reconstructed signal´s signal to noise ratio, and compression ratio. The measured results show that our framework can be used to reduce the transmitted data size by 70% (3×) while maintaining at least 10 dB signal to noise ratio for the reconstructed time domain frequency data. This size reduction with acceptable reconstructed signal quality will help reduce transmission energy and storage requirements for long-term sensing experiments, thus enabling the use of small and low power wireless sensors.