• Title/Summary/Keyword: a accelerometer

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Detection of Repetition Motion Using Neural network (신경망을 이용한 반복운동 검출)

  • Yoo, Byeong-hyeon;Heo, Gyeong-yong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.9
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    • pp.1725-1730
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    • 2017
  • The acceleration sensor and the gyroscopic sensor are used as representative sensors to detect repetitive motion and have been used to analyze various sporting components. However, both sensors have problems with noise sensitivity and accumulation of errors. There have been attempts to use two sensors together to overcome hardware problems. The complementary filter has shown successful results in mitigating the problems of both sensors by minimizing the disadvantages of accelerometer and gyroscope sensors and maximizing their advantages. In this paper, we proposed a modified method using neural network to reduce variable. The neural network is an algorithm that can precisely measure even in unexpected environments or situations by pre-learning the number of various cases. The proposed method applies a Neural Network by dividing the repetitive motion into three sections, the first, the middle and the end. As a result, the recognition rate is 96.35%, 98.77%, 96.92% and the accuracy is 97.18%.

Activity Recognition of Workers and Passengers onboard Ships Using Multimodal Sensors in a Smartphone (선박 탑승자를 위한 다중 센서 기반의 스마트폰을 이용한 활동 인식 시스템)

  • Piyare, Rajeev Kumar;Lee, Seong Ro
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39C no.9
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    • pp.811-819
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    • 2014
  • Activity recognition is a key component in identifying the context of a user for providing services based on the application such as medical, entertainment and tactical scenarios. Instead of applying numerous sensor devices, as observed in many previous investigations, we are proposing the use of smartphone with its built-in multimodal sensors as an unobtrusive sensor device for recognition of six physical daily activities. As an improvement to previous works, accelerometer, gyroscope and magnetometer data are fused to recognize activities more reliably. The evaluation indicates that the IBK classifier using window size of 2s with 50% overlapping yields the highest accuracy (i.e., up to 99.33%). To achieve this peak accuracy, simple time-domain and frequency-domain features were extracted from raw sensor data of the smartphone.

Robust Walking Algorithm of Biped Robot on Uneven Terrain (비평탄 지형에서 이족로봇의 강인한 보행 알고리즘)

  • Lee, Bo-Hoon;Park, Jong-Han;Lee, Chang-Seok;Kim, Yong-Tae
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.48 no.4
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    • pp.33-39
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    • 2011
  • Biped robot with high DOF has instability in mechanism. Therefore, it is important to guarantee walking stability of biped robot. Biped robot can stably walk on the flat ground using static walking patterns. However, walking stability of robot becomes increasingly worse on the uneven terrain. In the paper, we propose a robust walking algorithm of biped robot with motion stabilization to solve the problem The proposed algorithm was designed to stabilize walking motions based on the inclination of robot body using a gyro sensor and a accelerometer equipped in the center of the upper body. If unstable motions are recognized, angles of each joints are modified to increase stability by using compensation of angles of lower legs. The experimental results show that biped robot performs stable walking on the uneven terrain.

Implementation of Telematics System Using Driving Pattern Detection Algorithm (운전패턴 검출 알고리즘을 적응한 텔레매틱스 단말기 구현)

  • Kin, Gi-Seok;Jung, Hee-Seok;Yun, Kee-Bang;Jeong, Kyung-Hoon;Kim, Ki-Doo
    • 전자공학회논문지 IE
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    • v.45 no.4
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    • pp.33-41
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    • 2008
  • Telematics system includes the "vehicle remote diagnosis technology", "driving pattern analysis technology" which are commercially attractive in the real life. To implement those technologies, we need vehicle signal interface, vehicle diagnosis interface, accelerometer/yaw-rate sensor interface, GPS data processing, driving pattern analysis, and CDMA data processing technique. Based on these technologies, we analyze the error existence by diagnosing the EMS(Engine Management System), TMS(Transmission Management System), ABS/TCS, A/BAG in real time. And we are checking about a driving pattern and management of the vehicle, which are sent to the information center through the wireless communication. These database results will make the efficient vehicle and driver management possible. We show the effectiveness of our results by field driving test after completing the H/W & S/W design and implementation for vehicle remote diagnosis and driving pattern analysis.

Cone penetrometer incorporated with dynamic cone penetration method for investigation of track substructures

  • Hong, Won-Taek;Byun, Yong-Hoon;Kim, Sang Yeob;Lee, Jong-Sub
    • Smart Structures and Systems
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    • v.18 no.2
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    • pp.197-216
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    • 2016
  • The increased speed of a train causes increased loads that act on the track substructures. To ensure the safety of the track substructures, proper maintenance and repair are necessary based on an accurate characterization of strength and stiffness. The objective of this study is to develop and apply a cone penetrometer incorporated with the dynamic cone penetration method (CPD) for investigating track substructures. The CPD consists of an outer rod for dynamic penetration in the ballast layer and an inner rod with load cells for static penetration in the subgrade. Additionally, an energy-monitoring module composed of strain gauges and an accelerometer is connected to the head of the outer rod to measure the dynamic responses during the dynamic penetration. Moreover, eight strain gauges are installed in the load cells for static penetration to measure the cone tip resistance and the friction resistance during static penetration. To investigate the applicability of the developed CPD, laboratory and field tests are performed. The results of the CPD tests, i.e., profiles of the corrected dynamic cone penetration index (CDI), profiles of the cone tip and friction resistances, and the friction ratio are obtained at high resolution. Moreover, the maximum shear modulus of the subgrade is estimated using the relationships between the static penetration resistances and the maximum shear modulus obtained from the laboratory tests. This study suggests that the CPD test may be a useful method for the characterization of track substructures.

Development of Seismic Monitoring System for Natural Gas Governor Station and It's Field Application to Minimize Earthquake Damage (지진 피해 최소화를 위한 지진 감지 시스템 개발 및 현장적용 연구)

  • Yoo H.R.;Park S.S.;Park D.J.;Koo S.J.;Cho S.H.;Rho Y.W.
    • Journal of the Korean Institute of Gas
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    • v.4 no.3 s.11
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    • pp.19-25
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    • 2000
  • In order to prevent secondary disaster such as gas explosion which comes after a devastating magnitude earthquake, the seismic monitoring and transmission system for natural gas governor station was developed. To measure ground motions precisely and operate the seismic monitoring system efficiently, the position and method of accelerometer installation were recommended by the analysis of ground noise patterns of governor station. For making a decision on prompt shut-off of gas supplies in the event of a great earthquake, the real-time calculation algorithm of PGA(Peak Ground Acceleration) and SI(Spectrum Intensity) were developed and it has been implemented in the seismic monitoring and transmission system.

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Mobile Finger Signature Verification Robust to Skilled Forgery (모바일환경에서 위조서명에 강건한 딥러닝 기반의 핑거서명검증 연구)

  • Nam, Seng-soo;Seo, Chang-ho;Choi, Dae-seon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.26 no.5
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    • pp.1161-1170
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    • 2016
  • In this paper, we provide an authentication technology for verifying dynamic signature made by finger on smart phone. In the proposed method, we are using the Auto-Encoder-based 1 class model in order to effectively distinguish skilled forgery signature. In addition to the basic dynamic signature characteristic information such as appearance and velocity of a signature, we use accelerometer value supported by most of the smartphone. Signed data is re-sampled to give the same length and is normalized to a constant size. We built a test set for evaluation and conducted experiment in three ways. As results of the experiment, the proposed acceleration sensor value and 1 class model shows 6.9% less EER than previous method.

Classification of walking patterns using acceleration signal (가속도 신호를 이용한 걸음걸이 패턴 분류)

  • Jo, Heung-Kuk;Ye, Soo-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.8
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    • pp.1901-1906
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    • 2010
  • This classification of walking patterns is important and many kinds of applications. Therefore, we attempted to classify walking on level ground from slow walking to fast walking using a waist acceleration signal. A tri-axial accelerometer was fixed to the subject's waist and the three acceleration signals were recorded by bluetooth module at a sampling rate of 100 Hz eleven healthy. The data were analyzed using discrete wavelet transform. Walking patterns were classified using two parameters; One was the ratio between the power of wavelet coefficients which were corresponded to locomotion and total power in the anteroposterior direction (RPA). The other was the ratio between root mean square of wavelet coefficients at the anteroposterior direction and that at the vertical direction(RAV). Slow walking could be distinguished by the smallest value in RPA from other walking pattern. Fast walking could be discriminated from level walking using RAV. It was possible to classify the walking pattern using acceleration signal in healthy people.

Detection of Fall Direction using a Velocity Vector in the Android Smartphone Environment (안드로이드 스마트폰 환경에서 속도벡터를 이용한 넘어짐 방향 판단 기법)

  • Lee, Woosik;Song, Teuk Seob;Youn, Jong-Hoon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.2
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    • pp.336-342
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    • 2015
  • Fall-related injuries are the most common cause of accidental death for the elderly and the most frequent work-related injuries in construction sites. Due to the growing popularity of smartphones, there has been a number of research work related to the use of sensors embedded in the smartphone for fall detection. Falls can be detected easily by measuring the magnitude and direction of acceleration vectors. In general, the direction of the acceleration vector does not show the object movement, but the velocity vector directly indicates the tangential direction in which the object is moving. In this paper, we proposed a new method for computing the fall direction based on the characteristics of the velocity vector extracted from the accelerometer.

Evaluation and Selection of MEMS-Based Inertial Sensor to Implement Inertial Measurement Unit for a Small-Sized Vessel (소형 선박용 관성측정장치 개발을 위한 MEMS 기반 관성 센서의 평가와 선정)

  • Yim, Jeong-Bin
    • Journal of Navigation and Port Research
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    • v.35 no.10
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    • pp.785-791
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    • 2011
  • This paper describes the evaluation and selection of MEMS(Micro-Elect Mechanical System) based inertial sensor to fit to implement the Inertial Measurement Unit(IMU) for a small-sized vessel at sea. At first, the error model and the noise model of the inertial sensors are defined with Euler's equations and then, the inertial sensor evaluation is carried out with Allan Variance techniques and Monte Carlo simulation. As evaluation results for the five sensors, ADIS16405, SAR10Z, SAR100Grade100, LIS344ALH and ADXL103, the combination of gyroscope and accelerometer of ADIS16405 is shown minimum error having around 160 m/s standard deviation of velocity error and around 35 km standard deviation of position error after 600 seconds. Thus, we select the ADIS16405 inertial sensor as a MEMS-based inertial sensor to implement IMU and, the error reducing method is also considered with the search for reference papers.