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Clinical detection and movement recognition of neuro signals
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作者 张晓文 杨煜普 +5 位作者 许晓鸣 胡天培 高忠华 张健 陈统一 陈中伟 《Journal of Zhejiang University-Science B(Biomedicine & Biotechnology)》 SCIE CAS CSCD 2005年第4期272-279,共8页
Neuro signal has many more advantages than myoelectricity in providing information for prosthesis control, and can be an ideal source for developing new prosthesis. In this work, by implanting intrafascicular electrod... Neuro signal has many more advantages than myoelectricity in providing information for prosthesis control, and can be an ideal source for developing new prosthesis. In this work, by implanting intrafascicular electrode clinically in the amputee’s upper extremity, collective signals from fascicules of three main nerves (radial nerve, ulnar nerve and medium nerve) were suc- cessfully detected with sufficient fidelity and without infection. Initial analysis of features under different actions was performed and movement recognition of detected samples was attempted. Singular value decomposition features (SVD) extracted from wavelet coefficients were used as inputs for neural network classifier to predict amputee’s movement intentions. The whole training rate was up to 80.94% and the test rate was 56.87% without over-training. This result gives inspiring prospect that col- lective signals from fascicules of the three main nerves are feasible sources for controlling prosthesis. Ways for improving accu- racy in developing prosthesis controlled by neuro signals are discussed in the end. 展开更多
关键词 Neuro signal Intrafascicular electrode detection movement recognition
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An intelligent self-powered life jacket system integrating multiple triboelectric fiber sensors for drowning rescue
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作者 Yiping Zhang Chengyu Li +9 位作者 Chuanhui Wei Renwei Cheng Tianmei Lv Junpeng Wang Cong Zhao Zhaoyang Wang Fangming Li Xiao Peng Minyi Xu Kai Dong 《InfoMat》 SCIE CSCD 2024年第5期96-109,共14页
The inherent unpredictability of the maritime environment leads to low rates of survival during accidents.Life jackets serve as a crucial safety measure in underwater environments.Nonetheless,most conventional life ja... The inherent unpredictability of the maritime environment leads to low rates of survival during accidents.Life jackets serve as a crucial safety measure in underwater environments.Nonetheless,most conventional life jackets lack the capability to monitor the wearer's underwater body movements,impeding their effectiveness in rescue operations.Here,we present an intelligent self-powered life jacket system(SPLJ)composed of a wireless body area sensing network,a set of deep learning analytics,and a human condition detection platform.Six coaxial core-shell structure triboelectric fiber sensors with high sensitivity,stretchability,and flexibility are integrated into this system.Addi-tionally,a portable integrated circuit module is incorporated into the SPLJ to facilitate real-time monitoring of the wearer's movement.Moreover,by leveraging the deep-learning-assisted data analytics and establishing a robust correlation between the wearer's movements and condition,we have developed a comprehensive system for monitoring drowning individuals,achieving an outstanding recognition accuracy of 100%.This groundbreaking work intro-duces a fresh approach to underwater intelligent survival devices,offering promising prospects for advancing underwater smart wearable devices in rescue operations and the development of ocean industry. 展开更多
关键词 deep learning intelligent life jackets movement recognition SELF-POWERED triboelectric fiber sensors
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