Since entering the era of Industry 4.0,the concept of Healthcare 4.0 has also been put forward and explored by researchers.How to use Information Technology(IT)to better serve people’s healthcare is one of the most f...Since entering the era of Industry 4.0,the concept of Healthcare 4.0 has also been put forward and explored by researchers.How to use Information Technology(IT)to better serve people’s healthcare is one of the most featured emerging directions in the academic circle.An important field of Healthcare 4.0 research is the reliability engineering of healthcare service.Because healthcare systems often affect the health and even life of their users,developers must be very cautious in the design,development,and operation of these healthcare systems and services.The problems to be solved include the reliability of business process,system functions,and personal healthcare data.The Functional Resonance Analysis Method(FRAM)has been applied in reliability engineering for safety-critical systems in available studies,using both qualitative and quantitative approaches.However,the method has not been applied in the field of digital healthcare services development.Therefore,to narrow the gap,we present in this paper a semi-quantitative functional resonance analysis method to develop reliable healthcare services for diabetics.Moreover,this paper has tried to improve the reliability design of the service-oriented architecture(SOA)of traditional insulin pump therapy by system thinking.展开更多
The original temporal clustering analysis (OTCA) is an effective technique for obtaining brain activation maps when the timing and location of the activation are completely unknown, but its deficiency of sensitivity i...The original temporal clustering analysis (OTCA) is an effective technique for obtaining brain activation maps when the timing and location of the activation are completely unknown, but its deficiency of sensitivity is exposed in processing brain activation signal which is relatively weak. The time slice analysis method based on OTCA is proposed considering the weakness of the functional magnetic resonance imaging (fMRI) signal of the rat model. By dividing the stimulation period into several time slices and analyzing each slice to detect the activated pixels respectively after the background removal, the sensitivity is significantly improved. The inhibitory response in the hypothalamus after glucose loading is detected successfully with this method in the experiment on rat. Combined with the OTCA method, the time slice analysis method based on OTCA is effective on detecting when, where and which type of response will happen after stimulation, even if the fMRI signal is weak.展开更多
文摘Since entering the era of Industry 4.0,the concept of Healthcare 4.0 has also been put forward and explored by researchers.How to use Information Technology(IT)to better serve people’s healthcare is one of the most featured emerging directions in the academic circle.An important field of Healthcare 4.0 research is the reliability engineering of healthcare service.Because healthcare systems often affect the health and even life of their users,developers must be very cautious in the design,development,and operation of these healthcare systems and services.The problems to be solved include the reliability of business process,system functions,and personal healthcare data.The Functional Resonance Analysis Method(FRAM)has been applied in reliability engineering for safety-critical systems in available studies,using both qualitative and quantitative approaches.However,the method has not been applied in the field of digital healthcare services development.Therefore,to narrow the gap,we present in this paper a semi-quantitative functional resonance analysis method to develop reliable healthcare services for diabetics.Moreover,this paper has tried to improve the reliability design of the service-oriented architecture(SOA)of traditional insulin pump therapy by system thinking.
基金the National Natural Science Foundation of China (30370432)
文摘The original temporal clustering analysis (OTCA) is an effective technique for obtaining brain activation maps when the timing and location of the activation are completely unknown, but its deficiency of sensitivity is exposed in processing brain activation signal which is relatively weak. The time slice analysis method based on OTCA is proposed considering the weakness of the functional magnetic resonance imaging (fMRI) signal of the rat model. By dividing the stimulation period into several time slices and analyzing each slice to detect the activated pixels respectively after the background removal, the sensitivity is significantly improved. The inhibitory response in the hypothalamus after glucose loading is detected successfully with this method in the experiment on rat. Combined with the OTCA method, the time slice analysis method based on OTCA is effective on detecting when, where and which type of response will happen after stimulation, even if the fMRI signal is weak.
