• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.770-776
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• 2021

Positioning systems have been actively researched and developed over the past few years and have been used in many applications. This paper presents a method to determine a location in a large space using a sensor system consisting of an accelerometer and a single-axis gyroscope. In particular, to consider usability, a sensor device was loosely worn on the waist so that the experimental data could be used in practical applications. Based on the experimental results of circular tracks with radiuses of 1m and 3m, in this paper, an algorithm using the threshold of rotation angle was proposed and applied to the experimental results. A tracking experiment was performed on the grid-pattern track model. For raw sensor data, the average deviation between the final tracking point and the target point was approximately 15.2 m, which could be reduced to approximately 4.0 m using an algorithm applying the rotation angle threshold.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.640-645
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• 2013

This paper presents a step length estimation algorithm for Pedestrian Dead Reckoning using linear calibrated ZUPT (zero velocity update) with a foot mounted IMU. The IMU consists of 3 axis accelerometer, gyro and magnetometer. Attitude of IMU is estimated using an inertial navigation algorithm. To increase accuracy of step length estimation algorithm, we propose a stance detection algorithm and an enhanced ZUPT. The enhanced ZUPT calculates firefighter's step length considering velocity error caused by sensor bias during one step. This algorithm also works efficiently at various motions, such as crawling, sideways and stair stepping. Through experiments, the step length estimation performance of the proposed algorithm is verified.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.2
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• pp.75-83
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• 2005

NASA/DLR Gravity Recovery and Climate Experiment (GRACE) mission, which consists of two co-orbiting low altitude satellites, is to measure the Earth gravity field with unprecedented accuracy. Its key instruments include inter-satellite ranging systems and three-axis accelerometers. For the preliminary design and requirements analysis, extensive instrument simulation models are developed. These modeling techniques and orbit-gravity field estimation techniques are described.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.1
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• pp.29-34
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• 2015

The ECG(Electrocardiograph) ambulatory test as called Holter is performed usually to diagnose several heart diseases causing different arrhythmias. This paper exposes the insights of the design of a 10-lead ambulatory ECG recorder. Reducing the size and minimizing the power consumption of the ECG recorder are crucial to allow long recording time without causing discomfort to the patient. This paper proposes lower hardware design and differential compression algorithm to extend the maximum 72 hours recording time in consideration of smaller and light-weighted recorder size. The performance results by newly introduced compression algorithm are shown and discussed.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.91-98
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• 2019

Accidents of worker that occur in isolated places are difficult to rescue, unlike general construction accidents. There is a problem of communication limitation when an accident occurs in an isolated place. Also, it is difficult to search the accident place due to the absence of CCTV. In order to solve these problems, this paper proposes a device that combines IoT technology with a safety helmet, which must be worn in the workplace. The proposed device additionally designs and implements a real-time PPG(Photoplethysmography) sensor, body temperature sensor, accelerometer sensor and a camera sensor on the helmet. The proposed helmet system allows the user and the control center to monitor the state of the worker. In addition, when an abnormal biological signal or fall occurs to the worker, the image is transmitted to the control center. By using the proposed system, it is possible to check the status of the worker in real time, so that it has an advantage that it can cope with the accident quickly.

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.33-39
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• 2019

In this paper, we propose a parametric model for analyzing the motion information obtained from the acceleration sensors to measure the activity of the human body. The motion of the upper body and the lower body does not occur at the same time, and the motion analysis method using a single motion sensor involves a lot of errors. In this study, the 3-axis accelerometer is attached to the arms and legs, the body's activity data are measured, the momentum of the arms and legs are calculated for each channel, and the linear predictive coefficient is obtained for each channel. The periodicity of the upper body and the lower body is determined by analyzing the correlation between the channels. The linear predictive coefficient and the periodic value are used as data to measure the type of exercise and the amount of exercise. In the proposed method, we measured four types of movements such as walking, stair climbing, slow hill climbing, and fast hill descending. In order to verify the usefulness of the parameters, the recognition results are presented using the linear predictive coefficient and the periodic value for each motion as the neural network input.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.11
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• pp.2105-2110
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• 2008

Embedding the compact wearable units to monitor the health status of a person has been analysed as a convenient solution for the home health care. This paper presents a method to detect fall from the other activities of daily living and also to classify those activities. This kind of ambulatory monitoring of the elderly and people with limited mobility can not only provide their general health status but also alarms whenever an emergency such as fall or gait has been occurred and a help is needed. A timely assistance in such a situation can reduce the loss of life. This work shows a detailed analysis of the data received from a chest worn sensor unit embedding a 3-axis accelerometer and depicts which features are important for the classification of human activities. How to arrange and reduce the features to a new feature set so that it can be classified using a simple classifier and also improving the classification resolution. Principal component analysis (PCA) has been used for modifying the feature set and afterwards for reducing the size of the same. Finally a Neural network classifier has been used to analyse the classification accuracies. The accuracy for detection of fall events was found to be 86%. The overall accuracy for the classification of Activities or daily living (ADL) and fall was around 94%.

• International Journal of Highway Engineering
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• v.14 no.3
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• pp.141-149
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• 2012

This paper attempts to evaluate driving stability by the vibration of human body. The purpose of this research is to establish an evaluation methodology for controling the quality of road surface. The study was conducted to investigate the relationship between road surface profiles (IRI, International Roughness Index) and the fatigue caused by the vibration of human body. Furthermore, 3-axis acceleration in driving vehicles was examined based on sampling sections under various road conditions. The acceleration value of frequency bands were analyzed by the characteristics of road surface, and realized the range of human influence by conditions and type of road surface with ISO-2631 standards. In general, more human fatigue by vehicle vibration was appeared in concrete pavements with high IRIs based on the analysis from given test data. Whereas, The SMA asphalt pavement and the diamond grinded concrete pavement reduce the human fatigue.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1649-1654
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• 2021

In this paper, we introduce a regularization of long short-term memory (LSTM) based fall detection system using TensorFlow that can detect falls that can occur in the elderly. Fall detection uses data from a 3-axis acceleration sensor attached to the body of an elderly person and learns about a total of 7 behavior patterns, each of which is a pattern that occurs in daily life, and the remaining 3 are patterns for falls. During training, a normalization process is performed to effectively reduce the loss function, and the normalization performs a maximum-minimum normalization for data and a L2 regularization for the loss function. The optimal regularization conditions of LSTM using several falling parameters obtained from the 3-axis accelerometer is explained. When normalization and regularization rate λ for sum vector magnitude (SVM) are 127 and 0.00015, respectively, the best sensitivity, specificity, and accuracy are 98.4, 94.8, and 96.9%, respectively.

• Journal of Korea Multimedia Society
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• v.16 no.2
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• pp.226-233
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• 2013

Self-diagnosis, regular examination, completion examination and precise safety examination on an elevator offer primary sources for evaluating performance and stability of the elevator. as critical examination for operating the elevator. The items on vibration of an elevator in the self-diagnosis and safety examination are not especially specified but vibration itself is considered as essential element to provide diverse analysis data. There is the equipment "EVA-625" for measuring vibration of an elevator. It is operated by reading data via computer and analyzing data by skilled engineer. This study aims to design and realize software to analyze data collected through the LabVIEW, a graphic program language and hardware for receiving data measuring vibration of an elevator by using 3-Axis acceleration sensor.