• PNF and Movement
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• v.21 no.1
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• pp.1-10
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• 2023

Purpose: This systematic review aims to determine whether robot-assisted training is more effective in gait training for persons with subacute hemiparetic stroke. Methods: This study adopted a systematic review study design focused on subacute hemiparetic stroke, and four core academic databases were searched until June 11, 2021, for relevant studies, including PubMed, Embase, the Cochrane Library, and ProQuest Central. The review included randomized controlled trials (RCTs) evaluating the effects of robotic-assisted training on gait performance in persons with a diagnosis of subacute hemiparetic stroke. The selected RCT studies were qualitatively synthesized based on the population, intervention, comparison, outcome, settings, and study design (PICOS-SD). Results: The study selected five RCTs involving 253 subacute hemiparetic stroke patients and performing robotic-assisted gait training using the following devices: the Lokomat, Morning Walk, Walkbot, ProStep Plus, or Gait Trainer II. Five RCTs were eligible for the meta-analysis after quantitative synthesis, and the results showed that the robot-assisted gait training group had a greater gait performance than the control group based on the 10-meter walk test, Berg balance scale, Rivermed mobility index, functional ambulation category, and modified Barthel index. Conclusion: The results of this study showed that the gait performance of subacute hemiparetic stroke patients changes throughout robot-assisted gait training, but there were no indications that any of the clinically relevant effects of robot-assisted training are greater than those of conventional gait training. Further, the small sample size and different therapeutic intensities indicate that definitive conclusions could not be made.

• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.31-39
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• 2019

A robot usually adopts ANN (artificial neural network)-based object detection and instance segmentation algorithms to recognize objects but creating datasets for these algorithms requires high labeling costs because the dataset should be manually labeled. In order to lower the labeling cost, a new scheme is proposed that can automatically generate a training images and label them for specific objects. This scheme uses an instance segmentation algorithm trained to give the masks of unknown objects, so that they can be obtained in a simple environment. The RGB images of objects can be obtained by using these masks, and it is necessary to label the classes of objects through a human supervision. After obtaining object images, they are synthesized with various background images to create new images. Labeling the synthesized images is performed automatically using the masks and previously input object classes. In addition, human intervention is further reduced by using the robot arm to collect object images. The experiments show that the performance of instance segmentation trained through the proposed method is equivalent to that of the real dataset and that the time required to generate the dataset can be significantly reduced.

• Journal of the Korean Orthopaedic Association
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• v.53 no.6
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• pp.459-465
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• 2018

Of the many factors that affect the clinical outcomes of orthopedic surgery, the surgical procedure is the most important. Robotics have been developed to perform the surgical procedures more accurately and consistently. Robotic surgical procedures in the orthopedic field were developed 20 years ago. Some designs of surgical robots have disappeared due to practical problems and complications, and an another design of surgical robots is emerging. To date, the use of robot surgery in arthroplasty is still controversial in terms of the clinical outcomes, practicality, and cost-effectiveness, even though it has been reported to be effective in the alignment and positioning of components in the field of artificial joints. Early robotic surgery was based mainly on active robot surgery according to the scheduled operation without the intervention of the operator. Recently the semi-active system of robotic surgery has been introduced. In a semi-active system, the robot constrains the surgeon to a haptic boundary defined by the computer based on the 3-dimensional imaging preoperative plan, and the operator can change the preoperative plan through real-time feedback during operation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1427-1434
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• 2021

In this paper, we propose a psychological state estimation process that computes children's attention and tension in response to training stimuli. Joint attention was adopted as the training stimulus required for behavioral intervention, and the Discrete trial training (DTT) technique was applied as the training protocol. Three types of training stimulation contents are composed to check the user's attention and tension level and provided mounted on a character-shaped tabletop robot. Then, the gaze response to the user's training stimulus is estimated with the vision-based head pose recognition and geometrical calculation model, and the nervous system response is analyzed using the PPG and GSR bio-signals using heart rate variability(HRV) and histogram techniques. Through experiments using robots, it was confirmed that the psychological response of users to training contents on joint attention could be quantified.

• Journal of Korean Academy of Nursing
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• v.53 no.1
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• pp.55-68
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• 2023

Purpose: The purpose of this study was to identify the main keywords, network properties, and main topics of news articles related to artificial intelligence technology in the field of nursing. Methods: After collecting artificial intelligence-and nursing-related news articles published between January 1, 1991, and July 24, 2022, keywords were extracted via preprocessing. A total of 3,267 articles were searched, and 2,996 were used for the final analysis. Text network analysis and topic modeling were performed using NetMiner 4.4. Results: As a result of analyzing the frequency of appearance, the keywords used most frequently were education, medical robot, telecom, dementia, and the older adults living alone. Keyword network analysis revealed the following results: a density of 0.002, an average degree of 8.79, and an average distance of 2.43; the central keywords identified were 'education,' 'medical robot,' and 'fourth industry.' Five topics were derived from news articles related to artificial intelligence and nursing: 'Artificial intelligence nursing research and development in the health and medical field,' 'Education using artificial intelligence for children and youth care,' 'Nursing robot for older adults care,' 'Community care policy and artificial intelligence,' and 'Smart care technology in an aging society.' Conclusion: The use of artificial intelligence may be helpful among the local community, older adult, children, and adolescents. In particular, health management using artificial intelligence is indispensable now that we are facing a super-aging society. In the future, studies on nursing intervention and development of nursing programs using artificial intelligence should be conducted.

• Journal of IKEEE
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• v.23 no.4
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• pp.1440-1447
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• 2019

Currently, the prevalence of autism spectrum disorders in children is reported to be higher and shows various types of disorders. In particular, they are having difficulty in communication due to communication impairment in the area of social communication and need to be improved through training. Thus, this study proposes a method of acquiring voice information through a microphone mounted on a robot designed through preliminary research and using this information to make intelligent motions. An ANN(Artificial Neural Network) was used to classify the speech data into robot motions, and we tried to improve the accuracy by combining the Recurrent Neural Network based on Convolutional Neural Network. The preprocessing of input speech data was analyzed using MFCC(Mel-Frequency Cepstral Coefficient), and the motion of the robot was estimated using various data normalization and neural network optimization techniques. In addition, the designed ANN showed a high accuracy by conducting an experiment comparing the accuracy with the existing architecture and the method of human intervention. In order to design robot motions with higher accuracy in the future and to apply them in the treatment and education environment of children with autism.

• Medical Lasers
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• v.9 no.2
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• pp.103-109
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• 2020

Transoral microsurgery has come a long way as a go-to surgical intervention technique for head and neck cancers. This minimally invasive procedure had gained acceptance through comparative clinical studies against radical neck surgical procedures, radiotherapy, and chemotherapy. Laser technology has vastly improved the oncological outcomes of this procedure and brought about an appreciation of transoral laser surgery (TLM) as a mainstay for re-sectioning malignant tumors along the throat. As an established procedure, TLM has undergone several upgrades regarding the different energy devices used for cutting, ablation, and hemostasis. Continued advances in automation have eventually led to surgical robotics, resulting in the emergence of transoral robotic surgery (TORS) as a viable advanced alternative for TLM. Similarly, expansions and enhancements (image-based guidance, fluorescence spectroscopy, and advanced robotic system) have also been investigated as potential upgrades for TORS. This paper reviews a selection of publications on the significant technological advancements to TLM and TORS over the past five years.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.205-213
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• 2017

This paper is a study on the method to derive the functional level required for autonomous unmanned ground vehicle, one of the defense robots. Conventional weapon systems are not significantly affected by the operating environment, while defense robots exhibit different performance depending on the operating environment, even if they are on the same platform. If the performance of defense robot is different depending on operational environment, results of mission performance will be vary significantly. Therefore, it is necessary to clarify the level of function required by the military in order to research and develop most optimal defense robots. In this thesis, we propose a method to derive the required function level of unmanned ground vehicles, focusing on autonomous driving, one of the most vital functions of defense robots. Our results showed that the autonomous driving function depending intervention levels and evaluated functional sensitivity for autonomous driving of the unmanned vehicle using climate and topography as variables.

• Journal of Korean Society for Quality Management
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• v.51 no.3
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• pp.381-401
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• 2023

Purpose: The purpose of this study was to understand the perception of medical staff to propose an infected patient transport robot as a means of responding to infectious diseases. Methods: The data collected through the survey was analyzed through AHP analysis. The measurement tools used in this study were derived through the SERVQUAL model and Focus Group Interview(FGI), and consisted of four detailed questions for each of five classes: tangible, reliability, responsiveness, assurance, and empathy. Results: As a result of the study, there are concerns about risk factors that may occur in areas where medical staff intervention is minimized. Above all, we confirmed the consensus that safety should be the top priority during the process of robots to transport patients. In particular, highlighted were the resolution of device errors that may occur during the process for transporting patients and easy provision of the first aid. Additionally, the ability to monitor patients and suppress infection factors turned out to be important, which was directly related to the simplification of the role of medical staff and work efficiency. Conclusion: As one of the means of effectively controlling infectious diseases in a pandemic situation, a robot to transport the infected patient was considered. However, in order to commercialize this, specific verification of the safety of medical staff and patients is needed, and empirical data on providing the first aid, patient monitoring, and infection factor suppression should be presented.

• Journal of the Korean Society of Physical Medicine
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• v.15 no.4
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• pp.163-174
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• 2020

PURPOSE: This study examined the effects of Robot Tilt-table Training (RTT) on the lower extremity strength, balance, gait, and satisfaction with rehabilitation, in patients with subacute stroke (less than six months after stroke onset), and requiring intensive rehabilitation. METHODS: A total of 29 subacute stroke patients were divided into an RTT group (n = 14) and a Body Weight Support Treadmill Training (BWSTT) group (n = 15). The mean age of patients was 62 years. RTT and BWSTT were performed for four weeks, three times a week, for 30 minutes. Isometric strength of the lower extremities before and after intervention was compared by measuring the maximal voluntary isometric contraction of the lower extremity muscles. To compare the balance function, the center of pressure (COP) path-length and COP velocity were measured. Timed Up & Go test (TUG) and 10 Meter Walking Test (10 MWT) were evaluated to compare the gait function. A satisfaction with rehabilitation survey was conducted for subjective evaluation of the subject's satisfaction with the rehabilitation training imparted. RESULTS: In the intra-group comparison, both groups showed significant improvement in lower extremity strength, balance, gait, and satisfaction with rehabilitation, by comparing the parameters before and after the intervention (p < .05). Comparison of the amount of change between groups revealed significant improvement for all parameters in the RTT group, except for the 10 MWT (p < .05). CONCLUSION: Both groups are effective for all variables, but the RTT group showed enhanced efficacy for variables such as lower extremity strength, balance, gait, and satisfaction with rehabilitation, as compared to the BWSTT group.