• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.9
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• pp.905-912
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• 2008

Notion sickness is well known to be caused by long time exposure to the very low frequency motion in the multiple axes of human body Since the vestibular system for the perception of low frequency motion is located in the head, accurate measurement of 6 degree of freedom head motion is of great importance. In this study, the measurement system consisting of a safety helmet and 9 translational accelerometers was constructed for the estimation of 3 translational and 3 rotational motions of human head. Since estimation errors of 3 rotational components can be significantly magnified even by small offset of the sensitivity axis from the geometric center of an accelerometer, accurate measurement of sensitivity axis must be preceded. The method for accurate estimation of the offset was proposed, and the effect of offset on the estimation of angular acceleration was investigated.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1167-1172
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• 2015

This paper describes the implementation of wearable AHRS for an electromagnetic motion capture system that can trace and analyze human motion on the principal nine axes of inertial sensors. The module provides a three-dimensional (3D) attitude and heading angles combining MEMS gyroscopes, accelerometers, and magnetometers based on the extended Kalman filter, and transmits the motion data to the 3D simulation via Wi-Fi to realize the unrestrained movement in open spaces. In particular, the accelerometer in AHRS is supposed to measure only the acceleration of gravity, but when a sensor moves with an external linear acceleration, the estimated linear acceleration could compensate the accelerometer data in order to improve the precision of measuring gravity direction. In addition, when an AHRS is attached in an arbitrary position of the human body, the compensation of the axis of rotation could improve the accuracy of the motion capture system.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.216-220
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• 2009

In this paper we propose a motion recognition method for handheld controller 3-D acceleration signals, generated by 3 axis accelerometer in the controller, are transmitted to the computer by Bluetooth communication. We extract motion segments from continuous acceleration signals and apply to each motion model, which is trained in training phase. Hidden Markov Model was used to model each motion. We applied proposed method to three motion sets, the recognition result was good enough to practical use.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.55 no.9
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• pp.456-460
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• 2006

This paper deals with a novel autocalibration method of three-axis micromachined accelerometers applied to a new digital intelligent putter for golfers. This putter can help golfers monitor and analyze their putting posture and therefore modify their putting action to get better score and enjoy their lives through golf. The micromachined accelerometers to get information of the motion are the essential part of the putter to measure the three-axis acceleration as accurately as possible. This paper presents an efficient autocalibration algorithm to find the offset and sensitivity of accelerometers by only using the static measurement data at six different positions. The experimental results on the developed putters show the validity of the proposed algorithm for the new smart putter.

• Proceedings of the KIPE Conference
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• 2006.06a
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• pp.302-304
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• 2006

This paper deals with a novel autocalibration method of three-axis micromachined accelerometers applied to a new intelligent putter for golfers. This putter can help golfers monitor and analyze their putting posture and therefore modify their putting action to get better score and enjoy their lives through golf. The micromachined accelerometers to get information of the motion are the essential part of the putter to measure the three-axis acceleration as accurately as possible. This paper presents autocalibration algorithm to find the offset and sensitivity of accelerometers only by using six different static measurement data. The experimental results shows the validity of the algorithm for the new smart putter.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.469-475
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• 2015

This paper describes about the method for designing an extended Kalman filter to accurately measure the position of the spatial-phase system using a semiconductor sensor. Spatial position is expressed by the correlation of the rotated coordinate system attached to the body from the inertia coordinate system (a fixed coordinate system). To express the attitude, quaternion was adapted as a state variable, Then, the state changes were estimated from the input value which was measured in the gyro sensor. The observed data is the value obtained from the acceleration sensor. By matching between the measured value in the acceleration sensor and the predicted calculation value, the best variable was obtained. To increase the accuracy of estimation, designation of the extended Kalman filter was performed, which showed excellent ability to adjust the estimation period relative to the sensor property. As a result, when a three-axis gyro sensor and a three-axis acceleration sensor were adapted in the estimator, the RMS(Root Mean Square) estimation error in simulation was retained less than 1.7[$^{\circ}$], and the estimator displayed good property on the prediction of the state in 100 ms measurement period.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.559-565
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• 2017

A lot of studies have been conducted to recognize the motion state or behavior of the user using the acceleration sensor built in the smartphone. In this paper, we applied the neural networks to the 3-axis acceleration information of smartphone to study human behavior. There are performance issues in applying time series data to neural networks. We proposed a multi-temporal neural networks which have trained three neural networks with different time windows for feature extraction and uses the output of these neural networks as input to the new neural network. The proposed method showed better performance than other methods like SVM, AdaBoot and IBk classifier for real acceleration data.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.98-105
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• 2010

Health of the people involved in blood sugar, blood pressure, activity, and using bio-sensors to obtain biometric information, the system for monitoring health research for development is a lot. This paper analyzes the bio information by monitoring the u-health care agent system was developed. Activity measurement technology that uses 3-axis accelerometer sensor. 3-axis acceleration sensors, using information obtained from activity to activity analysis to calculate the exact algorithm was developed. More accurate than the existing system to calculate the calorie consumption, it is stored in the database management. and you can check your health status using of activity and bio-information.

• The Journal of the Acoustical Society of Korea
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• v.24 no.1E
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• pp.7-15
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• 2005

This paper addresses issues encountered in measuring the general, 6-degree-of-freedom motion of a human head, A complete mathematical description for measuring the head motion using the six-accelerometer configured bite-bar is suggested, The description shows that the six-axis vibration cannot be completely obtained without the roll, pitch and yaw angular velocity components, A new method of estimating the three orthogonal (roll, pitch and yaw) angular velocities from the six acceleration measurements is introduced. The estimated angular velocities are shown to enable further quantitative error analysis in measuring the translational and angular accelerations at the head. To make this point clear, experimental results are also illustrated in this paper. They show that when the effects of angular velocities are neglected in the head vibration measurement the maximum percentage errors were observed to be more than $3 \%$ for the angular acceleration of the head and to be close to $5 \%$ for its translational acceleration, respectively. It means that the inclusion of all the angular velocity dependent acceleration components gives more accurate measurement of the head vibration.

• Journal of Sensor Science and Technology
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• v.27 no.3
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• pp.165-169
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• 2018

A single-axis Cubli frame realized simply with an IMU sensor and DC motor is presented herein. To maintain the balance on the Cubli frame, an LQR controller based on a Lagrangian derivation of the dynamics was designed, which utilized the state variables of the frame angle and its angular acceleration, as well as the wheel angle and its angular acceleration. The designed LQR controller showed a settling time balancing capability of approximately two seconds and 40% of the maximum overshoot in Matlab/Simulink simulations. Our experimental results of the fabricated Cubli frame matched with the simulation results. It maintained balancing at the reference position even though an initial offset as well as external disturbance during the balancing was applied.