• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.941-946
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• 2021

This paper is a study on the design and implementation of a rehabilitation wearable robotic hand that reduces weight and volume by using a 3D printer and a motor. Rehabilitation wearable robots are important not only for the effect of rehabilitation but also for ease of use. However, most of the currently researched and developed rehabilitation exoskeleton robots are heavy in volume and weight, or they have to be used in place. Therefore, a wearable robot that is easy to wear and does not burden the user is required, so a lightweight electric rehabilitation wearable robot hand is proposed. A 3D printer was used to reduce the weight and volume and to make it easier to wear. In addition, to increase portability, the structure was simplified by adopting an electric method rather than a pneumatic method. Finally, the effectiveness was examined through the experiment of the lightweight electric rehabilitation wearable robot hand.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.531-537
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• 2015

Hand function is one of the essential functions required to perform the activities of daily living, and wearable robots that assist or recover hand functions have been consistently developed. Previously, wearable robots commonly employed conventional robotic technology such as linkage which consists of rigid links and pin joints. Recently, as the interest in soft robotics has increased, many attempts to develop a wearable robot with a soft structure have been made and are in progress in order to reduce size and weight. This paper presents the concept of a soft wearable robot composed of a soft structure by comparing it with conventional wearable robots. After that, currently developed soft wearable robots and related issues are introduced.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.936-942
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• 2005

Recently the exoskeletal power assistive equipment which is a kind of wearable robot has been widely developed to help the human body motion. For the elderly people and patients, however, some limits exist due to the weight and volume of the equipments. As a feasible solution, a tendon-driven exoskeletal power assistive device fur the lower body, and caster walker are proposed in this research. Since the caster walker carries the heavy items, the weight and volume of the wearable exoskeleton are minimized. The key control is used to generate the joint torque required to assist motions such as sitting, standing and walking. Experiments were performed for several motions and the EMG sensors were used to measure the magnitude of assistance. When the motion of sitting down and standing up was compared with and without wearing the proposed device, the $25\%$ assistance was acquired.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.17-18
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• 2014

현대사회와 미래사회는 가속화되어지는 IT기술에 의해서 융합되어진 작업의 효율 및 성능의 발전이 이슈화되고 있다. 따라서 1990년대부터는 군사 및 재활분야와 함께 제조업 및 유통업 등 전반적인 산업 모두에서 근력보조기구에 대한 연구가 활발히 진행되고 있다. 과거에는 일반인이 무거운 짐을 운반하는 것을 완전한 로봇이 대체하거나 몸이 불편한 사회적 약자가 휠체어 및 지팡이 또는 전동 휠체어와 같은 보조 개념이 아닌 완전한 대체의 개념을 가지고 있었다. 그러나 웨어러블이 대두됨에 따라 기계와 인체가 합쳐지는 상호작용 근력보조기구가 탄생했다. 근력보조기구는 힘/토크 센서를 통한 인간과 로봇간의 상호작용에 의해 인간의 다양한 상지 및 하지 동작을 구현할 수 있는 근력 강화용 웨어러블 로봇 등이 있다.

• Cartoon and Animation Studies
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• s.50
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• pp.423-452
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• 2018

The possibility of future industrialization of artificial intelligence was studied through aspects of artificial intelligence art and movie. The field of artificial intelligence is developing by imitating humans through past and present, so it can be inferred that it is important to grasp the future image presented in movie and artificial intelligence art. Human values are represented differently in artificial intelligence films and arts. Artificial intelligence film and art are concerned with the external and internal aspects of human values, respectively. The AI movie looks at similar external aspects in human and AI shape and function, but artificial intelligence art deals with human alienation and lack of communication due to artificial intelligence technology development. Artificial intelligence in movies is a direction to visualize the imagination for artificial intelligence technology, and artificial intelligence art is expressed in the way of making and implementing works using technology. The future of artificial intelligence, which we have shown in imagination in movies today, is being realized technologically. Artificial intelligence art reflects the problems of artificial intelligence technology that can be appeared through current technology, and human problems that may arise from artificial intelligence technology development. Movies and artificial intelligence art reflect the current problems, and through them we can see the future of artificial intelligence. The future of artificial intelligence in movies is an artificial intelligence service that provides human convenience, cyborg artificial intelligence industry, industry that uses exoskeleton robot and exoskeleton suit, and artificial intelligence secretary. If we look at the future of artificial intelligence through the artificial intelligence art in terms of the problems of artificial intelligence technology and the problem of human value, there are artificial intelligence to learn from trial and error or mistakes, self-expression and communication by lifelogging, recovery of miscommunications by a reflective thinking, and an expansion of the area of artificial intelligence artist through human uncertainty. The future industrialization potential of artificial intelligence as study through aspects of artificial intelligence art and movie is an industry that extends the five senses, an industry that improves the insufficient physical ability of the human, an industry that enhances the physical ability of the human being, and an industry that maintains psychological and mental well-being.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1918-1919
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• 2011

상체 지원 외골격 로봇은 크게 인간의 근력을 보조하는 형태와 인간의 근력을 증강하는 형태가 있다. 여기서는 인간의 근력을 증강하는 외골격 로봇을 중심으로 기술하고자 한다. 이러한 외골격 로봇은 팔의 EMG (Electromyograph;근전도) 신호를 측정하는 방법보다는 손의 힘을 직접 감지하는 방법을 통한 팔꿈치와 어깨의 엑추에이터를 구동하는 방식을 취하는 경향이 있다. 본 논문에서도 후자의 방식을 이용하여 손에 작용하는 힘을 분석하여 외골격 로봇을 움직이는 방식을 취하였다. 손의 힘 중에서도 인간을 중심으로 볼 때 위방향과 전진방향의 힘을 분석하기 위하여 2개의 F/T(Force/Torque) 센서를 사용하였으며 팔을 벌리는 동작은 엑추에이터 없이 자유롭게 동작이 가능하도록 설계하였다. 이러한 위방향 및 전진방향 힘의 크기를 팔꿈치와 어깨의 엑추에이터의 동작으로 바꾸어 인간의 동작을 도울 수 있고 힘을 증폭할 수 있는 외골격 로봇을 설계 제작하였다. F/T 센서는 손의 힘을 전기적 신호로 바꾸어주는 로드셀로 이루어지며 손의 힘을 최대한 잘 반영하기 위한 구조를 고안하였다. F/T 센서의 전기신호는 증폭기를 거쳐서 잡음을 제거한 후에 A/D 변환하여 processor에서 처리되어진다.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.182-188
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• 2023

Due to the acceleration of an aging society, the need for lower limb exoskeletons to assist gait is increasing. And for use in daily life, it is essential to have technology that can accurately estimate gait phase even in the walking environment and walking speed of the wearer that changes frequently. In this paper, we implement an LSTM-based gait phase estimation learning model by collecting gait data according to changes in gait speed in outdoor level ground and stair environments. In addition, the results of the gait phase estimation error for each walking environment were compared after learning for both max hip extension (MHE) and max hip flexion (MHF), which are ground truth criteria in gait phase divided in previous studies. As a result, the average error rate of all walking environments using MHF reference data and MHE reference data was 2.97% and 4.36%, respectively, and the result of using MHF reference data was 1.39% lower than the result of using MHE reference data.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.59-64
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• 2015

In this paper, we found the usefulness of the deep belief network (DBN) in the fields of brain-computer interface (BCI), especially in relation to imagined speech. In recent years, the growth of interest in the BCI field has led to the development of a number of useful applications, such as robot control, game interfaces, exoskeleton limbs, and so on. However, while imagined speech, which could be used for communication or military purpose devices, is one of the most exciting BCI applications, there are some problems in implementing the system. In the previous paper, we already handled some of the issues of imagined speech when using the International Phonetic Alphabet (IPA), although it required complementation for multi class classification problems. In view of this point, this paper could provide a suitable solution for vowel classification for imagined speech. We used the DBN algorithm, which is known as a deep learning algorithm for multi-class vowel classification, and selected four vowel pronunciations:, /a/, /i/, /o/, /u/ from IPA. For the experiment, we obtained the required 32 channel raw electroencephalogram (EEG) data from three male subjects, and electrodes were placed on the scalp of the frontal lobe and both temporal lobes which are related to thinking and verbal function. Eigenvalues of the covariance matrix of the EEG data were used as the feature vector of each vowel. In the analysis, we provided the classification results of the back propagation artificial neural network (BP-ANN) for making a comparison with DBN. As a result, the classification results from the BP-ANN were 52.04%, and the DBN was 87.96%. This means the DBN showed 35.92% better classification results in multi class imagined speech classification. In addition, the DBN spent much less time in whole computation time. In conclusion, the DBN algorithm is efficient in BCI system implementation.