• ICROS
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• v.16 no.3
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• pp.40-45
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• 2010

물체의 운동을 측정하기 위하여 관성 센서(inertial sensor)에 대한 배경 지식이 없는 사용자가 가속도계(accelerometer)를 사용하고자 할 경우 센서의 이름이 주는 혼동에 의하여 물체의 운동 가속도(acceleration)를 쉽게 얻어낼 수 있으리라 기대하게 된다. 반면, 가속도계가 실제 측정하여 주는 값은 비력 가속도(acceleration due to specific force)에 해당되므로 적절한 처리를 부가하지 않으면 기대한 바와 같이 물체의 운동 가속도를 얻을 수 없다. 가속도계의 측정값으로부터 운동 가속도를 추출하기 위해서는 중력장 가속도 (gravitational acceleration), 중력 가속도 (acceleration due to gravity), 비력 가속도, 그리고 운동 가속도 사이의 관계를 명확하게 구분 이해할 필요가 있다. 본 고에서는 앞선 고들에서 다룬(막대) 벡터, 좌표값, 좌표계, 좌표변환행렬, 그리고 코리올리 효과 등의 개념을 확장하여 다양한 개념의 가속도들을 구분 설명하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.94-95
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• 2017

지정된 경로에서 6축 센서의 가속도와 각속도를 이용하여 물체의 이동거리를 계산하는 경우 가속도 센서에서 나오는 데이터는 중력을 사용하여 값을 보내주는데, 평평한 상태에서는 중력가속도만 나오므로 영향이 없지만 물체가 움직이면서 기울어지거나 흔들리는 경우 중력가속도와 운동가속도가 더해지고 이에 따라 이동거리 계산에 오차가 발생한다. 이 논문에서는 가속도와 각속도만으로 보정이 힘들다고 판단하여 적외선 센서를 사용하여 이동거리를 산출하는 방법을 제안하고 시스템을 개발한다. 제안한 시스템은 지정된 경로를 따라 이동할 때 적외선 센서를 이용하여 궤도의 구분선을 인식하여 기존 6축 센서로 계산된 이동거리를 보정한다.

• The Korean Journal of Physiology
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• v.16 no.2
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• pp.153-157
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• 1982

It has been hypothesized that the effectiveness of the popular mini-trampoline as a conditioning device is due to the increased gravitational forces which are imparted to every cell in the body during its use. This study evaluated a means of determining the acceleration forces on a subject using a minitrampoline. By cinematic evaluation, a plot of the changes in distance over time was obtained. Using the formulas developed at the Arizona State University Crash Survival Investigators' School, the maximum acceleration forces were determined to be approximately $3.2+G_z$.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.254-259
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• 2013

A newly developed fall recognition algorithm using gravity weighted 3-axis accelerometer data as the input of HMM (Hidden Markov Model) is introduced. Five types of fall feature parameters including the sum vector magnitude(SVM) and a newly-defined gravity-weighted sum vector magnitude(GSVM) are applied to a HMM to evaluate the accuracy of fall recognition. A GSVM parameter shows the best accuracy of falls which is 100% of sensitivity and 97.96% of specificity, and comparing with SVM, the results archive more improved recognition rate, 5.2% of sensitivity and 4.5% of specificity. GSVM shows higher recognition rate than SVM due to expressing falls characteristics well, whereas SVM expresses the only momentum.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.63-65
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• 2013

본 논문에서는 가속도센서와 자이로센서를 통해 측정된 값을 무선 통신을 이용하여 스마트폰으로 전달하여 실시간으로 모션을 분석하는 스마트폰 실시간 모션 분석 알고리즘을 제안한다. 3축 가속도 센서의 실시간 모션 분석과 중력가속도를 사용한 모션 분석의 경우에는 장소나 높이 또는 주변의 자력에 따라 정확한 값을 획득하여 분석하기 어려운 점이 있다. 이에 본 논문에서는 가속도 센서와 자이로 센서를 통하여 보다 정밀한 모션 분석을 하였으며, 이를 이용하여 모션을 실시간으로 분석하여 활용하면 스포츠와 의학 등 다양한 분야에서 활용할 수 있을 것이다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.2
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• pp.106-113
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• 2017

Attitude determination algorithms for aircraft and land vehicles use earth gravitational vector and geomagnetic vector; hence, magnetometers and accelerometers are employed. In dynamic situation, the output from accelerometers includes not only gravitational vector but also motional acceleration, thus it is hard to determine accurate attitude. The acceleration compensation method treated in this paper solves the problem to compensate the specific force vector for motional acceleration calculated by a GPS receiver. This paper analyzed the error from the corrected vector regarded as a constant by conventional acceleration compensation method, and improve the error by rederivation from measurements. The analyzed error factors and improvements by the proposed algorithm are verified by computer simulations.

• Aerospace Industry
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• s.88
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• pp.44-45
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• 2005

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.69-77
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• 2022

Physical experiment through MBL has been used in many schools for a long time since students can check the experiment results immediately and conduct the experiment easily. However, conducting the experiment, not knowing the principle of the device or simply concentrating on the derived data has been raised as the problem of MBL experiment. To supplement this problem, this study measured the acceleration of gravity with the picket fence method, which is often used in MBL experiment, utilizing Arduino, calculated the error rate through a comparison to the actual acceleration of gravity and discussed the educational application of the experiment to measure it. As a result of the experiment, the error rate between the acceleration of gravity calculated by the experiment and the actual acceleration of gravity was about 1%, so it turned out that relatively accurate measurements were possible. Also, the sample mean of the experimental value was included in the confidence interval of 95%, so it could be concluded that it was a significant experiment. In addition, this study showed the possibility of the educational application of the experiment to measure it through the following: It can supplement the structural disadvantages of MBL; it can consider the interaction between Physics and Math; it is possible to converge with information course in STEAM education; and it is inexpensive to be equipped with the equipment. Hopefully, the physical experiment utilizing Arduino will further be revitalized in science gifted education based on this study.

• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.43-52
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• 2014

In this paper, we propose Gravity Removal and Vector Rotation algorithm for counting steps of wearable device, and we evaluated the proposed GRVR algorithm with Micro-Electro-Mechanical (MEMS) 3-axis accelerometer equipped in low-power wearable device while the device is mounted on various positions of a walking or running person. By applying low-pass filter, the gravity elements are canceled from acceleration on each axis of yaw, pitch and roll. In addition to DC-bias removal and the low-pass filtering, the proposed GRVR calculates acceleration only on the yaw-axis while a person is walking or running thus we count the step even if the wearable device's axis are rotated during walking or running. The experimental result shows 99.4% accuracies for the cases where the wearable device is mounted in the middle and on the right of the belt, and 91.1% accuracy which is more accurate than 83% of commercial 3-axis pedometer when worn on wrist for the case of axis-rotation.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.19 no.4
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• pp.30-36
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• 2011

Inertial navigation systems requires gravity model to compute gravity acceleration and its trajectory accuracy depends on the gravity model accuracy especially for a long range flight. The gravity model accuracy is important for satellite orbit prediction as well. The precision gravity model requires a precision coordinate transformation between inertial and Earth fixed coordinates. Precision gravity acceleration algorithms with a coordinate transform are studied and a computer program is developed. The effects of individual model components on trajectory error are analyzed.