Before revision:  Our experimental results show that adapting the node setup to the workload at runtime can save up to 50\% power consumption and a quantized neural network reaches an accuracy value higher than 98 \% for arrhythmia disorders detection on MIT-BIH Arrhythmia dataset.
After revision:  Our experimental results show that adapting the node setup to the workload at runtime can save up to 50\% power consumption . Our optimized and quantized neural network reaches an accuracy value higher than 98 \% for arrhythmia disorders detection on MIT-BIH Arrhythmia dataset.