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홍승홍 대한의용생체공학회 1989 의공학회지 Vol.10 No.2
An electrical stimulator was designed to induce locomotion for paraplegic patients caused by central nervous system injury. Optimal stimulus parameters, which can minimize muscle fatigue and can achieve effective muscle contraction were determined in slow and fast muscles in Sprague-Dawley rats. Stimulus patterns of our stimulator were designed to simulate electromyographic activity monitored during locomotion of normal subjects. Muscle types of the lower extremity were classified according to their mechanical property of contraction, which are slow muscle (msoleus m.) and fast muscle (medial gastrocneminus m., rectus femoris m., vastus lateralis m.). Optimal parameters of electrical stimulation for slow muscles were 20 Hz, 0.2 ms square pulse. For fast muscle, 40 Hz, 0.3 ms square pulse was optimal to produce repeated contraction. Higher stimulus intensity was required when synergistic muscles were stimulated simultaneously than when they were stimulated individually. Electrical stimulation for each muscle was designed to generate bipedal locomotion, so that individual muscles alternate contraction and relaxation to simulate stance and swing phases. Portable electrical stimulator with 16 channels built in microprocessor was constructed and applied to paraplegic patients due to lumbar cord injury. The electrical stimulator restored partially gait function in paraplegic patients.
洪勝弘 光云大學校 1976 論文集 Vol.5 No.-
The object of this paper is to automate the digital data acquisition and the boundary detection in liver scintigram using the inexpensive input equipments. The digital data acquisitition and the conversion of visual information to an electrical signal were performed with a system of conventional vidicon camera, a video tape recorder and a scan conversion memory. The threshold decision based on statistical principles was developed to detect boundary in liver scintigram. A image of liver scintigram was divided the entire picture into 64 small regions. The kurtosis and variances for each small region were used as factor select the histogram do occur mear the boundary. For these selected density histograms the thresholds were computed according the method of maximum-likelihood ratio which minimizes the probability of misclassification. Therefore, first the author demonstrated the applicability of boundary detection, and second, proved good agreement with human recognition, and were considered to be useful for diagnoses. Finally, the author demonstrated the dynamic study performed using with dynamic image processing system. Counts falling within the selected area can be defined and the data therein can be recorded as a transit time activity histogram.