• PNF and Movement
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• v.18 no.1
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• pp.23-34
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• 2020

Purpose: To explore the effects of action observation combined with modified constraint-induced movement therapy on upper-extremity function and the activities of daily living in subacute stroke patients. Methods: Twenty-four subacute stroke patients were randomly assigned to the experimental group or the control group (n = 12 each). Both groups received therapy based on motor learning concepts, including repetitive and task-specific practice. The experimental group watched video clips for 10 minutes related to tasks performed during modified constraint-induced movement therapy while the control group watched videos unrelated to upper-extremity movement. These programs were performed for 40 minutes a day five times a week for four weeks. Their scores on the Fugl-Meyer assessment of upper extremities (FMA-UE), the action research arm test (ARAT), a motor activity log (amount of use [AOU] and quality of movement [QOM]), and the modified Barthel index (MBI) were recorded. Results: In both groups, all variables were significantly different between the pre-test and post-test periods (p < 0.05). The post-test variables were significantly different within each group (p < 0.05). In the experimental group, the changes between pre-test and post-test scores in the FMA-UE (14.39 ± 4.31 versus 6.31 ± 4.63), the ARAT (16.00 ± 4.73 versus 11.46 ± 3.73), MAL-AOU (1.57 ± 0.15 versus 1.18 ± 0.28), and MBI (27.54 ± 4.65 versus 18.08 ± 8.52) were significantly higher than those of the control group (p < 0.05). Conclusion: These findings suggest that action observation combined with modified constraint-induced movement therapy may be a beneficial rehabilitation option to improve upper-extremity function in subacute stroke patients with moderate impairment.

• Journal of Animal Science and Technology
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• v.65 no.2
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• pp.441-458
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• 2023

The poultry industry, which produces excellent sources of protein, suffers enormous economic damage from diseases. To solve this problem, research is being conducted on the early detection of infection according to the behavioral characteristics of poultry. The purpose of this study was to evaluate the potential of a non-movement behavior observation method to detect sick chickens. Forty 1-day-old Ross 308 males were used in the experiments, and an isolator equipped with an Internet Protocol (IP) camera was fabricated for observation. The chickens were inoculated with Salmonella enterica serovar Gallinarum A18-GCVP-014, the causative agent of fowl typhoid (FT), at 14 days of age, which is a vulnerable period for FT infection. The chickens were continuously observed with an IP camera for 2 weeks after inoculation, chickens that did not move for more than 30 minutes were detected and marked according to the algorithm. FT infection was confirmed based on clinical symptoms, analysis of cardiac, spleen and liver lesion scores, pathogen re-isolation, and serological analysis. As a result, clinical symptoms were first observed four days after inoculation, and dead chickens were observed on day six. Eleven days after inoculation, the number of clinical symptoms gradually decreased, indicating a state of recovery. For lesion scores, dead chickens scored 3.57 and live chickens scored 2.38. Pathogens were re-isolated in 37 out of 40 chickens, and hemagglutination test was positive in seven out of 26 chickens. The IP camera applied with the algorithm detected about 83% of the chickens that died in advance through non-movement behavior observation. Therefore, observation of non-movement behavior is one of the ways to detect infected chickens in advance, and it appears to have potential for the development of remote broiler management system.

• Journal of Korea Game Society
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• v.16 no.6
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• pp.131-142
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• 2016

Recently, a variety of methodologies based on the use of educational coding robots have been proposed and experimented in newly emerging korean educational coding markets. Due to imprecise movement accuracy of the existing coding robots, however, such robots are mainly used as a toy. Inspired by these observations, we developed a simple adjustment method during robot movements, which is based on the observation results of 6 line-tracking sensors: 3 sensors in the center of a robot and other 3 sensors at the front. These sensors help to determine whether the robot is in the right location and whether it rotates as expected. Through the well-designed experiments, we report the effectiveness of our proposed solution: the average distance error of 1.57cm and the average degree error of 2.38 degree before and after complex movements. In near future, we hope our method to be popularly used in various educational coding robot platforms.

• Therapeutic Science for Rehabilitation
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• v.12 no.1
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• pp.23-35
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• 2023

Objective : This study is to examine the practical use of clinical observational evaluation of sensory integration therapy and the difficulty and importance of measuring results for each sub-item, and through this, to confirm the usefulness of the application of Artificial Intelligence measurement technology in clinical observational measurement and the need for application. Methods : The questionnaire consisted of the actual use of the sensory integration evaluation tool, the difficulty of measurement for each detailed item of clinical observation, the usefulness of AI measurement technology, the importance of evaluation for each detailed item, and the need for developing AI measurement technology. Results : The detailed items that were difficult to measure during clinical observation were the Finger-to-Nose Test and Postural control (71.0%), followed by Eye movement and Protective Extension Test (67.7%). 83.9% of the study subjects answered that it would be useful to apply AI measurement technology when observing images. Postural control (on the ball) (90.3%) was the highest item that answered that AI measurement technology was needed, followed by Eye movement (83.9%), and Prone Extension and Protective Extension Test (77.4%). Conclusion : The results confirmed the desire of therapists that clinical observation is an important evaluation tool in the field of child occupational therapy in Korea.

• Journal of Broadcast Engineering
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• v.22 no.2
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• pp.234-239
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• 2017

A real-time violence detection algorithm based on a new descriptor using the magnitude and direction changes of movement in images is proposed. The descriptor was developed from the observation that the changes of violent actions are much larger than those of normal movements. Descriptor feature vectors consisting of descriptor values during several frames are obtained and these are inputs to SVM(Support Vector Machine) classifier for discriminating violence actions from and non-violence actions. Comparison experiments between the ViF(Violent Flow) and the proposed algorithm were conducted with three different types of datasets. The experimental results show that the proposed algorithm outperforms the ViF in every case.

• The Journal of Korean Physical Therapy
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• v.15 no.1
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• pp.155-170
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• 2003

Lumbar segmental instability is considered to represent a significant sub-group within the chronic low back pain population. This condition has a unique clinical presentation that displays its symptoms and movement dysfunction within the neutral zone of the motion segment. The loosening of the motion segment secondary to injury and associated dysfunction of the local muscle system renders it biomechanically vulnerable in the neutral zone. There in evidence of muscle dysfunction related to the control of the movement system. There is a clear link between reduced proprioceptive input, altered slow motor unit recruitment and the development of chronic pain states. Dysfunction in the global and local muscle systems in presented to support the development of a system of classification of muscle function and development of dysfunction related to musculoskeletal pain. The global muscles control range of movement and alignment, and evidence of dysfunction is presented in terms of imbalance in recruitment and length between the global stability muscles and the global mobility muscles. The local stability muscles demonstrate evidence of failure of aeequate segmental control in terms of allowing excessive uncontrolled translation or specific loss of cross-sectional area at the site of pathology Motor recruitment deficits present as altered timing and patterns of recruitment. The evidence of local and global dysfunction allows the development of an integrated model of movement dysfunction. The clinical diagnosis of this chronic low back pain condition is based on the report of pain and the observation of movement dysfunction within the neutral zone and the associated finding of excessive intervertebral motion at the symptomatic level. Four different clinical patterns are described based on the directional nature of the injury and the manifestation of the patient's symptoms and motor dysfunction. A specific stabilizing exercise intervention based on a motor learning model in proposed and evidence for the efficacy of the approach provided.

• The Journal of Korean Physical Therapy
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• v.27 no.3
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• pp.135-139
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• 2015

Purpose: The aim of this study was to compare EEG topographical maps in patients with chronic stroke after action observation physical training. Methods: Ten subjects were recruited from a medical hospital. Participants observed the action of transferring a small block from one box to another for 6 sessions of 1 minute each, and then performed the observed action for 3 minutes, 6 times. An EEG-based brain mapping system with 32 scalp sites was used to determine cortical reorganization in the regions of interest (ROIs) during observation of movement. The EEG-based brain mapping was comparison in within-group before and after training. ROIs included the primary sensorimotor cortex, premotor cortex, superior parietal lobule, inferior parietal lobule, superior temporal lobe, and visual cortex. EEG data were analyzed with an average log ratio in order to control the variability of the absolute mu power. The mu power log ratio was in within-group comparison with paired t-tests. Results: Participants showed activation prior to the intervention in all of the cerebral cortex, whereas the inferior frontal gyrus, superior frontal gyrus, precentral gyrus, and inferior parietal cortex were selectively activated after the training. There were no differences in mu power between each session. Conclusion: These findings suggest that action observation physical training contributes to attaining brain reorganization and improving brain functionality, as part of rehabilitation and intervention programs.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1106-1110
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• 2004

A human sign language is generally composed of both static and dynamic gestures. Each gesture is represented by a hand shape, its position, and hand movement (for a dynamic gesture). One of the problems found in automated sign language translation is on segmenting a hand movement that is part of a transitional movement from one hand gesture to another. This transitional gesture conveys no meaning, but serves as a connecting period between two consecutive gestures. Based on the observation that many dynamic gestures as appeared in Thai sign language dictionary are of quasi-periodic nature, a method was developed to differentiate between a (meaningful) dynamic gesture and a transitional movement. However, there are some meaningful dynamic gestures that are of non-periodic nature. Those gestures cannot be distinguished from a transitional movement by using the signal quasi-periodicity. This paper proposes a hybrid method using a combination of the periodicity-based gesture segmentation method with a HMM-based gesture classifier. The HMM classifier is used here to detect dynamic signs of non-periodic nature. Combined with the periodic-based gesture segmentation method, this hybrid scheme can be used to identify segments of a transitional movement. In addition, due to the use of quasi-periodic nature of many dynamic sign gestures, dimensionality of the HMM part of the proposed method is significantly reduced, resulting in computational saving as compared with a standard HMM-based method. Through experiment with real measurement, the proposed method's recognition performance is reported.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.8
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• pp.1080-1088
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• 2018

General methods of controlling a drone are divided into manual control and automatic control, which means a drone moves along the route. In case of manual control, a man should be able to figure out the location and status of a drone and have a controller to control it remotely. When people control a drone, they collect information about the location and position of a drone with the eyes and have its internal information such as the battery voltage and atmospheric pressure delivered through telemetry. They make a decision about the movement of a drone based on the gathered information and control it with a radio device. The automatic control method of a drone finding its route itself is not much different from manual control by man. The information about the position of a drone is collected with the gyro and accelerator sensor, and the internal information is delivered to the CPU digitally. The location information of a drone is collected with GPS, atmospheric pressure sensors, camera sensors, and ultrasound sensors. This paper presents an investigation into drone control by a remote computer. Instead of using the automatic control function of a drone, this approach involves a computer observing a drone, determining its movement based on the observation results, and controlling it with a radio device. The computer with a Depth camera collects information, makes a decision, and controls a drone in a similar way to human beings, which makes it applicable to various fields. Its usability is enhanced further since it can control common commercial drones instead of specially manufactured drones for swarm flight. It can also be used to prevent drones clashing each other, control access to a drone, and control drones with no permit.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.307-314
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• 2006

In this paper, we present a comprehensive study for the development of quadruped walking robot. To understand the walking posture of a tetrapod animal, we begin with a careful observation on the skeletal system of tertapod animals. From taking a side view of their skeletal system, it is noted that their fore limbs and hind limbs perform characteristic roles during walking. Moreover, the widths of footprints and energy efficiency in walking have a close relationship through taking a front view of their walking posture. According to these observations, we present a control method where the kinematical solutions are not necessary because we develop a new rhythmic gait pattern for the quadruped walking robot. Though the proposed control method and rhythmic pattern are simple, they can provide the suitable motion planning for the robot since the resultant movement is based on the animal's movements. The validity of the proposed idea is demonstrated through dynamic simulations.