• Journal of Sensor Science and Technology
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• v.26 no.1
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• pp.7-14
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• 2017

A threshold-based fall recognition algorithm using a tri-axial accelerometer and a bi-axial gyroscope mounted on the skin above the upper sternum was proposed to recognize fall-like activities of daily living (ADL) events. The output signals from the tri-axial accelerometer and bi-axial gyroscope were obtained during eight falls and eleven ADL action sequences. The thresholds of signal vector magnitude (SVM_Acc), angular velocity (${\omega}_{res}$), and angular variation (${\theta}_{res}$) were calculated using MATLAB. When the measured values of SVM_Acc, ${\omega}_{res}$, and ${\theta}_{res}$ were compared to the threshold values (TH1, TH2, and TH3), fall-like ADL events could be distinguished from a fall. When SVM_Acc was larger than 2.5 g (TH1), ${\omega}_{res}$ was larger than 1.75 rad/s (TH2), and ${\theta}_{res}$ was larger than 0.385 rad (TH3), eight falls and eleven ADL action sequences were recognized as falls. When at least one of these three conditions was not satisfied, the action sequences were recognized as ADL. Fall-like ADL events such as jogging and jumping up (or down) have posed a problem in distinguishing ADL events from an actual fall. When the measured values of SVM_Acc, ${\omega}_{res}$, and ${\theta}_{res}$ were applied to the sequential processing algorithm proposed in this study, the sensitivity was determined to be 100% for the eight fall action sequences and the specificity was determined to be 100% for the eleven ADL action sequences.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.629-642
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• 2013

Recently, with the advent of smart phones, it brought many changes in lives of modern people. Especially, application utilizing the sensor information of smart phone, which provides the service adapted by user situations, has been emerged. Sensor data of smart phone can be used for recognizing the user situation, Because it is closely related to the behavior and habits of the user. currently, GPS sensor one of mobile sensor has been utilized a lot to recognize basic user activity. But, depending on the user situation, activity recognition system cannot receive GPS signal, and also not collect received data. So utilization is reduced. In this paper, for solving this problem, we suggest a method of user activity recognition that focused on the accelerometer sensor data using smart phone. Accelerometer sensor is stable to collect the data and it's sensitive to user behavior. Finally this paper suggests a noble approach to use state transition diagrams which represent the natural flow of user activity changes for enhancing the accuracy of user activity recognition.

• Smart Structures and Systems
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• v.22 no.1
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• pp.95-103
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• 2018

Active vibration control via inertial mass actuators has been shown as an effective tool to significantly reduce human-induced vertical vibrations, allowing structures to satisfy vibration serviceability limits. However, a lot of practical obstacles have to be solved before experimental implementations. This has motivated simple control techniques, such as direct velocity feedback control (DVFC), which is implemented in practice by integrating the signal of an accelerometer with a band-pass filter working as a lossy integrator. This work provides practical guidelines for the tuning of DVFC considering the damping performance, inertial mass actuator limitations, such as stroke and force saturation, as well as the stability margins of the closed-loop system. Experimental results on a full scale steel-concrete composite structure (behaves similar to a footbridge) with adjustable span are reported to illustrate the main conclusions of this work.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.3
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• pp.245-250
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• 2015

Portable devices, such as smart phones and personal digital assistants (PDAs) play an important role in our everyday life. In this paper, we propose a step count algorithm based on SVM(signal vector magnitude) and a adaptive threshold processing to monitor the physical activity. The algorithm measures a user's step counts using the smart phone's inbuilt accelerometer and g sensor. Experiment results showed the proposed algorithm has good performance in accuracy and adaptability than the app on your smart phone.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.581-583
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• 2011

최근에 급격히 증가한 스마트폰의 사용자들이 이동중에도 안정적인 무선 네트워크를 이용하기 위해서는 핸드오프는 반드시 필요하다. 핸드오프를 위하여 기존에 연결되어 있는 AP(Access Point)와의 연결을 끊고 주변의 AP 를 스캐닝한 후 새로운 AP 로 재연결을 하는 과정을 거치게 된다. 이러한 과정 중에 본 논문에서는 스캐닝 단계에서 발생하는 문제점을 분석하고 이에 대한 개선방안으로 AP 의 신호세기와 스마트폰의 센서를 이용하여 사용자의 이동성을 고려하는 스캐닝 방식을 제안한다.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.368-372
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• 2009

The method to get the feature have been proposed to recognize the user activity by setting specific action for making the user independent result in previous research. However, it was only applied in specific environment and it was difficult to implement because it regarded only some specific feature as the recognized object. To improve this problem we detected the normality/abnormality of the activity based on the repetition and the continuity of the past activity pattern. We applied the unsupervised learning method, not supervised, and clustered the data which was collected within a certain period of time and we regarded it as the basis of the evaluation of the repetition. We demonstrated to be able to detect the abnormal activity based on wether the data was generated repeatedly.

• Journal of Korea Multimedia Society
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• v.23 no.11
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• pp.1372-1382
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• 2020

This paper proposes a core technology for a micro river monitoring terminal device suitable for flood monitoring in small rivers and valleys. Our proposed device is basically equipped with a 77GHz radar, gyro and accelerometer sensors. To measure the flow velocity and water level, we proposed a signal processing technique that extracts pure water energy components from the observed Doppler velocity and reflection intensity from the radar. And to determine the stability of the river structure equipped with our device, we constantly monitor the displacement of the measured values of the gyro and accelerometer sensors. Experimental result verified that our method detects pure water energy in various river environments and distinguishes between flow velocity and water level well. And we verified that vibration and position change of structures can be determined through a gyro sensor. In future research, we will work to build a secure digital twin river network by lowering the cost of supplying RF-WAV devices. Also we expect our device to contribute to securing a preventive golden time in rivers.

• Wind and Structures
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• v.21 no.6
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• pp.677-691
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• 2015

In this study, the geometrical setup of a turbine blade is tracked. A research-scale rotating turbine blade system is setup with a single 3-axes accelerometer mounted on one of the blades. The turbine system is rotated by a controlled motor. The tilt and rolling angles of the rotating blade under operating conditions are determined from the response measurement of the single accelerometer. Data acquisition is achieved using a prototype wireless sensing system. First, the Rodrigues' rotation formula and an optimization algorithm are used to track the blade rolling angle and pitching angles of the turbine blade system. In addition, the blade flapwise natural frequency is identified by removing the rotation-related response induced by gravity and centrifuge force. To verify the result of calculations, a covariance-driven stochastic subspace identification method (SSI-COV) is applied to the vibration measurements of the blades to determine the system natural frequencies. It is thus proven that by using a single sensor and through a series of coordinate transformations and the Rodrigues' rotation formula, the geometrical setup of the blade can be tracked and the blade flapwise vibration frequency can be determined successfully.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.961-968
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• 1999

In this paper we handle a system that transform sensor data to sensor information. Sensor informations from redundant accelerometers are manipulated to represent the configuration of objects carrying sensors. Basic sensor unit of the proposed systme is composed of 3 accelerometers that are aligned along x-y-z coordination axes of motion. To refine the sensor information, at first the sensor data are fused by geometrical optimization to reduce the variance of sensor information. To overcome the error caused from inexact alignment of each sensor to the coordination system, we propose a calibration technique that identifies the transformation between the coordinate axes and real sensor axes. The calibration technique make the sensor information approach real value. Also, we propose a technique that decomposes the accelerometer data into motion acceleration component and gravity acceleration component so that we can get more exact configuration of objects than in the case of raw sensor data. A set of experimental results are given to show the usefulness of the proposed method as well as the experiments in which the proposed techniques are applied to human body motion capture.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.2
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• pp.185-198
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• 2016

In this work, experimental errors from an impact hammer test were investigated to develop a statistic-based technique for updating a finite element model. Digital signal processing was analyzed by using theoretical models and experiments when errors occurred during the experimental procedure. First, the duration time and peak level of the excitation signal, the stiffness and position of elastic springs connecting the specimen as well as the support, position and mass of the accelerometer were considered as error factors during the experiment. Then the picket fence effect, leakage, and exponential window function were considered as candidate error factors during the digital signal processing. Finally, methods to reduce errors are suggested.