Xianghong Cao, Xinyu Wang, Xin Geng^*, Donghui Wu, Houru An

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 385-408, 2024, DOI:10.32604/cmes.2024.046752

Abstract This study proposes a pose estimation-convolutional neural network-bidirectional gated recurrent unit (PSE-CNN-BiGRU) fusion model for human posture recognition to address low accuracy issues in abnormal posture recognition due to the loss of some feature information and the deterioration of comprehensive performance in model detection in complex home environments. Firstly, the deep convolutional network is integrated with the Mediapipe framework to extract high-precision, multi-dimensional information from the key points of the human skeleton, thereby obtaining a human posture feature set. Thereafter, a double-layer BiGRU algorithm is utilized to extract multi-layer, bidirectional temporal features from the human posture feature set, and a… More >

Xiaoyan Jiang^1,2, Zuojin Hu¹, Shuihua Wang², Yudong Zhang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 35-82, 2023, DOI:10.32604/cmes.2023.027676

Abstract Over the years, the continuous development of new technology has promoted research in the field of posture recognition and also made the application field of posture recognition have been greatly expanded. The purpose of this paper is to introduce the latest methods of posture recognition and review the various techniques and algorithms of posture recognition in recent years, such as scale-invariant feature transform, histogram of oriented gradients, support vector machine (SVM), Gaussian mixture model, dynamic time warping, hidden Markov model (HMM), lightweight network, convolutional neural network (CNN). We also investigate improved methods of CNN, such as stacked hourglass networks, multi-stage… More >

Tan Chen Tung¹, Uswah Khairuddin¹, Mohd Ibrahim Shapiai¹, Norhariani Md Nor^2,*, Mark Wen Han Hiew², Nurul Aisyah Mohd Suhaimie³

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1493-1508, 2023, DOI:10.32604/cmc.2023.029277

Abstract Dairy farm management is crucial to maintain the longevity of the farm, and poor dairy youngstock or calf management could lead to gradually deteriorating calf health, which often causes premature death. This was found to be the most neglected part among the management workflows in Malaysia and has caused continuous loss over the recent years. Calf posture recognition is one of the effective methods to monitor calf behaviour and health state, which can be achieved by monitoring the calf behaviours of standing and lying where the former depicts active calf, and the latter, passive calf. Calf posture recognition module is… More >

Taher M. Ghazal^1,2,*, Mohammad Kamrul Hasan¹, Siti Norul Huda Abdullah¹, Khairul Azmi Abubakkar¹, Mohammed A. M. Afifi²

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2579-2597, 2022, DOI:10.32604/cmc.2022.019706

Abstract Smart healthcare applications depend on data from wearable sensors (WSs) mounted on a patient’s body for frequent monitoring information. Healthcare systems depend on multi-level data for detecting illnesses and consequently delivering correct diagnostic measures. The collection of WS data and integration of that data for diagnostic purposes is a difficult task. This paper proposes an Errorless Data Fusion (EDF) approach to increase posture recognition accuracy. The research is based on a case study in a health organization. With the rise in smart healthcare systems, WS data fusion necessitates careful attention to provide sensitive analysis of the recognized illness. As a… More >