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Pressure Image Recognition of Lying Positions Based on Multi-feature value Regularized Extreme Learning Algorithm

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S.W. Lee, S. Sarp, D.J. Jeon and J.H. Kim, Smart water grid: the future water management platform, Desal. Water Treat., 2015.55 (2):pp.339–346 Search in Google Scholar

R.S. Baranowski. K Kalin. Positional sleep-disordered breathing in patients with arrhythmia. Should we advise our patients to avoid supine position during sleep. Journal of Electro cardiology, 2019, 57:138-142. Search in Google Scholar

K. Spiegel, K. Knutson, R. Leproult. Sleep loss: A novel risk factor for insulin resistance and Type 2 diabetes. Journal of Applied Physiology, 2005, 99(5):2008-2019. Search in Google Scholar

Z. Liu. A Method to Recognize Sleeping Position Using an CNN Model Based on Human Body Pressure Image. IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS): IEEE, 2019:219-224. Search in Google Scholar

T. Ruan, C. Liu, K.Y. Yin. Pattern Recognition of Human Hand Movements Based on Surface Electromyography Signals for Amputees. Journal of Terahertz Science and Electronic Information Technology, 2020:1-6. Search in Google Scholar

Y. Zhang, C.M. Xia, J.Z. Xie. Comparative Study of Features and Classification Algorithms in Mechanomyography Based Head Movement Classification. Journal of Data Acquisition and Processing, 2020, 35(04):711-719. Search in Google Scholar

M. Masek, C.P. Lam, C. Tranthim-Fryer, et al. Sleep monitor: A tool for monitoring and categorical scoring of lying position using 3D camera data. Softwarex, 2018, 7:341-346. Search in Google Scholar

L. Xia, C.C. Chen, J. Aggarwal. View invariant human action recognition using histograms of 3D joints. IEEE Computer Society Conference on Computer Vision &. Pattern Recognition Workshops. Providence: IEEE, 2012:20-27. Search in Google Scholar

O.D. Lara, M. Labrador. A Survey on Human Activity Recognition using Wearable Sensors. IEEE Commun Surv Tutorials. 2013;15(3):1192-209. Search in Google Scholar

S. Ranasinghe, A. MacHot F, H.C. Mayr. A review on applications of activity recognition systems with regard to performance and evaluation. Int J Distrib Sens Networks. 2016;12(8). Search in Google Scholar

N. Qamar, N. Siddiqui, M. Ehatisham-Ul-Haq, et al. An Approach towards Position Independent Human Activity Recognition Model based on Wearable Accelerometer Sensor. Procedia Computer Science, 2020, 177:196-203. Search in Google Scholar

D.Y. Geng, J.J. Dong, Q. Ning, et al. Research on Sleeping Posture Recognition Method Based on Multi-channel Piezoelectric Thin-film Sensor. Modern Electronics Technique, 2020, 43(20):5-8.. Search in Google Scholar

Z.B. Ren, Y. Li, S.J. Guo, et al. Sleep Posture Pressure Image Recognition Based on Fuzzy-rough Set Theory. Computer Engineering and Applications, 2018, 54(03):172-177. Search in Google Scholar

S. Shukla, B.S. Raghuwanshi. Online sequential class-specific extreme learning machine for binary imbalanced learning. Neural Networks, 2019, 119:235-248. Search in Google Scholar

H.C. Sun. et al. Monitoring Driving Psychological Fatigue Through Unconstrained Heartbeat Signal Extraction by Using Pressure Sensor Array. IEEE Access, 2020.8:p. 22193-22202. Search in Google Scholar

G. Varol, A.A. Salah. Efficient large-scale action recognition in videos using extreme learning machines. Expert Systems with Applications, 2015. Search in Google Scholar

X. Cui, P. Zhang, J. Zhao, et al. Study on Inspection of Corn Seed Breakage Based on Machine Vision. Agricultural Mechanization Research, 2019, 41(02):28-33+84. Search in Google Scholar

Y. Jiang, S. Deng, H. Sun, et al. Unconstrained Monitoring Method for Heartbeat Signals Measurement using Pressure Sensors Array. Sensors, 2019, 19(2). Search in Google Scholar

X. Chen, M. Koskela. Skeleton-based action recognition with extreme learning machines. Neurocomputing, 2015, 149(pt.a):387-396. Search in Google Scholar

Y.Q. Zhang. Optimized Human Movement Gesture Recognition Algorithm Based on Hu Invariant Moment Features. Computer Science, 2014, 41(03):306-309. Search in Google Scholar

eISSN:
2444-8656
Langue:
Anglais
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Volume Open
Sujets de la revue:
Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics