• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.85-96
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• 2023

This study developed and evaluated a safe route guidance service for electric personal assistive mobility device used mainly by the mobility impaired people to improve their mobility. Thirteen underlying factors affecting the mobility of electric personal assistive mobility device have been derived through a survey with the mobility impaired people and employees in related organizations in Busan Metropolitan City. After assigning safety scores to individual factors and identifying the relevant factors along routes of interest with an object detection AI model, the safe route for electric personal assistive mobility device was provided through an optimal path-finding algorithm. As a result of comparing the general route of T-map and the recommended route of this study for the identical routes, the latter had relatively fewer obstacles and the gentler slope than the former, implicating that the recommended route is safer than the general one. As future works, it is necessary to enhance the function of a route guidance service based on the real-time location of users and to conduct spot investigations to evaluate and verify its social acceptability.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.5
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• pp.491-496
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• 2015

Electric handbike can be easily detachable to various sizes of manual wheelchair and the elderly and people with disabilities can use them easily. Therefore, connectors used for coupling between the handbike and manual wheelchair must secure structural stability for occupant safety. However, related research is rare. The aim of this study is to find the connector with highly structural stability by comparing static and dynamic mechanical characteristics among three typical connectors(a snatch lock, a slide latch, and a fastener) by computational simulations. To perform static and dynamic simulation, we referred to durability test based on Korean Standards and then calculated mechanical stresses in connectors. The results showed that the snatch lock addressed the lowest von-mises stress under the same mechanical condition. Therefore when using the combination of a handbike and a wheelchair, we concluded that the snatch lock is considered as the structurally stable connector to structural stability and usability.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.149-155
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• 2021

In this study, we intend to develop a defective road surface object recognition model that automatically detects road surface defects that restrict the movement of the transportation handicapped using electric mobile devices with deep learning. For this purpose, road surface information was collected from the pedestrian and running routes where the electric mobility aid device is expected to move in five areas within the city of Busan. For data, images were collected by dividing the road surface and surroundings into objects constituting the surroundings. A series of recognition items such as the detection of breakage levels of sidewalk blocks were defined by classifying according to the degree of impeding the movement of the transportation handicapped in traffic from the collected data. A road surface object recognition deep learning model was implemented. In the final stage of the study, the performance verification process of a deep learning model that automatically detects defective road surface objects through model learning and validation after processing, refining, and annotation of image data separated and collected in units of objects through actual driving. proceeded.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.851-860
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• 2020

With an increase in the aging population and a rising social interest in health and welfare, studies to improve healthcare in the elderly are being actively conducted. This study attempted to improve the current design and manufacture of elevating electric wheelchairs to enhance user safety and convenience. Seat design based on the user's body shape, convenience while boarding or alighting, caster turning radius and, safety and stability features that prevent shaking when the user gets up or sits down were improved. A driving experiment was conducted to evaluate the operation of the indoor electric wheelchair designed and manufactured with these additional functionalities. During the test, the performance parameters evaluated were continuous driving time, turning radius, maximum lifting and lowering load, maximum lifting height, noise level, minimum distance sensing by the driving auxiliary sensor, ability to interact with server and app programs, and the duty cycle maximum error rate. The test confirmed that this improved electric wheelchair successfully met target parameters. In a future study, we will evaluate this improved electric wheelchair from a user's perspective for its usability parameters, such as satisfaction, convenience and stability.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.415-424
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• 2019

In this paper, a minimum rotation radius was designed and fabricated to overcome the threshold so that elderly or disabled people who have difficulty moving can move and transfer safely and conveniently in a narrow room. In the indoor environment, where the sedentary culture develops, this study aimed to provide convenience for passengers with fracture diseases, geriatric diseases, and other knee and waist diseases. First, links, seats, armrests, covers, motors, batteries, chargers, controllers, etc. were attached to the frame so that they could be moved and lifted indoors. The product design and structure were designed considering the user's environment and physical characteristics, and IoT functions were added. A driving experiment was performed to confirm the operating performance of the manufactured indoor moving and lifting wheelchair. The performance tests, such as continuous running time, turning radius, maximum actuator load, maximum lift height, sound pressure level, minimum sensing distance of the driving aid sensor, interworking of server and app programs, device compatibility, and duty cycle error rate, were performed. As a result of the test, the built-in wheelchair could achieve the performance test target of each item and operate successfully.