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Evidence-based apply in principal health-related in the managerial perspective : a nationwide survey.
Further, the developed algorithm was effectively used to control the driving function to assist the walking, sitting-standing, and climbing up-down the step activities in daily life. CONCLUSIONS The movement intention detection function for users developed in this paper can be used to effectively control a rehabilitative training system for patients with hemiplegia to improve gait movement and posture balance, thereby improving their function of activities of daily living.BACKGROUND A two-hospital patient referral problem intends to calculate an optimal value of referral patients between two hospitals and to evaluate whether or not the current number of referral patients is too low. OBJECTIVE The goal of this study is to develop a simulation-based optimization algorithm to find the optimal referral between two hospitals with the unfixed daily patient referral policy. METHODS This study applied system simulation and a bat algorithm (BA) to build a simulation model in accordance with the status of the two hospitals case and to calculate an optimal value of daily referral patients. RESULTS Based on the 20 test instances, we verified the stability of this algorithm. The results show that the average magnetic resonance imaging (MRI) patient wait time reduced from 16 days to eight days. The hospital should increase the average total monthly MRI referral patients to 370 under the limitation of the daily referral patients to 25. CONCLUSIONS This research investigated the two-hospital patient referral problems. We conducted and analyzed a simulation model and improved the case hospital's conditions, enhancing the quality of its medical care. Idasanutlin in vitro The findings of this study can extend to other departments or hospitals.BACKGROUND Stimulating current distribution in the tissue is unknown due to the complex distribution. OBJECTIVE A preliminary in vivo measurement of the magneto-acoustic (MA) signal of the human finger is performed in this study. The approach for locating the magneto-acoustic source of the stimulating current is studied. METHODS We use a lock-in amplifier to measure the MA signal under continuous wave electrical stimulation. The phase of the MA signal is used to extract the location of the sonic source. The experimental system is designed to measure the MA signal under electrical stimulation. RESULTS Preliminary experiments results show that the amplitude precision is improved to less than 1 μPa. The sonic source is located with millimetre precision. CONCLUSIONS We propose a new MA source-locating method with high measurement and location precision. This method will be significant to the study of the imaging and monitoring of the current distribution of electrical stimulation with high precision.BACKGROUND Mobile rehabilitation systems for patients with gait disorder are being developed. Safety functions to prevent patients from falling are considered during product development; however, few studies have been conducted on systems that have been prevalidated for healthy adults prior to application to patients. OBJECTIVE This study analyzed the characteristics of lower extremity muscles and foot pressure in healthy adults during unbalanced walking with differences in the speed of left and right speed using a two-belt treadmill. METHODS Twenty subjects performed gait motions with a difference in the weight support conditions (0% and 30%) and the left and right lower limb speeds (1-3 km/h). Each subject's muscular activities and foot pressure signals were collected. The gait patterns of the faster side exhibit similar characteristics to the paralyzed leg, and the slower side is similar to the non-paralyzed leg. RESULTS Weight-supporting healthy subjects showed asymmetric gait patterns, similar to hemiplegic patients, because of the difference in the speed of the left and right side. CONCLUSIONS The quantitative results can be used to develop a training protocol for two-belt treadmills with differently controlled left and right speeds for gait rehabilitation in hemiplegic patients.BACKGROUND Microscopic image analysis based on image processing is required for quantitative evaluation of decellularization. Existing methods are not widely used because of expensive commercial software, and machine learning-based techniques lack generality for decellularization because many high-resolution image data has to be processed. OBJECTIVE In this study, we developed an image processing algorithm for quantitative analysis of tissues and cells in a general microscopic image. METHODS The proposed method extracts the color images obtained by the microscope into reference images consisting of grayscale, red (R), green (G), and blue (B) information and transforms each into a binary image. The transformed images were extracted by separating the cells and tissues through outlier noise elimination, logical multiplication and labeling. In order to verify the method, decellularization of porcine arotic valve was performed by the electrical method. Slice samples were obtained by time and the proposed method was applied. RESULTS The experimental results show that the segmentation of cells and tissues, and quantitative analysis of the number of cells and changes in tissue area during the decellularization process was possible. CONCLUSIONS The proposed method shows that cell and tissue extraction and quantitative numerical analysis were possible in different brightness of microscopic images.BACKGROUND TO BE PROVIDED. OBJECTIVE In this paper, a prior knowledge fusion method based on Haar-like feature and contour feature is proposed to locate and detect key areas in medical images. METHOD For the image to be processed, six Haar-like features and five contour features are extracted respectively. The improvement of Haar-like feature extraction template better adapts to the complexity of regional structure of medical images. The design of the contour feature extraction process fully reflects the consideration of feature invariance. The two features, together with prior knowledge, are fed into their respective decision makers and final fusers as the basis for determining and locating key regions. RESULTS The experimental results show that the proposed method has excellent performance in locating key regions of medical images on MRI. When the capacity of the database increases from 10 to 200, the accuracy of locating the key areas of the image to be processed still reaches more than 90%. CONCLUSION TO BE PROVIDED.
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