• Journal of rehabilitation welfare engineering & assistive technology
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• v.7 no.2
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• pp.19-26
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• 2013

This paper propose a surface EMG signal based gait phase recognition method that selects features and channels adaptively. The proposed method can be used to control powered artificial prosthetic for lower limb amputees and can reduce overhead in real-time pattern recognition by selecting adaptive channels and features in an embedded device. The method can enhance the classification accuracy by adaptively selecting channels and features based on sensitivity and specificity of each subject because EMG signal patterns may vary according to subject's locomotion convention. In the experiments, we found that the muscles with highest recognition rate are different between human subjects. The results also show that the average accuracy of the proposed method is about 91% whereas those of existing methods using all channels and/or features is about 50%. Therefore we assure that sEMG signal based gait phase recognition using small number of adaptive muscles and corresponding features can be applied to control powered artificial prosthetic for lower limb amputees.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1088-1095
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• 2019

The information and communication technology that is being developed recently has been greatly influencing the automobile market. In recent years, devices equipped with IT technology have been installed for the safety and convenience of the driver. However, it has the advantage of increased convenience as well as the disadvantage of increasing traffic accidents due to driver's distraction. In order to prevent such accidents, it is necessary to develop safety systems of various types and ways. In this paper implements a platform that can recognize LDWS and FCWS and PDWS by using a single camera without using radar sensor and camera fusion and stereo camera method using two or more sensors, and proposes to study multi-function driving safety platform using a single camera by analyzing recognition rate evaluation and validity on a vehicle.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.160-163
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• 2021

최근 국내 전동킥보드 공유서비스의 증가 추세에 따라 전동킥보드와 보행자 혹은 차량과의 충돌사고가 증가하고 있다. 이러한 충돌사고로 인한 사고를 예방하기 위해 본 논문에서는 영상처리 기술에 기반한 후방위험요소 감지 시스템을 제안한다. 제안 시스템은 전동킥보드 사용자의 안전 헬멧에 라즈베리파이와 파이캠을 장착하여 가까이 오는 보행자나 차량을 영상처리 기법을 활용하여 인식하도록 하여 이들과의 충돌을 사전에 방지하도록 해준다. 제안 시스템의 정확도를 파악하기 위해 입력영상의 해상도별 처리속도와 정확도를 비교한다. 아울러, 제안 시스템을 안전 헬멧에 장착하여 테스트필드 실험을 통해 실제 환경에서 사용가능 여부를 검증한다.

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.75-83
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• 2018

Recently, autonomous vehicles have been actively studied. Pedestrian detection and recognition technology is important in autonomous vehicles. Pedestrian detection using CNN(Convolutional Neural Netwrok), which is mainly used recently, generally shows good performance, but there is a performance degradation depending on the environment of the image. In this paper, we propose a pedestrian detection system applying long-term memory structure of hippocampal neural network based on CNN network with LGP-FL (Local Gradient Pattern-Feature Layer) added. First, change the input image to a size of $227{\times}227$. Then, the feature is extracted through a total of 5 layers of convolution layer. In the process, LGP-FL adds the LGP feature pattern and stores the high-frequency pattern in the long-term memory. In the detection process, it is possible to detect the pedestrian more accurately by detecting using the LGP feature pattern information robust to brightness and color change. A comparison of the existing methods and the proposed method confirmed the increase of detection rate of about 1~4%.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.374-375
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• 2011

보행자 탐지를 위해 많은 알고리즘들이 제안되었고 그 중 HOG 알고리즘은 가장 좋은 성능을 보이는 알고리즘으로 알려져 있다. 하지만 HOG(Histogram of Oriented Gradients) 알고리즘은 연산량이 많아 계산 속도가 느려 실시간 시스템에 적용하기는 힘들다. 본 논문은 HOG 알고리즘으로 얻어진 특징 벡터를 이용해 보행자를 인식하는 방법의 속도 개선에 대하여 연구하였다. 기존 HOG 알고리즘에서 계산량이 많은 곳이 어느 부분인지 분석하고, 그 중 기울기와 방향을 계산하는 부분의 근사화를 통해 계산 속도를 높이는 방법을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.1064-1065
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• 2017

트레드밀 인터페이스는 사용자의 보행 모션을 인식하여 가상세계를 네비게이션 할 수 있는 보행 플랫폼이다. 특히 작은 보행 영역을 가지는 트레드밀의 경우, 보행자 속도 예측 방법에 의해 더욱 효과적인 지면 모션의 생성이 가능하다. 본 연구에서는 착용형 압력 센서로 부터 측정되는 족부 압력 데이터를 기반으로 하는 보행속도 예측 방법과 트레드밀 제어 방법을 제시하고자 한다. 속도 예측은 지면 반발력 데이터 중 압력중심의 변화 속도를 통해 도출되며, 예측된 속도를 트레드밀 속도 제어에 안정적으로 적용하기 위한 피드포워드 제어 방법을 제시한다. 또한 족부 압력 데이터 측정이 가능한 자율 제어 트레드밀 시스템 구현과 보행 실험 과정을 소개한다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.10
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• pp.13-19
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• 2007

Location awareness is one of the key functions to build U-city. Recently, many of works for location-aware systems are emerging to commercially apply to on-going large-scale apartment complex. As dwellers or cars being attached with active tags are moving in the U-city complex, the active tags periodically broadcast their own identifiers mu routers fixed along the street or in a building use those information to calculate location of thorn. There are several issues to be considered for such an environment. In this paper we propose i) a new architecture for location-aware system considering such issues ii) technical issues to implement it using active tags, and iii) a mathematical analytic model to investigate overall performance and verify it by comparing with actual experimental results. Through mathematical analysis, we can show that it is more efficient for the routers to send location signals than the tags do. We also show that there are several additional services available in the apartment complex. We conduscted several experiments hi a real ease parking lot to show that our system can locate the location of dwellers or cars.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1361-1368
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• 2020

The system for counting the number of people has traditionally been implemented in various ways. Existing systems include infrared sensors, lasers, cameras, etc. In the case of such an existing system, there are restrictions on space such as ceilings and sides of walls. In this paper, we propose a method of detecting the footsteps of pedestrians using a piezoelectric mat containing a number of piezoelectric sensors and counting the number of pedestrians passing simultaneously by using the data collected from the piezoelectric mat. When pedestrians pass over piezoelectric mats, the collected sensor data was aggregated using SPI communication and transmitted to PC server using TCP/IP communication. Performance analysis shows that approximately 600 step data can be recognized with 99% accuracy. This is to overcome the shortcomings of other counting systems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.62-72
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• 2023

Recently, the importance of monitoring and management measures for bicycle road related facilities has been increasing. However, research on the monitoring and evaluation of users' safety and convenience in walking spaces including bicycle path is insufficient. In this study, we would like to construct health monitoring data for cylists-pedestrians mixed road using a mobile mapping system, and propose a plan to calculate the level of service of the mixed roads from the perspective of pedestrians and cyclists using artificial intelligence based object detection techniques. The monitoring and level of service calculation method of cylists-pedestrians mixed roads proposed in this study is expected to be used as basic information for planning and management such as maintenance and reconstruction of walking spaces in preparation for the increase of electric bicycles and personal mobility in the future.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1227-1232
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• 2017

In this study, we have studied a system to reduce the inconvenience and the accident rate at the intersection when the visually impaired use traffic information by using pressure sensor and ultrasonic sensor. By using the pressure sensor to light the strip LED, the driver recognizes the pedestrian, thereby reducing the accident rate. In addition to the pedestrian signal light information, the ultrasonic sensor and Bluetooth transmit the bus position information to the application so that the user can listen to the voice.