Yazeed Yasin Ghadi1, Mouazma Batool2, Munkhjargal Gochoo3, Suliman A. Alsuhibany4, Tamara al Shloul5, Ahmad Jalal2, Jeongmin Park6,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1037-1053, 2022, DOI:10.32604/cmc.2022.027422
Abstract Over the last decade, there is a surge of attention in establishing ambient assisted living (AAL) solutions to assist individuals live independently. With a social and economic perspective, the demographic shift toward an elderly population has brought new challenges to today’s society. AAL can offer a variety of solutions for increasing people’s quality of life, allowing them to live healthier and more independently for longer. In this paper, we have proposed a novel AAL solution using a hybrid bidirectional long-term and short-term memory networks (BiLSTM) and convolutional neural network (CNN) classifier. We first pre-processed the signal data, then used time-frequency… More >
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