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MoS2 nanoflowers and PEDOT:PSS nanocomposite enabling wearable dual-mode pressure sensors Journal article
Wang, Feng Ming, Yang, Wei Jia, Ma, Ke, Shen, Geng Zhe, Su, Dao Jian, Li, Bai Jun, Wang, Shuang Peng, Qin, Bo Long, Zhang, Chi, Xin, Yue, Cao, Xiao Bing, He, Xin. MoS2 nanoflowers and PEDOT:PSS nanocomposite enabling wearable dual-mode pressure sensors[J]. Science China Technological Sciences, 2024, 67(6), 1737-1747.
Authors:  Wang, Feng Ming;  Yang, Wei Jia;  Ma, Ke;  Shen, Geng Zhe;  Su, Dao Jian; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:4.4/4.3 | Submit date：2024/07/04
Force-sensitive Sensor  Mos2/pedot:Pss Nanocomposite  Multi-scaled Microstructure  Object Grasping Recognition  Physiological Signals Monitoring  
Emotion recognition based on multimodal physiological signals using spiking feed-forward neural networks Journal article
Yang, Xudong, Yan, Hongli, Zhang, Anguo, Xu, Pan, Pan, Sio Hang, Vai, Mang I., Gao, Yueming. Emotion recognition based on multimodal physiological signals using spiking feed-forward neural networks[J]. Biomedical Signal Processing and Control, 2024, 91, 105921.
Authors:  Yang, Xudong;  Yan, Hongli;  Zhang, Anguo;  Xu, Pan;  Pan, Sio Hang; et al.
Favorite | TC[WOS]:4 TC[Scopus]:3  IF:4.9/4.9 | Submit date：2024/05/16
Emotion Recognition  Feature Extraction  Multimodal Physiological Signals  Spiking Feed-forward Neural Networks  Time Series  Wearable Wristbands  
Recent advances in nanogenerators-based flexible electronics for electromechanical biomonitoring Review article
2021
Authors:  Zhaoyang Li;  Yong Cui;  Junwen Zhong
Favorite | TC[WOS]:27 TC[Scopus]:30  IF:10.7/9.9 | Submit date：2022/08/31
Piezoelectric  Electrostatic  Nanogenerator  Physiological Signals  
Prediction Indicators for Acute Exacerbations of Chronic Obstructive Pulmonary Disease by Combining Non-linear analyses and Machine Conference paper
Jin, Yu, Zhang, Teng, Cao, Zhixin, Zhao, Na, Chen, Chang, Wang, Dandan, Lei, Kuan Cheok, Leng, Dongliang, Zhang, Xiaohua Douglas. Prediction Indicators for Acute Exacerbations of Chronic Obstructive Pulmonary Disease by Combining Non-linear analyses and Machine[C], 2019, 2515-2521.
Authors:  Jin, Yu;  Zhang, Teng;  Cao, Zhixin;  Zhao, Na;  Chen, Chang; et al.
Favorite | TC[WOS]:5 TC[Scopus]:5 | Submit date：2022/04/15
Acute Exacerbations  Chronic Obstructive Pulmonary Disease  Home Telehealth  Machine Learning  Non-linear Analysis  Physiological Signals