This paper proposes an immersive training system for patients with hand dysfunction who can perform rehabilitation training independently. The system uses Leap Motion binocular vision sensors to collect human hand inf...This paper proposes an immersive training system for patients with hand dysfunction who can perform rehabilitation training independently. The system uses Leap Motion binocular vision sensors to collect human hand information, and uses the improved PCA<sub><img src="Edit_d6662636-9073-4fbd-855f-9a36e871d5a4.png" width="10" height="15" alt="" /></sub> (Principal Component Analysis) to perform data fusion on the real-time data collected by the sensor to obtain more hands with fewer principal components, and improve the stability and accuracy of the data. Immediately, the use of improved SVM<sub><img src="Edit_10c78725-e09e-4dcf-ae05-e21205df4acc.png" width="10" height="15" alt="" /></sub> (Support Vector Machine) and KNN<sub><img src="Edit_0ee97f55-2773-4b48-93b3-93f61aa25577.png" width="10" height="15" alt="" /></sub> (K-Nearest Neighbor Algorithm) for gesture recognition and classification is proposed to enable patients to perform rehabilitation training more effectively. Finally, the effective evaluation results of the rehabilitation effect of patients by the idea of AHP<sub><img src="Edit_70dd1964-28be-4137-afa5-9a184704f08e.png" width="10" height="15" alt="" /></sub> (Analytic Hierarchy Process) are taken as necessary reference factors for doctors to follow up treatment. Various experimental results show that the system has achieved the expected results and has a good application prospect.展开更多
Smoke is the main cause of fire death. In order to minimize the potential danger of smoke hazard, a rational VR based fire training simulator should fully consider all aspects of smoke hazard. In the simulator, the vi...Smoke is the main cause of fire death. In order to minimize the potential danger of smoke hazard, a rational VR based fire training simulator should fully consider all aspects of smoke hazard. In the simulator, the visualization of data based on FDS (Fire Dynamics Simulator) and FED fire dynamic data and volume rendering is further optimized, which can be effectively and quickly applied to virtual fire protection. In addition, a comprehensive smoke hazard assessment model based on FED and FED is established to assess the IHD value of different paths, which represents the safety of different paths, and can be used for evacuation or rescue in virtual training. Taking the case of campus fire drill as an experiment, the research shows the accuracy and effectiveness of smoke assessment based on FDS and FED model. The road force with the highest safety can be selected through the comprehensive model. So the assessment model is proved to be valuable.展开更多
文摘This paper proposes an immersive training system for patients with hand dysfunction who can perform rehabilitation training independently. The system uses Leap Motion binocular vision sensors to collect human hand information, and uses the improved PCA<sub><img src="Edit_d6662636-9073-4fbd-855f-9a36e871d5a4.png" width="10" height="15" alt="" /></sub> (Principal Component Analysis) to perform data fusion on the real-time data collected by the sensor to obtain more hands with fewer principal components, and improve the stability and accuracy of the data. Immediately, the use of improved SVM<sub><img src="Edit_10c78725-e09e-4dcf-ae05-e21205df4acc.png" width="10" height="15" alt="" /></sub> (Support Vector Machine) and KNN<sub><img src="Edit_0ee97f55-2773-4b48-93b3-93f61aa25577.png" width="10" height="15" alt="" /></sub> (K-Nearest Neighbor Algorithm) for gesture recognition and classification is proposed to enable patients to perform rehabilitation training more effectively. Finally, the effective evaluation results of the rehabilitation effect of patients by the idea of AHP<sub><img src="Edit_70dd1964-28be-4137-afa5-9a184704f08e.png" width="10" height="15" alt="" /></sub> (Analytic Hierarchy Process) are taken as necessary reference factors for doctors to follow up treatment. Various experimental results show that the system has achieved the expected results and has a good application prospect.
文摘Smoke is the main cause of fire death. In order to minimize the potential danger of smoke hazard, a rational VR based fire training simulator should fully consider all aspects of smoke hazard. In the simulator, the visualization of data based on FDS (Fire Dynamics Simulator) and FED fire dynamic data and volume rendering is further optimized, which can be effectively and quickly applied to virtual fire protection. In addition, a comprehensive smoke hazard assessment model based on FED and FED is established to assess the IHD value of different paths, which represents the safety of different paths, and can be used for evacuation or rescue in virtual training. Taking the case of campus fire drill as an experiment, the research shows the accuracy and effectiveness of smoke assessment based on FDS and FED model. The road force with the highest safety can be selected through the comprehensive model. So the assessment model is proved to be valuable.
