Photoplethysmogram (PPG) signal utilize the light-based method to sense the blood-flow-rate as controlled by the actions of heart’s pumping. It is extensively utilized in the healthcare with application ranging from the pulse oximetry in the serious care units to the heart rate (HR) measurement in the wearable devices. This paper introduces an algorithm known as BCAE-FS (Bio-Signal Compression using Auto-Encoder and Feature Selection) which is a combined generative method, which incorporates Feature Selection(FS) and Auto-Encoder(AE) together. At the end, our proposed algorithm can differentiate the signals which are more significant and important as one unit over the irrelevant one to get very effective feature for the classification task. Our method not only accomplishes the FS on the learned level of higher feature, but also endows the AE to construct the discriminative units. Our experimental results outperforms the other various existing compression methods.
Volume 12 | 01-Special Issue
Pages: 583-592
DOI: 10.5373/JARDCS/V12SP1/20201107