• Journal of Practical Engineering Education
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• v.10 no.2
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• pp.119-124
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• 2018

Educational equipment that enables the user or device to recognize the indoor position by using the acceleration and angular velocity of the IMU (Inertial Measurement Unit) sensor is introduced. With this educational equipment, various position recognition and tracking algorithms can be learned and creative engineering design works can be realized. The data value of the IMU sensor is transmitted to the MCU (microcontroller unit) through $I^2C$ (Inter-Integrated Circuit), and the indoor position recognition algorithm is applied by processing the data value through the filter and numerical method. It is then designed to use wireless communication to send and receive processed values and to be recognized by the user. As an example using this equipament, the case of "Implementation and recognition of virtual position using computation of moving direction and distance using IMU sensor" is introduced, and various creative engineering design application is discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.757-770
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• 2020

We propose a hand gesture recognition method that is compatible with a head-up display (HUD) including small processing resource. For fast link adaptation with HUD, it is necessary to rapidly process gesture recognition and send the minimum amount of driver hand gesture data from the wearable device. Therefore, we use a method that recognizes each hand gesture with an inertial measurement unit (IMU) sensor based on revised correlation matching. The method of gesture recognition is executed by calculating the correlation between every axis of the acquired data set. By classifying pre-defined gesture values and actions, the proposed method enables rapid recognition. Furthermore, we evaluate the performance of the algorithm, which can be implanted within wearable bands, requiring a minimal process load. The experimental results evaluated the feasibility and effectiveness of our decomposed correlation matching method. Furthermore, we tested the proposed algorithm to confirm the effectiveness of the system using pre-defined gestures of specific motions with a wearable platform device. The experimental results validated the feasibility and effectiveness of the proposed hand gesture recognition system. Despite being based on a very simple concept, the proposed algorithm showed good performance in recognition accuracy.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.15 no.3
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• pp.223-234
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• 2011

Objectives: This study shows feasibility and suitability of a microelectromechanical system inertial measurement unit(MEMS-IMU) as a helpful measurement device for evaluating movement system impairment syndrome. Methods: We reviewed articles of two fields in this study. First, we reviewed articles about movement system impairment syndrome(MSIS) as a brand new viewpoint of diagnosing and treating musculoskeletal pain. Second, we reviewed articles about conventional motion analysis system and inertial measurement unit(IMU) to show the superiority of IMU in analyzing the human movement. All papers were searched by SciVerse, world largest search engine and database about many academic fields including engineering and medicine. Results: Some physical quantities of human motions can be useful to the diagnosis of MSIS, and those data can be obtained by the MEMS-IMU without the weak points of the conventional motion analysis systems. Conclusions: Using MEMS-IMU as a measurement unit for diagnosing and evaluating MSIS is feasible and can be extended to many further studies.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.38-46
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• 2011

3D motion analysis system which is currently widely used for walking analysis has limitations due to both necessity of wide space for many cameras for measurement, high cost, and complicated preparation procedure, which results in low accessability in use and application for clinical diagnosis. To resolve this problem, we developed 3-dimensional wireless ambulatory measurement system based on inertial sensor which can be easily applicable for clinical diagnosis for lower extremity deformity and developed system was evaluated by applying for 10 elderly people with diabetes mellitus. Developed system was composed of wireless ambulatory measurement module that consists of inertial measurement unit (IMU) which measures the gait characteristics, microcontroller which collects and precesses the inertial data, bluetooth device which transfers the measured data to PC and Window's application for storing and processing and analyzing received data. This system will utilize not only to measure lower extremity (foot) problem conveniently in clinical medicine but also to analyze 3D motion of human in other areas as sports science, rehabilitation.

• Journal of Aerospace System Engineering
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• v.4 no.1
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• pp.32-37
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• 2010

Guided weapon is very excellent strategy system than conventional weapons. Recently, several devices and a technology developed much developing more, inertia measuring device is one example. Inertia measuring device is device that is used to improe more accuracy of guided weapon, this device is operated by sensors of inside. Sensors of inside are parts that is very sensitive about impact or shock, heat that interact when shoot, it is main purpose that verify durability of sensor by heat delivered from outside in this study.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.5
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• pp.115-120
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• 2006

A Korean Road Roughness Classification(KRC) method is proposed. Using a dynamic road profiling device equipped with the Accelerometer Established Inertial Profiling Reference(AEIPR) method, road profile measurement is performed on various types of public paved roads in Korea. The road profiling data are processed to classify the characteristics of Korean road roughness. The resultant Korean road roughness classification(KRC) is shown different characteristics compared to the road classification proposed by ISO, MIRA, and Wong. The proposed KRC is composed of 8 classes(A-H, very good-poor) based on the power spectral density and is in good agreements with the characteristics of Korean paved road roughness and can be used well in vehicle ride comfort simulation using domestic road profile.

• ETRI Journal
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• v.42 no.1
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• pp.46-53
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• 2020

Gait analysis is an effective clinical tool across a wide range of applications. Recently, inertial measurement units have been extensively utilized for gait analysis. Effective gait analyses require good estimates of heel-strike and toe-off events. Previous studies have focused on the effective device position and type of triaxis direction to detect gait events. This study proposes an effective heel-strike and toe-off detection algorithm using a smart insole with inertial measurement units. This method detects heel-strike and toe-off events through a time-frequency analysis by limiting the range. To assess its performance, gait data for seven healthy male subjects during walking and running were acquired. The proposed heel-strike and toe-off detection algorithm yielded the largest error of 0.03 seconds for running toe-off events, and an average of 0-0.01 seconds for other gait tests. Novel gait analyses could be conducted without suffering from space limitations because gait parameters such as the cadence, stance phase time, swing phase time, single-support time, and double-support time can all be estimated using the proposed heel-strike and toe-off detection algorithm.

• Journal of Drive and Control
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• v.12 no.2
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• pp.27-33
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• 2015

Excavators are versatile earthmoving equipment that are used in civil engineering, hydraulic engineering, grading and landscaping, pipeline construction and mining. Effective operator training is essential to ensure safe and efficient operating of the machine. The virtual reality excavator based on simulation using conventional large size monitors is limited by the inability to provide a realistic real world training experience. We proposed a flexible observation method with a head tracking system to improve user feeling and sensation when operating a virtual reality excavator. First, an excavation simulator is designed by combining an excavator SimMechanics model and the virtual world. Second, a head mounted display (HMD) device is presented to replace the cumbersome large screens. Moreover, an Inertial Measurement Unit (IMU) sensor is mounted to the HMD for tracking the movement of the operator's head. These signals consequently change the virtual viewpoint of the virtual reality excavator. Simulation results were used to analyze the performance of the proposed system.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.730-744
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• 2023

The topic of this paper is the recognition of human activities using egocentric vision, particularly captured by body-worn cameras, which could be helpful for video surveillance, automatic search and video indexing. This being the case, it could also be helpful in assistance to elderly and frail persons for revolutionizing and improving their lives. The process throws up the task of human activities recognition remaining problematic, because of the important variations, where it is realized through the use of an external device, similar to a robot, as a personal assistant. The inferred information is used both online to assist the person, and offline to support the personal assistant. With our proposed method being robust against the various factors of variability problem in action executions, the major purpose of this paper is to perform an efficient and simple recognition method from egocentric camera data only using convolutional neural network and deep learning. In terms of accuracy improvement, simulation results outperform the current state of the art by a significant margin of 61% when using egocentric camera data only, more than 44% when using egocentric camera and several stationary cameras data and more than 12% when using both inertial measurement unit (IMU) and egocentric camera data.

• Journal of Biomedical Engineering Research
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• v.38 no.6
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• pp.330-335
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• 2017

Cardiac arrest is owing to the failure of the heart that makes the blood circulation stop. Arrested blood circulation prevents the supply of the oxygen and the glucose and it results the loss of consciousness and, finally, brain death. Many public institution installed the AED for emergency treatment, but, it is not efficient when the patient is alone. In this paper, we made multiplexed wearable device for cardiac arrest detection. With this device, we measure the individual's electrocardiography, heart sound and motion. If the cardiac arrest is detected, the device make a warning horn and transmit the signal for defibrillation. We obtain 98.33% of ECG data, 94.5% of PCG data and 98.38% of IMU data accuracy for each evaluation and 93.33% accuracy for integrated evaluation.