• KIPS Transactions on Computer and Communication Systems
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• v.10 no.9
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• pp.251-260
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• 2021

Gait analysis is one of the research fields for obtaining various information related to gait by analyzing human ambulation. It has been studied for a long time not only in the medical field but also in various academic areas such as mechanical engineering, electronic engineering, and computer engineering. Efforts have been made to determine whether there is a problem with gait through gait analysis. In this paper, as a pre-step to find out gait abnormalities, it is investigated whether it is possible to differentiate whether experiment participants wear elderly simulation suit or not by applying gait data to machine learning models for the same person. For a total of 45 participants, each gait data was collected before and after wearing the simulation suit, and a total of six machine learning models were used to learn the collected data. As a result of using an artificial neural network model to distinguish whether or not the participants wear the suit, it showed 99% accuracy. What this study suggests is that we explored the possibility of judging the presence or absence of abnormality in gait by using machine learning.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.216-224
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• 2014

층간소음의 대부분의 원인이 아이들 뛰거나 발걸음으로 나타나고 있어 층간소음 저감을 위한 선행 연구로 층간소음의 주요 충격원인 보행 행위에 대한 정밀한 연구가 필요하다. 성인 보행 충격력과 그에 따른 바닥충격음을 계측하여 보행하중이 바닥충격음에 영향을 주는 요소를 분석하였다. 보행하중 중 발 뒤꿈치 충격력은 전체 충격하중을 주파수 특성을 대변할 수 있는 임펄스 형태의 하중으로 충격력은 뱅머신 또는 고무공보다 낮지만 1 차 영점(First zero)이 80Hz 정도로 높아 유효 가진 주파수 대역이 표준 중량충격원 보다 높았다. 구조물과 수음실의 고유모드 특성으로 인해 외부 충격에 대한 구조체 진동 및 음압의 공진 현상이 발생되기 때문에 공진 성분이 포함되는 바닥충격음 레벨은 순수 충격력 특성인 보행 또는 표준 중량충격원의 옥타브 밴드 충격력 폭로레벨과는 전혀 다른 주파수 특성을 나타내었다.

• Journal of Biomedical Engineering Research
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• v.38 no.3
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• pp.129-136
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• 2017

The exoskeleton robot is a technology developed to be used in various fields such as military, industry and medical treatment. The exoskeleton robot works by sensing the movement of the wearer. By recognizing the wearer's daily activities, the exoskeleton robot can assist the wearer quickly and efficiently utilize the system. In this study, LDA, QDA, and kNN are used to classify gait types through kinetic data obtained from subjects. Walking was selected from general walking and stair walking which are mainly performed in daily life. Seven IMUs sensors were attached to the subject at the predetermined positions to measure kinematic factors. As a result, LDA was classified as 78.42%, QDA as 86.16%, and kNN as 87.10% ~ 94.49% according to the value of k.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.249-256
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• 2016

Recently, a number of techniques to ensure the free walking for the visually impaired and transportation vulnerable have been studied. As a device for free walking, there are such as a smart cane and smart glasses to use the computer vision, ultrasonic sensor, acceleration sensor technology. In a typical technique, such as techniques for finds object and detect obstacles and walking area and recognizes the symbol information for notice environment information. In this paper, we studied recognization algorithm of the selected symbols that are required to visually impaired, with the deep learning algorithm. As a results, Use CNN(Convolutional Nueral Network) technique used in the field of deep-learning image processing, and analyzed by comparing through experimentation with various deep learning architectures.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.199-208
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• 2023

The emergence of COVID-19 virus has shaken almost every aspect of human life including but not limited to social, financial, and economic changes. One of the most significant impacts was obviously healthcare. Now though the pandemic has been over, its aftereffects are still there. Among them, a prominent one is people lifestyle. Work from home, enhanced screen time, limited mobility and walking habits, junk food, lack of sleep etc. are several factors that have still been affecting human health. Consequently, diseases like diabetes, high blood pressure, anxiety etc. have been emerging at a speed never witnessed before and it mainly includes the people at young age. The situation demands an early prediction, detection, and warning system to alert the people at risk. AI and Machine learning has been investigated tremendously for solving the problems in almost every aspect of human life, especially healthcare and results are promising. This study focuses on reviewing the machine learning based approaches conducted in detection and prediction of diabetes especially during and post pandemic era. That will help find a research gap and significance of the study especially for the researchers and scholars in the same field.

• Journal of the Korean Institute of Navigation
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• v.20 no.4
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• pp.81-98
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• 1996

The purpose of this study was analysis of the muscle action in physical exercise in the rolling machine. The rolling machine moved by eletric power-driven was made to keep the constant cycle and size of rolling. The subjects of this study consist of 4 seaman(SM) and 4 landman (LM). The experiment analyzed the muscle power of lower and upper limbs by Intergrated Electromyogram(IEMG). The measurement was made on the ground, and 6 and 8 degrees of rolling separately. This study concludes as follows ; including analysis of IEMG of heavy exercise in two hands curl, a standstill walking and just standing. 1. IEMG of the lower limbs when standing. 1) In 6 degrees of rolling, for the landman(LM), vastus medialis m.(9.73), vastus lateralis m.(9.55), and rectus femores m.(8.73) acted more. As for the seaman(SM), tibialis anterior m.(5.38), biceps femores m.(5.05), and gastrocnemius m.(4.47) acted more. 2) In 8 degrees of rolling, in common, for both LM and SM, it were vastus medialis m.(11.20 and 8.97), vastus lateralis m.(16.20 and 4.63), and tibialis anterior m.(5.13 and 4.47). 3) It was showed that IEMG of LM was larger than that of SM. 2. IEMG of the lower limbs when walking. 1) On the ground, for the LM, gastrocnemius m.(7.08), vastus medialis m.(6.65), and vastus latralis m.(6.60) acted more. As for the SM, vastus lateralis m.(7.08), vastus medialis m.(6.58) and restus femores m.(5.10) acted more. 2) In both 8 and 6 degrees of rolling, vastus medials m.(14.50 and 11.98), vastus lateralis m.(10.10 and 14.10), and gastrocnemius m.(11.75 and 7.10) acted more in two groups. 3) It was showed that IEMG of LM was larger than that of SM. 3. IEMG of the lower limbs when heavy exercise(two hands curl). 1) On the ground, for the LM, vastus lateralis m.(21.68), vastus medialis m.(16.08), and rectus femores m.(14.08) acted more. As for the SM, tibialis anterior m.(16.08), vastus medialis m.(14.58), and vastus lateralis m.(8.78) acted more. 2) In 8 and 6 dgrees of rolling, it were vastus medialis m.(17.05 and 12.45), vastus lateralis m.(37.98 and 17.08), and tibialis anterior m.(19.83 and 13.20). 3) It was showed that IEMG of LM was larger than that of SM. 4. IEMG of the upper limbs when heavy exercise. 1) On the ground, the brachialis m.(44.30 and 17.80), and biceps brachii m.(13.40 and 25.10) acted more in two groups. 2) In both 6 and 8 degrees of rolling, the brachialis m.(37.60 and 24.35), and biceps brachii m.(11.38 and 7.97) acted more in two groups. 3) It was showed that IEMG of SM was larger than that of LM.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.31-37
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• 2024

In this study, we propose a machine vision-based pedestrian signal detection algorithm that operates efficiently even in computing resource-constrained environments. This algorithm demonstrates high efficiency within limited resources and is designed to minimize the impact of ambient lighting by sequentially applying HSV color space-based image processing, binarization, morphological operations, labeling, and other steps to address issues such as light glare. Particularly, this algorithm is structured in a relatively simple form to ensure smooth operation within embedded system environments, considering the limitations of computing resources. Consequently, it possesses a structure that operates reliably even in environments with low computing resources. Moreover, the proposed pedestrian signal system not only includes pedestrian signal detection capabilities but also incorporates IoT functionality, allowing wireless integration with a web server. This integration enables users to conveniently monitor and control the status of the signal system through the web server. Additionally, successful implementation has been achieved for effectively controlling 50W LED pedestrian signals. This proposed system aims to provide a rapid and efficient pedestrian signal detection and control system within resource-constrained environments, contemplating its potential applicability in real-world road scenarios. Anticipated contributions include fostering the establishment of safer and more intelligent traffic systems.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.193-199
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• 2014

In this paper, we present an overview of the structure of a lab-built powered knee prosthesis and the control of it. We build a powered prosthesis prototype on the basis of previous researches and aim at obtaining the essential technology related with its control. We adopt the slider-crank mechanism with a DC motor as an actuator to manipulate the knee joint. We also build an embedded control system for the prosthesis with a 32-bit DSP controller as a main computation unit. We divide the gait phase into five stages and use a FSM (Finite State Machine) to generate a torque reference needed for each stage. We also propose to use a position-based impedance controller for driving the powered knee prosthesis stably. We perform some walking experiments at fixed speeds on a tread mill in order to show the feature of the built powered prosthesis. The experimental results show that our prosthesis has the ability to provide a functional gait that is representative of normal gait biomechanics.

• The Journal of Sustainable Design and Educational Environment Research
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• v.9 no.3
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• pp.34-40
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• 2010

In this study, vibration characteristics of reinforced concrete slab in large span educational facilities were evaluated. A 21.75m X 14.4m full scale reinforced concrete slab specimen was constructed with pre-flex hybrid beams. Vibrations were generated by three different methods such as free falling method of a 6kg sand bag, a 70kg person walking method and impact method by impulse hammer. Vibrations were generated more than 3 times at single location. Vibration characteristic data were collected by SA390 signal analyzer machine at 5 different locations.

• The Journal of the Acoustical Society of Korea
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• v.10 no.6
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• pp.23-42
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• 1991

본 논문은 시스템 운동학적 자유보다도 많은 수의 input을 사용하여 비선형 구속조건을 갖는 메 카니즘의 정역학적 평형을 유지시키는 경우와 같이 일반 로봇 시스템의 협력 작업시 일어나는 antagonistic stiffness를 연구하였다. 이러한 antagonistic 상황은 coordinations of multiple manipulators, multi-fingered end-efector, walking machine, 그리고 인간의 움직임등을 포함하는 많은 로봇 시스템의 작동시에 일어난다. Antagonism으로 야기되는 stiffness는 이러한 시스템의 특성을 파악하는 좋은 척도 가 될 수 있다. Antagonistic stiffness의 개념은 시스템을 구성하는 강체들의 상대 변위의 함수로 얻어 지기 때문에 바강체들이 변형하는 특성을 나타내는 structural stiffness와는 구별된다. 따라서 이 개념은 여유입력들에 의해 얻어지는 시스템의 effective stiffness로 해석될 수 있고, 일반 로봇 mechanism의 개 경로 안정도의 척도로 이용될 수 있으며 목적에 따라서 stiffness의 제어가 가능한 비선형 spring을 만 드는 데에도 응용이 가능하다. 본 논문에서는 antagonism이 일어나는 몇가지 상황에서의 stiffness 특성 과 개경로 안정성 조건등을 해석적, 기하학적 관점에서 다루었다.