1 research outputs found
Ultra Low-Power and Real-time ECG Classification Based on STDP and R-STDP Neural Networks for Wearable Devices
This paper presents a novel ECG classification algorithm for real-time
cardiac monitoring on ultra low-power wearable devices. The proposed solution
is based on spiking neural networks which are the third generation of neural
networks. In specific, we employ spike-timing dependent plasticity (STDP), and
reward-modulated STDP (R-STDP), in which the model weights are trained
according to the timings of spike signals, and reward or punishment signals.
Experiments show that the proposed solution is suitable for real-time
operation, achieves comparable accuracy with respect to previous methods, and
more importantly, its energy consumption is significantly smaller than previous
neural network based solutions.Comment: Published in IEEE Transactions on Biomedical Circuits and Systems
(TBioCAS), 201