In order to reduce nursing intensity and improve freedom of the elderly and the disabled, a multi-function nursing wheelchair which can switch chair to bed and realize many kinds of posture transformation is designed....In order to reduce nursing intensity and improve freedom of the elderly and the disabled, a multi-function nursing wheelchair which can switch chair to bed and realize many kinds of posture transformation is designed. This paper introduces the mechanical structure design （position adjustment mechanism and variable wheelbase mechanism） and control design of posture transformation unit of multifunctional nursing wheelchair.展开更多
Cardiovascular disease is the leading cause of death globally.This disease causes loss of heart muscles and is also responsible for the death of heart cells,sometimes damaging their functionality.A person’s life may ...Cardiovascular disease is the leading cause of death globally.This disease causes loss of heart muscles and is also responsible for the death of heart cells,sometimes damaging their functionality.A person’s life may depend on receiving timely assistance as soon as possible.Thus,minimizing the death ratio can be achieved by early detection of heart attack(HA)symptoms.In the United States alone,an estimated 610,000 people die fromheart attacks each year,accounting for one in every four fatalities.However,by identifying and reporting heart attack symptoms early on,it is possible to reduce damage and save many lives significantly.Our objective is to devise an algorithm aimed at helping individuals,particularly elderly individuals living independently,to safeguard their lives.To address these challenges,we employ deep learning techniques.We have utilized a vision transformer(ViT)to address this problem.However,it has a significant overhead cost due to its memory consumption and computational complexity because of scaling dot-product attention.Also,since transformer performance typically relies on large-scale or adequate data,adapting ViT for smaller datasets is more challenging.In response,we propose a three-in-one steam model,theMulti-Head Attention Vision Hybrid(MHAVH).Thismodel integrates a real-time posture recognition framework to identify chest pain postures indicative of heart attacks using transfer learning techniques,such as ResNet-50 and VGG-16,renowned for their robust feature extraction capabilities.By incorporatingmultiple heads into the vision transformer to generate additional metrics and enhance heart-detection capabilities,we leverage a 2019 posture-based dataset comprising RGB images,a novel creation by the author that marks the first dataset tailored for posture-based heart attack detection.Given the limited online data availability,we segmented this dataset into gender categories(male and female)and conducted testing on both segmented and original datasets.The training accuracy of our model reached an impressive 99.77%.Upon testing,the accuracy for male and female datasets was recorded at 92.87%and 75.47%,respectively.The combined dataset accuracy is 93.96%,showcasing a commendable performance overall.Our proposed approach demonstrates versatility in accommodating small and large datasets,offering promising prospects for real-world applications.展开更多
According to the bedridden patient＇s physical condition, one kind of electric nursing bed which can be used in the smart home environment and realize many＇ kinds of posture transformation. This paper introduces the ...According to the bedridden patient＇s physical condition, one kind of electric nursing bed which can be used in the smart home environment and realize many＇ kinds of posture transformation. This paper introduces the mechanical system design of the electric nursing bed and the method of integration with the smart home environment, designs the combined bed board and the mechanical structure of posture transformation, remote controlling equipments in the smart home environment.展开更多
基金Supported by NSFC(61170005)Special Topic of the Ministry of Education about Humanities and Social Sciences(12JDGC007)+2 种基金University Quality Project of Anhui Province(20100096)Graduate Education Reform Project of Hefei University of Technology(2011yjs003)National College Students' Training Project of Innovation and Entrepreneurship(201210359078)
文摘In order to reduce nursing intensity and improve freedom of the elderly and the disabled, a multi-function nursing wheelchair which can switch chair to bed and realize many kinds of posture transformation is designed. This paper introduces the mechanical structure design （position adjustment mechanism and variable wheelbase mechanism） and control design of posture transformation unit of multifunctional nursing wheelchair.
基金Researchers Supporting Project Number(RSPD2024R576),King Saud University,Riyadh,Saudi Arabia。
文摘Cardiovascular disease is the leading cause of death globally.This disease causes loss of heart muscles and is also responsible for the death of heart cells,sometimes damaging their functionality.A person’s life may depend on receiving timely assistance as soon as possible.Thus,minimizing the death ratio can be achieved by early detection of heart attack(HA)symptoms.In the United States alone,an estimated 610,000 people die fromheart attacks each year,accounting for one in every four fatalities.However,by identifying and reporting heart attack symptoms early on,it is possible to reduce damage and save many lives significantly.Our objective is to devise an algorithm aimed at helping individuals,particularly elderly individuals living independently,to safeguard their lives.To address these challenges,we employ deep learning techniques.We have utilized a vision transformer(ViT)to address this problem.However,it has a significant overhead cost due to its memory consumption and computational complexity because of scaling dot-product attention.Also,since transformer performance typically relies on large-scale or adequate data,adapting ViT for smaller datasets is more challenging.In response,we propose a three-in-one steam model,theMulti-Head Attention Vision Hybrid(MHAVH).Thismodel integrates a real-time posture recognition framework to identify chest pain postures indicative of heart attacks using transfer learning techniques,such as ResNet-50 and VGG-16,renowned for their robust feature extraction capabilities.By incorporatingmultiple heads into the vision transformer to generate additional metrics and enhance heart-detection capabilities,we leverage a 2019 posture-based dataset comprising RGB images,a novel creation by the author that marks the first dataset tailored for posture-based heart attack detection.Given the limited online data availability,we segmented this dataset into gender categories(male and female)and conducted testing on both segmented and original datasets.The training accuracy of our model reached an impressive 99.77%.Upon testing,the accuracy for male and female datasets was recorded at 92.87%and 75.47%,respectively.The combined dataset accuracy is 93.96%,showcasing a commendable performance overall.Our proposed approach demonstrates versatility in accommodating small and large datasets,offering promising prospects for real-world applications.
基金Supported by Special Topic of the Ministry of Education about Humanities and Social Sciences(12JDGC007)University Quality Project of Anhui Province(20100096)+2 种基金Graduate Education Reform Project of Hefei University of Technology(2011yjs003)National College Students' Training Project of Innovation and Entrepreneurship(201210359078)University of Anhui Provincial Natural Science Research Project(KJ2011ZD01)
文摘According to the bedridden patient＇s physical condition, one kind of electric nursing bed which can be used in the smart home environment and realize many＇ kinds of posture transformation. This paper introduces the mechanical system design of the electric nursing bed and the method of integration with the smart home environment, designs the combined bed board and the mechanical structure of posture transformation, remote controlling equipments in the smart home environment.
