한국 조선시대 인골에서의 해리스 선 출현 양상 연구

학위논문 (석사)-- 서울대학교 대학원 : 의학과, 2011.8. 신동훈.Maste

뇌졸중 환자에서 고유감각 및 편마비측 상지 기능 회복 촉진을 위한 2축 거울상 로봇 치료 시스템

학위논문 (박사)-- 서울대학교 대학원 : 의학과 의공학 전공, 2016. 8. 김성완.Introduction: Mirror therapy has been performed as an effective occupational therapy in a clinical setting for functional recovery of a hemiplegic arm after stroke. It is conducted by eliciting a visual illusion through the use of a mirror as if the hemiplegic arm is moving in real-time while moving the healthy arm. It can facilitate brain neuroplasticity through activation of the sensorimotor cortex. However, conventional mirror therapy has a critical limitation in that the hemiplegic arm is not actually moving. Methods: We developed a real-time 2-axis mirror robot system as a simple add-on module for conventional mirror therapy using a closed feedback mechanism, which allows for real-time movement of the hemiplegic arm. This is the first attempt that combined a robot with a real mirror for facilitation of proprioception followed by motor recovery. We used three attitude and heading reference system sensors, two brushless DC motors for elbow and wrist joints, and exoskeletal frames. Results: Motion synchronicity between the motors in the hemiplegic arm and the AHRS sensors in the healthy arm was validated. A study with six healthy subjects showed that robotic mirror therapy was safe and feasible. We further selected useful tasks for activities of daily living training through feedback from six rehabilitation doctors. Two chronic stroke patients showed improvement in the Fugl-Meyer assessment scale and elbow flexor spasticity, proprioception and hemispatial neglect after a 2-week application of the mirror robot system. The enhancement of proprioceptive input can be explained by the functional MRI results. The results revealed that both the lower part of the superior parietal lobule and the premotor cortex (PMC) were activated during the passive range of motion (ROM) exercise, whereas the PMC was mainly activated during the active ROM exercise. Conclusions: Robotic mirror therapy could enhance proprioceptive stimulus to the sensory cortex, which is considered to be very important in neuroplasticity and functional recovery of hemiplegic arms. The mirror robot system presented in this study can be easily developed and utilized effectively to advance occupational therapy.Introduction 1 Materials and Methods 5 1) Mirror therapy tasks 5 2) Components of the mirror robot system 8 3) Clinical application of the mirror robot system 22 4) Functional magnetic resonance imaging analysis 26 Results 29 1) Validation of motion synchronicity between the motors and AHRS sensors 29 2) A clinical study for healthy subjects 31 3) Feedback from rehabilitation doctors 34 4) A case study for stroke patients 34 Discussion 45 Conclusions 51 References 53 Supplementary figure and tables 59 Abstract in Korean 64Docto

Forecasting the Walking Assistance Rehabilitation Level of Stroke Patients Using Artificial Intelligence

Cerebrovascular accidents (CVA) cause a range of impairments in coordination, such as a spectrum of walking impairments ranging from mild gait imbalance to complete loss of mobility. Patients with CVA need personalized approaches tailored to their degree of walking impairment for effective rehabilitation. This paper aims to evaluate the validity of using various machine learning (ML) and deep learning (DL) classification models (support vector machine, Decision Tree, Perceptron, Light Gradient Boosting Machine, AutoGluon, SuperTML, and TabNet) for automated classification of walking assistant devices for CVA patients. We reviewed a total of 383 CVA patients' (1623 observations) prescription data for eight different walking assistant devices from five hospitals. Among the classification models, the advanced tree-based classification models (LightGBM and tree models in AutoGluon) achieved classification results of over 90% accuracy, recall, precision, and F1-score. In particular, AutoGluon not only presented the highest predictive performance (almost 92% in accuracy, recall, precision, and F1-score, and 86.8% in balanced accuracy) but also demonstrated that the classification performances of the tree-based models were higher than that of the other models on its leaderboard. Therefore, we believe that tree-based classification models have potential as practical diagnosis tools for medical rehabilitation