Adaptive sensing of ECG signals using R-R interval prediction

There is growing demand for systems consisting of tiny sensor nodes powered with small batteries that acquire electrocardiogram (ECG) data and wirelessly transmit the data to remote base stations or mobile phones continuously over a long period. Conserving electric power in the wireless sensor nodes (WSNs) is essential in such systems. Adaptive sensing is promising for this purpose since it can reduce the energy consumed not only for data transmission but also for sensing. However, the basic method of adaptive sensing, referred to here as “plain adaptive sensing,” is not suitable for ECG signals because it sometimes capture the R waves defectively. We introduce an improved adaptive sensing method for ECG signals by incorporating R-R interval prediction. Our method improves the characteristics of ECG compression and drastically reduces the total energy consumption of the WSNs.