• Title/Summary/Keyword: 스마트 보행분석

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Effects of Smartphone Usage on Walking Speed using Machine Learning Method (기계학습을 이용한 스마트폰 이용이 보행속도에 미치는 영향 분석)

  • Jin, Hye ryun;Do, Myung sik
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.18 no.2
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    • pp.93-103
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    • 2019
  • This study analyzed the impact of smartphone usage on walking speed during walking on two pedestrian walkways in Daejeon Metropolitan City. For the analysis, the video data about the actual use of smartphone was acquired and the walking speed was calculated based on the walking density of the pedestrian Level Of Service(LOS) presented in the Road Capacity Manual. Multiple regression analysis and decision tree using machine learning were used to analyze the impact of smartphone usage on walking speed, and as the explanatory variables, gender, disable smartphone, use of smartphone using auditory function, use of smartphone using visual function, LOS A, LOS B, LOS C were adopted. The result showed that LOS C had the highest impact on walking speed change and the women's group using their visual function was founded to have the slowest walking speed in LOS C. In particular, the author found that walking speed significantly decreased in the case of use of visual function rather than listening to music or the hearing on the phone.

Development of Insole Type Capacitive Pressure Sensor for Smart Gait Analysis (스마트 보행분석을 위한 깔창 형태의 전기용량성 압력센서 개발)

  • Woo, Hyunsoo;Min, Se Dong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2012.07a
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    • pp.411-412
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    • 2012
  • 본 논문에서는 인간의 가장 기본적이며 기초적인 운동인 걸음걸이로부터 검출할 수 있는 걸음 수 및 보행분석을 위해 전도성 섬유를 이용한 전기용량성압력 센서를 깔창형태로 개발하였다. 개발된 깔창 형태의 센서는 보행시의 압력을 측정하여 보행신호를 검출하고, 검출된 신호를 이용하여 걸음 수 및 보행 분석을 실시하였다. 개발된 센서의 성능 검증을 위하여 상용 만보계 및 관찰자의 수계로 도출된 보수를 비교하였으며, 자세에 따른 압력차이를 측정하였다. 기존의 상용 만보계는 저속(1 Km/h)으로 걸었을 때 보수가 잘 측정되지 않은 반면 개발된 센서는 저속에서도 관찰자 수계대비 정확한 보수를 도출 할 수 있었다. 또한 자세에 따라 압력 값을 토대로 사용자의 자세를 모니터링 할 수 있음을 보였다. 본 연구는 향후 스마트폰과 무선 연동하는 스마트 보행관리 시스템을 개발하기 위한 기초연구이다.

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Effects of Smartphone Usage Patterns on Human Factors of Pedestrian Safety: Focused on Users in Their 20's and 30's (스마트폰 이용행태가 보행안전도의 인적요인에 미치는 영향: 20~30대 사용자들을 중심으로)

  • You, Seung-Hee;Kwon, Chang-Hee
    • Journal of Digital Convergence
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    • v.15 no.9
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    • pp.79-85
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    • 2017
  • The purpose of this study was to investigate utilization behaviors of smartphones while walking that are increasing recently and to examine the effects of smartphone usage patterns on human factors of pedestrian safety. In order to understand the motives and actual conditions of pedestrians' use of smart phones, a online questionnaire survey was conducted on people in their 20~30s who use smartphones. As a result, 98.6% of the respondents had experience using smartphones while walking. After performing the survey by extracting 17 uses the synchronization elements in the prior studies was extracted with two factors from the factor analysis. Particularly, respondents whose motivation to use smartphones was 'pandemic' were analyzed to have an influence on the risk of accident due to use of smartphones among human factors of pedestrian safety.

Influence of Smart Phone Use on Gait Pattern in Healthy Adults (스마트폰 사용이 건강한 성인의 보행패턴에 미치는 영향)

  • Moon, Jong-Hoon;Kim, Sung-Hyun;Na, Chang-Ho;Hong, Deok-Gi;Heo, Sung-Jin
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.1
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    • pp.199-206
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    • 2018
  • This study was to investigate the Influence of smart phone use on gait in healthy adults. Twenty healthy adults were recruited in this study. All subjects performed twice for each normal gait and smart phone gait. The normal gait walked at their chosen speed, and the smart phone gait walked while watching the video. GAITRite system was used to identify the temporal and spatial variables related to the gait pattern during walking. Statistical analysis was analyzed by paired t-test. In comparison of temporal variables, smart phone gait was significantly lower in gait speed and cadence than in normal gait(p<.05), and was significantly longer in single support time and double support time(p<.05). In comparison of spatial variables, smart phone gait was significantly shorter in step length and stride length than in normal gait(p<.05) and significantly longer in step width(p<.05). The results of this study demonstrated that smartphone use can negatively affect the correct gait patterns during walking.

Analysis of Abnormal Gait and Over Pronation/Supination Gait Using Smart Insole (스마트 인솔을 이용한 비정상 보행 및 발의 내·외전 분석)

  • Kim, Jinu;Lee, Eun-Young;Kim, Dongho
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.10a
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    • pp.907-910
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    • 2018
  • 오늘날 보행 분석은 여러 하지 관절, 뼈 및 근육, 신경 등의 이상을 판단할 수 있는 매우 중요한 지표로 사용되고 있다. 하지만 비정상 보행, 비대칭 보행을 하고 있는 사람들은 자신이 인지 할 수 있을 만큼 그 문제의 정도가 심각하지 않은 상태라면, 그 사실을 모른 채 살아간다. 결국 이런 문제가 지속된다면 향후 큰 질병이 발생하는 요인이 될 수 있다. 본 논문에서는 40개의 압력센서를 내장한 인솔을 통해 각 발의 압력 데이터를 수집하여 미리 정의한 정상 보행 시 나타나는 압력 분포를 기준으로 비정상 보행 여부를 판단하고 보행 시 나타나는 부분별 압력분포 데이터를 이용하여 보행 시 사용자 발의 과내전(over pronation)과 과외전(over supination) 경향도 분석하였다. 스마트 인솔을 사용하여 시간과 공간의 제약이 없는 사용자 친화적이면서 비정상 보행 판단 및 발의 과내 외전 경향 분석에 대해 자가 진단을 보조할 수 있을 것으로 기대한다.

Constructing Effective Smart Crosswalk Traffic Light Mechanism Through Simulation Technique (시뮬레이션 기법을 통한 효율적 스마트 보행신호등 메커니즘 구축)

  • Lee, Hyeonjun;Moon, Soyoung;Kim, R.Youngchul;Son, Hyeonseung
    • KIISE Transactions on Computing Practices
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    • v.22 no.2
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    • pp.113-118
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    • 2016
  • The walking speed of handicapped people generally is slower than that of normal people. So it is difficult for them to cross at crosswalks within the allotted time provided by the traffic light. This problem can be solved by expanding the time of the traffic light. However, if the latency of the traffic light is increased without distinguishing the handicapped among all other pedestrians, the efficiency of traffic signal lights will decrease. In this paper, we propose a smart traffic signal connecting mechanism between the previous pedestrian traffic signal and a pedestrian's device (smartphone). This Smart pedestrian traffic light, through this mechanism, minimizes traffic congestion by providing additional walking time only to the handicapped among pedestrians. This crosswalk traffic light recognizes the handicapped using a technique called Internet of things (IOT). In this paper, we extract the data necessary to build an effective smart crosswalk traffic light mechanism through simulation techniques. We have extracted different kinds of traffic signal times with our virtual simulation environment to verify the efficiency of the smart crosswalk pedestrian traffic light system. This approach can validate the effective delay time of the traffic signal time through a comparison based on number of pedestrians.

A Gait Analysis Using Smart Phone Images of the Knee Joint Angle and Stride Length (스마트폰 영상을 이용한 슬관절 각도 및 활보장에 대한 보행분석)

  • Jang, J.H.;Lim, C.J.;Song, K.H.;Chung, S.T.
    • Journal of rehabilitation welfare engineering & assistive technology
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    • v.7 no.2
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    • pp.139-144
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    • 2013
  • Various types of disease in the nervous and musculoskeletal system can change gait, and the gait analysis is very important in determining the progression of the disease. Most methods of analyzing gait are subject to high-priced equipment and spatial restrictions. This study used smart phone images and the walking track analysis program to make a comparative analysis with the existing gait analysis on the basis of the stride length measurements and the changes in the knee joint angle for walking. The test necessary to analyze gait was conducted in seven healthy men, and data about the angle of right and left knee joints and stride length were used to analyze gait. The gait analysis in this study obtained the similar results to the existing ones. The use of the methods suggested in this study will enable gait analysis to be made without high-priced equipment and spatial restrictions.

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Effects of Smart Phone Use on the Gait Parameters When Healthy Young Subjects Negotiated an Obstacle (스마트폰 사용이 정상인의 장애물 보행에 미치는 영향)

  • Kim, Chang-Yong;Jeong, Hye-Won;Kim, Hyeong-Dong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.1
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    • pp.471-479
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    • 2015
  • This study examined the effects of smart phone use while young adults negotiated an obstacle (2 cm high). Seventy-four young adults (mean age: $23.76{\pm}3.17years$, age range: 20-27 years) participated in the study. They were allocated randomly into two groups; smart phone group and no smart phone group. The smart phone group negotiated an obstacle while simultaneously using a smart phone at a self-paced speed whereas the no smart phone group negotiated an obstacle with no special option. A motion analysis system were used to measure the gait parameters, such as toe clearance, cadence, step length, step width, stride length, and walking velocity in two groups. The toe clearance, and step-width, cadence, and step-length were significantly greater for the smart phone group than the no smart phone group (p<.05) and the walking velocity was significantly lower in the smart phone group (p<.05). On the other hand, there was no significant difference in the stride length between the two groups. This study suggests that smart phone use degrades the obstacle avoidance abilities of healthy young adults, which may increase risk of falls.

The Current Situation of "Using a Smartphone while Doing Something Else" and Related Factors ("보행 시 스마트 폰 사용"의 현상과 관련 요인)

  • Tomomi, MIZUNO;Katsum, TOKUDA;CHO, Hong-joong
    • Journal of Digital Convergence
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    • v.14 no.12
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    • pp.561-569
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    • 2016
  • Purpose : We will clarify the situation of using a smartphone and what kind of factors are currently related when people use a smartphone while doing something else in order to obtain basic information to educate people to prevent the use of smartphone while doing something else. Methods : We conducted an anonymous self-administered questionnaire survey with 885 people who commuted by train to six companies located in Tokyo, Chiba, and Osaka and 550 university students who commuted by train to five universities located in the same areas. The research period was from April to May of 2014. Results : 33% of the subjects used a feature phone and 73% of the subjects used a smartphone. 38% of them listened to music, using their smartphones or feature phones while walking. Binominal logistic regression analysis was done with dependent variables of using a smartphone while walking and independent variables of age, sex, and educational advertisement. The results showed that people in their 20s used a smartphone while walking 4.93 times more than people in their 30s(p <0.00). No significant difference was found in the relationship between sex and educational advertisement(poster, TV, or magazine) and using a smatphone while doing something else.

Discussion on the Value of Using Gait Analysis System Using Smart Shoes (스마트 신발을 활용한 보행분석 시스템 활용 가치에 대한 논의)

  • Park, Tae-Sung;Shin, Myung-Jun;Lee, Lee-Eun
    • Journal of Convergence for Information Technology
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    • v.9 no.3
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    • pp.128-133
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    • 2019
  • The purpose of this study is to verify whether the data measured by the researcher and the smart shoe sensor data are the same or similar by performing the 6 - minute walking test and time up and go test after putting smart shoes on a normal person. Ten normal adult males participated. After wearing smart shoes, they performed a 6-minute walk test and a time up and go test. The results of this experiment show that the accuracy of the current sensor is high. The difference in the distance of the 6-minute walking test is that the difference is because the turning point, which is not calculated in the actual 30-m track, measures the distance. From this point of view, it can be seen that smart shoes measure more accurate distance and it is expected that various tests will be possible through smart sensors.