Yuesheng Zhao1, Xiaoling Wang1,*, Yutong Luo2,*, Muhammad Shamrooz Aslam3
CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3325-3347, 2023, DOI:10.32604/cmc.2023.040528
Abstract With the rapid advancement of wearable devices, Human Activities Recognition (HAR) based on these devices has emerged as a prominent research field. The objective of this study is to enhance the recognition performance of HAR by proposing an LSTM-1DCNN recognition algorithm that utilizes a single triaxial accelerometer. This algorithm comprises two branches: one branch consists of a Long and Short-Term Memory Network (LSTM), while the other parallel branch incorporates a one-dimensional Convolutional Neural Network (1DCNN). The parallel architecture of LSTM-1DCNN initially extracts spatial and temporal features from the accelerometer data separately, which are then concatenated and fed into a fully… More >
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