• Journal of Information Processing Systems
• /
• v.15 no.3
• /
• pp.478-491
• /
• 2019

This work develops a monitoring system for the population with health concerns. A belt integrated with an on-body circuit and sensors measures a wearer's selected vital signals. The electrocardiogram sensors monitor heart conditions and an accelerometer assesses the level of physical activity. Sensed signals are transmitted to the circuit module through digital yarns and are forwarded to a mobile device via Bluetooth. An interactive application, installed on the mobile device, is used to process the received signals and provide users with real-time feedback about their status. Persuasive functions are designed and implemented in the interactive application to encourage users' physical activity. Two signal processing algorithms are developed to analyze the data regarding heart and activity. A user study is conducted to evaluate the performance and usability of the developed system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2005.11a
• /
• pp.883-886
• /
• 2005

This paper proposed a wireless measurement system (WMS) for an effective condition monitoring using wireless communication. WMS consists of two parts: transmitter(TM) acquired a dynamic signal from physical system using ICP type accelerometer sensor. An acquired signal modulated through the low/high pass filter and amplifier in DAQ board, which converted to digital signal. Embedded board(E-board) transferred digital signals to base station(BS) through the socket IEEE.802.11.b. BS is adopted IOCP server structure. Because it can acquired signal well during transferred digital signal. Signal processing used LabVIEW Library, BS(server) designed to realize multi-thread using visual C++.NET for 1 many meaning data processing

• Proceedings of the KSR Conference
• /
• 1999.05a
• /
• pp.143-150
• /
• 1999

The vibration signals of driving parts of electric train are distorted its signal patterns due to the impact components, which occurs when wheel passes rail joints. An elimination method of the impact components is investigated using adaptive signal processing technique in this study. The result shows that adaptive interference canceling method seems to be more effective than line enhancement technique. The application of adaptive interference canceling method to the signal measured at bogie shows that the extractions of the signals of driving parts of traction motor, reduction gear, and axle bearing are successful. Therefore, only the signals of bogie, which is the place to attach an accelerometer easily, is sufficient for the fault diagnosis and the safety evaluation of electric train. Also, adaptive interference canceling method can be applicable to evaluate the performance of vibration isolation between bogie and car body and to investigate the characteristics of indoor sound.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.6
• /
• pp.1150-1158
• /
• 2010

In this paper, a new reliable portable activity monitoring device implemented with the buddhist-style bowing activity and walking step detection algorithm, is presented. In order to monitor the bowing and walking activities, miniaturized 3-axis accelerometer sensor with the sensitivity of 800 mV/g was used. After initial signal conditioning, vector magnitude of accelerometer signals was calculated. Syntactic peak detection method was used in order to feature points. All signal processing algorithms were implemented in ultra-low power microcontroller MSP430 with double precision floating point arithmetic. For evaluation, 19 young man($24.22\pm5.22$ yrs) and woman($22.28\pm2.72$ yrs) were involved. The accuracy of the proposed algorithms were 98.91 %($\pm0.011$) for walking step detection and 98.25 %($\pm0.023$) for buddhist-style bowing activity. Comparing to the commercialized pedometer accuracy, 87.1 %($\pm0.058$), the proposed walking step detection algorithms show more reliable accuracy.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.18 no.8
• /
• pp.872-878
• /
• 2008

Many industrial operations require continuous or nearly-continuous operation of machines, interruption of which can result in significant cost loss. The condition monitoring of these machines has received considerable attentions in recent years. Rapid developments in semiconductor, computing, and communication with a remote site have led to a new generation of sensor called "smart" sensors which are capable of wireless communication with a remote site. The purpose of this research is to develop a new type of smart sensor for on-line condition monitoring. This system is addressed to detect conditions that may lead to equipment failure when it is running. Moreover it will reduce condition monitoring expense using low cost MEMS accelerometer. This system is capable for signal preprocessing task and analog to digital converter which is controlled by CPU. This sensor communicates with a remote site PC using TCP/IP protocols. The developed sensor executes performance tests for data acquisition accuracy estimations.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.36 no.10
• /
• pp.1003-1010
• /
• 2008

In this paper, we propose the new method to decrease the navigation error by measurement time synchronization error in RLG Trapping signal processing. There are two methods to eliminate the dither motion in RLG. One is the stripping signal processing method. Another is the trapping signal processing method. This two methods have various error sources in measurement output. We perform the error modelling and analysis for the measurement time synchronization error between angular rate from RLG and acceleration from accelerometer in the trapping signal processing method. And we verify the navigation performance through simulation and experiment. Results of simulation and experiment show that the proposed method is very effective in decreasing the navigation error.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.26 no.6
• /
• pp.373-379
• /
• 2006

Vibration-based structural health monitoring is one of non-destructive evaluation (NDE) techniques for civil infrastructures. This paper presents a novel fiber optic accelerometer system to monitor civil engineering structures and a successful application of the novel sensor system for measuring ambient vibration of a real building structure. This sensor system integrates the Moire fringe phenomenon with fiber optics to achieve accurate and reliable measurements. The sensor system is immune to electromagnetic (EM) interference making it suitable for difficult applications in such environments involving strong EM fields, electrical spark-induced explosion risks, and cabling problems, prohibiting the use of conventional electromagnetic accelerometers. A prototype sensor system has been developed, together with a signal processing software. The experimental studies demonstrated the high-performance of the fiber optic sensor system. Especially, the sensor was successfully used for monitoring a real building on UCI (University of California Irvine, USA).

• IEIE Transactions on Smart Processing and Computing
• /
• v.6 no.1
• /
• pp.21-26
• /
• 2017

In this paper, we suggest an automated sleep scoring method using machine learning algorithms on accelerometer data from a wristband device. For an experiment, 36 subjects slept for about eight hours while polysomnography (PSG) data and accelerometer data were simultaneously recorded. After the experiments, the recorded signals from the subjects were preprocessed, and significant features for sleep stages were extracted. The extracted features were classified into each sleep stage using five machine learning algorithms. For validation of our approach, the obtained results were compared with PSG scoring results evaluated by sleep clinicians. Both accuracy and specificity yielded over 90 percent, and sensitivity was between 50 and 80 percent. In order to investigate the relevance between features and PSG scoring results, information gains were calculated. As a result, the features that had the lowest and highest information gain were skewness and band energy, respectively. In conclusion, the sleep stages were classified using the top 10 significant features with high information gain.

• Journal of the Institute of Convergence Signal Processing
• /
• v.19 no.4
• /
• pp.186-191
• /
• 2018

As influence of the 4th industry is growing with development of information society more electronic devices and sensor are used in the field. As this is the case, importance of signal processing during data transfer is rising Furthermore, the need for technology to remove noise caused by various reasons and to stabilize sensor output is growing as well. This research suggests digital filter algorithm that efficiently remove noise by stabilizing output of accelerating sensor. The standard value of this algorithm is calculated by applying Gaussian coefficient. To maintain its feature, final output is obtained by subtracting weight depending on variance from standard value For its evaluation, it is compared with other protocols and its function is checked through output features.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.9 no.4
• /
• pp.71-80
• /
• 2006

Strapdown Inertial navigation systems consist of an inertial sensor assembly(ISA), electronic modules to process sensor data, and a navigation computer to calculate attitude, velocity and position. In the ISA, most gryoscopes such as RLGs and FOGs, have digital output, but typical accelerometers use current as an analog output. For a high precision inertial navigation system, sufficient stability and resolution of the accelerometer board converting the analog accelerometer output into digital data needs to be guaranteed. To achieve this precision, the asymmetric error and A/D reset scale error of the accelerometer board must be properly compensated. If the relation between the acceleration error and the errors of boards are exactly known, the compensation and estimation techniques for the errors may be well developed. However, the A/D Reset scale error consists of a pulse-train type term with a period inversely proportional to an input acceleration additional to a proportional term, which makes it difficult to estimate. In this paper, the effects on the acceleration output for auto-pilot situations and the effects of A/D reset scale errors during horizontal alignment are qualitatively analyzed. The result can be applied to the development of the real-time compensation technique for A/D reset scale error and the derivation of the design parameters for accelerometer board.