• Title/Summary/Keyword: 지능보행

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Implementation of Acceleration Sensor-based Human activity and Fall Classification Algorithm (가속도 센서기반의 인체활동 및 낙상 분류를 위한 알고리즘 구현)

  • Hyun Park;Jun-Mo Park;Yeon-Chul, Ha
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.2
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    • pp.76-83
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    • 2022
  • With the recent development of IT technology, research and interest in various biosignal measuring devices is increasing. As an aging society is in full swing, research on the elderly population using IT-related technologies is continuously developing. This study is about the development of life pattern detection and fall detection algorithm, which is one of the medical service areas for the elderly, who are rapidly developing as they enter a super-aged society. This study consisted of a system using a 3-axis accelerometer and an electrocardiogram sensor, collected data, and then analyzed the data. It was confirmed that behavioral patterns could be classified from the actual research results. In order to evaluate the usefulness of the human activity monitoring system implemented in this study, experiments were performed under various conditions, such as changes in posture and walking speed, and signal magnitude range and signal vector magnitude parameters reflecting the acceleration of gravity of the human body and the degree of human activity. was extracted. And the possibility of discrimination according to the condition of the subject was examined by these parameter values.

Development and Validation of AI Image Segmentation Model for CT Image-Based Sarcopenia Diagnosis (CT 영상 기반 근감소증 진단을 위한 AI 영상분할 모델 개발 및 검증)

  • Lee Chung-Sub;Lim Dong-Wook;Noh Si-Hyeong;Kim Tae-Hoon;Ko Yousun;Kim Kyung Won;Jeong Chang-Won
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.3
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    • pp.119-126
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    • 2023
  • Sarcopenia is not well known enough to be classified as a disease in 2021 in Korea, but it is recognized as a social problem in developed countries that have entered an aging society. The diagnosis of sarcopenia follows the international standard guidelines presented by the European Working Group for Sarcopenia in Older People (EWGSOP) and the d Asian Working Group for Sarcopenia (AWGS). Recently, it is recommended to evaluate muscle function by using physical performance evaluation, walking speed measurement, and standing test in addition to absolute muscle mass as a diagnostic method. As a representative method for measuring muscle mass, the body composition analysis method using DEXA has been formally implemented in clinical practice. In addition, various studies for measuring muscle mass using abdominal images of MRI or CT are being actively conducted. In this paper, we develop an AI image segmentation model based on abdominal images of CT with a relatively short imaging time for the diagnosis of sarcopenia and describe the multicenter validation. We developed an artificial intelligence model using U-Net that can automatically segment muscle, subcutaneous fat, and visceral fat by selecting the L3 region from the CT image. Also, to evaluate the performance of the model, internal verification was performed by calculating the intersection over union (IOU) of the partitioned area, and the results of external verification using data from other hospitals are shown. Based on the verification results, we tried to review and supplement the problems and solutions.

Evaluation of Transportation Policy Using Multidimensional Scaling Method (다차원척도법에 의한 교통정책 평가 인지 차이 분석에 관한 연구)

  • Lee, Won Gyu;Jung, Hun Young;Ko, Sang Seon;Yoon, Hang Mook
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.3D
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    • pp.255-261
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    • 2010
  • The evaluation regarding a transportation policy by an evaluation volition viewpoint there is a difference. Consequently the insurgent analysis which is simple compared to against the evaluation object it was accurate, the analysis which leads the order anger probably is necessary. The research which it sees for the evaluation regarding the transportation policy of the metropolis divided in road being understood, public transportation, parking and pedestrian environment, wide area transportation and transportation information and transportation field whole. And against these field it tried the ALSCAL method and MDPREF method which is a Multidimensional Scale method and it analyzed. The regression analysis result for a dimensional analysis ALSCAL method the case of the transportation policy star improvement degree which it follows in introduction presence of intelligence transportation system and MDPREF method it confronted to the transportation policy star improvement degree which it follows in expansion to construction of specific function appeared with the fact that it is the tendency probably. And the evaluation object and evaluation in the object which will cut the positioning one result was each divided in 4 group. And two methods all it was visible a similar tendency. The ALSCAL method currently transportation system construction degree condition in base and, the MDPREF method currently improvement degree of the transportation policy which it follows in traffic system construction appeared with the fact that it is desirable to establish a hereafter traffic policy in base.