• The Journal of Korean Physical Therapy
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• 제22권6호
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• pp.59-63
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• 2010

Purpose: Driving a car is an essential component of daily life. For safe driving, each driver must perceive sensory information and respond rapidly and accurately. Brake response time (BRT) is a particularly important factor in the total stopping distance of a vehicle, and therefore is an important factor in traffic accident prevention research. The purpose of the current study was (1) to compare accelerometer. BRTs analyzed by three different methods and (2) to investigate possible correlations between accelerometer-BRTs and foot switch-BRTs, which are measured method using a foot switch. Methods: Eighteen healthy subjects participated in this study. BRT was measured with either a tri-axial accelerometer or a footswitch. BRT with a tri-axial accelerometer was analyzed using three methods: maximum acceleration time, geometrical center, and center of maximum and minimum acceleration values. Results: Both foot switch-BRTs and accelerometer-BRTs were delayed. ANOVA for accelerometer BRTs yielded significant main effects for axis and analysis, while the interaction effect between axis and analysis was not significant. Calculating the Pearson correlation between accelerometer-BRT and foot switch-BRT, we found that maximum acceleration time and center of maximum and minimum acceleration values were significantly correlated with foot switch-BRT (p<0.05). The X axis of the geometrical center was significantly correlated with foot switch-BRTs (p<0.05), but Y and Z axes were not (p>0.05). Conclusion: These findings suggest that the maximum acceleration time and the center of maximum and minimum acceleration value are significantly correlated with foot switch-BRTs.

• 센서학회지
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• 제25권2호
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• pp.79-85
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• 2016

This paper proposes a threshold-based fall recognition algorithm to discriminate between falls and activities of daily living (ADL) using a tri-axial accelerometer and a bi-axial gyroscope sensor mounted on the upper sternum. The experiment was executed ten times according to the proposed experimental protocol. The output signals of the tri-axial accelerometer and the bi-axial gyroscope were measured during eight falls and eleven ADL action sequences. The threshold values of the signal vector magnitude (SVM_Acc), angular velocity (${\omega}_{res}$), and angular variation (${\theta}_{res}$) parameter were calculated using MATLAB. From the preliminary study, three thresholds (TH1, TH2, and TH3) were set so that the falls could be distinguished from ADL. When the parameter SVM_Acc is greater than 2.5 g (TH1), ${\omega}_{res}$ is greater than 1.75 rad/s (TH2), and ${\theta}_{res}$ is greater than 0.385 rad (TH3), these action sequences are recognized as falls. If at least one or more of these conditions is not satisfied, the sequence is classified as ADL.

• 센서학회지
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• 제26권1호
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• pp.7-14
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• 2017

A threshold-based fall recognition algorithm using a tri-axial accelerometer and a bi-axial gyroscope mounted on the skin above the upper sternum was proposed to recognize fall-like activities of daily living (ADL) events. The output signals from the tri-axial accelerometer and bi-axial gyroscope were obtained during eight falls and eleven ADL action sequences. The thresholds of signal vector magnitude (SVM_Acc), angular velocity (${\omega}_{res}$), and angular variation (${\theta}_{res}$) were calculated using MATLAB. When the measured values of SVM_Acc, ${\omega}_{res}$, and ${\theta}_{res}$ were compared to the threshold values (TH1, TH2, and TH3), fall-like ADL events could be distinguished from a fall. When SVM_Acc was larger than 2.5 g (TH1), ${\omega}_{res}$ was larger than 1.75 rad/s (TH2), and ${\theta}_{res}$ was larger than 0.385 rad (TH3), eight falls and eleven ADL action sequences were recognized as falls. When at least one of these three conditions was not satisfied, the action sequences were recognized as ADL. Fall-like ADL events such as jogging and jumping up (or down) have posed a problem in distinguishing ADL events from an actual fall. When the measured values of SVM_Acc, ${\omega}_{res}$, and ${\theta}_{res}$ were applied to the sequential processing algorithm proposed in this study, the sensitivity was determined to be 100% for the eight fall action sequences and the specificity was determined to be 100% for the eleven ADL action sequences.

• 대한안전경영과학회지
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• 제14권1호
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• pp.87-93
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• 2012

The purpose of this study suggests a personalized algorithm of physical activity energy expenditure prediction through comparison and analysis of individual physical activity. The research for a 3-axial accelerometer sensor has increased the role of physical activity in promoting health and preventing chronic disease has long been established. Estimating algorithm of physical activity energy expenditure was implemented by using a tri-axial accelerometer motion detector of the SVM(Signal Vector Magnitude) of 3-axis(x, y, z). A total of 10 participants(5 males and 5 females aged between 20 and 30 years). The activities protocol consisted of three types on treadmill; participants performed three treadmill activity at three speeds(3, 5, 8 km/h). These activities were repeated four weeks.

• International Journal of Internet, Broadcasting and Communication
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• 제13권2호
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• pp.260-266
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• 2021

Handwriting using the dominant and nondominant arms was analyzed in 52 young adults with the aid of a three-axial accelerometer. We measured a signal vector magnitude (SVM) and the percentage of the total signal vector magnitude (%TSVM) for the metacarpophalangeal joint (MCP), radial styloid process (RSP), and lateral epicondyle (LE) of both arms. The SVM for the MCP was lower in the dominant arm than the nondominant arm, whereas that for the RSP was higher. %TVSM was lower for the MCP than for the RSP and LE in the nondominant arm, but higher for the MCP than for the LE in the nondominant arm. These findings suggest that controlling the MCP will improve the quality of handwriting, including when using the nondominant arm.

• 한국콘텐츠학회논문지
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• 제11권12호
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• pp.103-111
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• 2011

최근 만성질환을 예방하고 건강을 증진시킬 목적으로 신체활동에 대한 중요성이 인식되면서 신체활동 연구가 활발히 진행되고 있다. 본 연구에서는 3축 가속도 동작감지기 x, y, z축에 대한 $cm/s^2$의 가속도 합인 SVM(Signal Vector Magnitude)를 이용하여 신체활동 에너지 소비량 알고리즘을 구현하였다. 기존 실험을 통해 타당도가 입증된 COUNT 방식의 Freedson, Hendelman, Leenders, Yngve 알고리즘에 SVM 방식을 적용하여 구현 하였다. COUNT와 SVM 상관관계 분석을 위하여 총 10명의(성인 남성 5명, 여성 5명, 20 ~ 30 대) 피험자를 대상으로 실험을 진행하였다. 피험자는 트레드밀위에서 3단계 신체활동 (걷기: 3km/h, 빨리 걷기: 5km/h, 러닝: 8km/h)을 1주 간격으로 4주 간 반복 실험을 진행하였다. 실험결과 얻어진 COUNT와 SVM의 간의 상관관계를 분석하여 다양한 신체활동에 따른 맞춤형 에너지 측정 알고리즘을 구현하였다.

• 재활복지공학회논문지
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• 제5권1호
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• pp.27-33
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• 2011

3축 가속도 동작감지기를 이용하여 x, y, z축에 대한 가속도 합인 SVM(Signal Vector Magnitude)를 적용한 신체활동 에너지 소비량과 신체활동 강도 예측 알고리즘을 구현하였다. 신체 건강한 20~30대 성인 남성 5명, 여성 5명을 대상으로 골반 장골능에 엑티그라프(LLC, USA)와 피트미터(Fit.life. korea)를 착용하고 트레드밀위에서 3단계 신체활동(걷기: 3km/h, 빨리 걷기: 5km/h, 러닝: 8km/h)을 수행하였다. 각 신체활동 단계별로 7분간 신체활동을 수행하고 5분간 휴식을 통하여 각 신체활동 단계별로 안정화된 상태에서 실험하였다. 이러한 실험을 1주 간격으로 4주간 반복 실험을 진행하였다. 실험결과 얻어진 엑티그라프와 피트미터의 600여개 데이터 상관관계를 분석하여 METs와 kcal 그리고 신체활동 강도를 구분하는 알고리즘을 구현하였다.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2005년도 추계 종합학술대회 논문집
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• pp.548-551
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• 2005

본 연구에서는 3푹 가속도센서를 소형 센서모듈로 구성하고 이를 사람의 신체 부위에 부착하여 센서의 3차원적 방향에 구애되지 않고 동작에 의한 중력방향의 가속도를 계산할 수 있는 장치와 알고리즘을 개발하였다. 센서모듈을 이용하여 컴퓨터 시스템에 의해 사람의 보행 및 동작을 측정하기 위해서는 정량적인 처리가 가능하도록 데이터를 가공하여야 한다. 센서 모듈로부터 데이터의 획득, 가능한 범위의 직교 좌표계로 변환, 중력방향의 단일 스칼라 값 변환의 과정으로 센서 출력 데이터를 정규화 하였다.

• 한국IT서비스학회지
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• 제10권1호
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• pp.65-72
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• 2011

In this paper, we consist of three dimensional acceleration sensor as a small-sized sensor module to acquire base technologies that need to estimate exhibition audience' moving distance. and that we developed algorism and device that can calculate acceleration in gravity direction with attaching it to people's body part without regard to three dimensional direction. By making use of the sensor module, we have to process the data that let it quantitatively process possible to measure people's walk and movement by computer system. We normalized sensor output data in the process of change from sensor module to acquisition of data, rectangular coordinates and single scalar acceleration value in gravity direction. Printed out sensor data attaching sensor module to people's body part is used for motion pattern detection after normalization, Motion sensor devised mode change algorism because it print data of other pattern according to attached position of body. For algorism design, we collected data occurring during walking about subject and we also defined occurring problem domain after analyzing the data. We settle defined problem domain and that we simulated the walking number measuring instrument with highly efficient in restricted environment.

• 인터넷정보학회논문지
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• 제12권3호
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• pp.17-26
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• 2011

본 논문에서는 3축 가속도 센서를 이용하여 사람이 보행 시 발생하는 센서 데이터를 획득하여 실시간 걸음 수 검출이 가능한 웨어러블 디바이스를 개발하였다. 피험자 59명을 대상으로 트레드밀에서 Actical 과 본 연구에서 개발된 디바이스를 착용 후 36분 동안 테스트 프로토콜에 따라 느리게 걷기, 걷기, 빠르게 걷기, 천천히 뛰기, 뛰기, 빠르게 뛰기 등의 다양한 걸음 속력에서 테스트를 진행하였다. 3축 가속도 센서의 X, Y, Z축 출력 값을 하나의 대표 값으로 처리하는 신호벡터크기(Signal Vector Magnitude : SVM)를 사용하였다. 또한 정확한 걸음 수를 검출하기 위해 휴리스틱 알고리즘(Heuristic Algorithm : HA)을 제안하고 적응적인 임계값 알고리즘(Adaptive Threshold Algorithm : ATA), 적응적인 잠금 구간 알고리즘(Adaptive Locking Period Algorithm : ALPA)을 제안한다. 실험결과 제안하는 알고리즘의 걸음 수 인식률은 97.34%로 Actical의 인식률(91.74%)보다 5.6%향상 되었다.