• 센서학회지
• /
• 제18권6호
• /
• pp.449-455
• /
• 2009

In this paper, we developed a digital gait analyzer using the triaxial accelerometer(TA). An approach for normal gait detection employing decay slope peak detection(DSPD) algorithm was presented. The TA was attached to the center of the waist of a subject. The subject walked a bare floor at 60, 92 and 120 steps/minute. We analyzed vertical axis acceleration signal for gait detection. At 60, 92, 120 steps/minute walking, detection accuracy of gait events were over 99 % accuracy.

• 전자공학회논문지CI
• /
• 제48권2호
• /
• pp.127-137
• /
• 2011

본 논문에서는 3축 가속도 센서를 이용하여 사람이 보행 시 발생하는 센서 데이터를 획득하여 실시간 걸음 수 검출과 활동량으로 변환 가능한 웨어러블 디바이스를 개발하였다. 피험자 59명을 대상으로 트레드밀에서 호흡가스대사분석기(K4B2), Actical 그리고 본 연구에서 개발된 디바이스를 착용 후 36분 동안 테스트 프로토콜에 따라 느리게 걷기, 걷기, 빠르게 걷기, 천천히 뛰기, 뛰기, 빠르게 뛰기 등의 다양한 걸음 속력에서 테스트를 진행하였다. 3축 가속도 센서의 X, Y, Z축 출력 값을 하나의 대표 값으로 처리하는 신호벡터크기(Signal Vector Magnitude :SVM)를 사용하였다. 또한 정확한 걸음 수를 검출하기 위해 휴리스틱 알고리즘(Heuristic Algorithm :HA)을 제안하고 적응적인 임계값 알고리즘(Adaptive Threshold Algorithm :ATA), 적응적인 잠금 구간 알고리즘(Adaptive Locking Period Algorithm :ALPA)을 제안한다. 그리고 인체 활동량 측정을 위하여 가속도 센서 출력 데이터와 피험자 정보를 이용하여 에너지소비량(Energy Expenditure :EE)을 추정하는 회귀식을 도출하였다. 실험결과 제안하는 알고리즘의 걸음 수 인식률은 97.34%를 보였으며 활동량 변환 알고리즘도 Actical의 성능보다 1.61% 향상 되었다.

• 인터넷정보학회논문지
• /
• 제12권3호
• /
• pp.17-26
• /
• 2011

본 논문에서는 3축 가속도 센서를 이용하여 사람이 보행 시 발생하는 센서 데이터를 획득하여 실시간 걸음 수 검출이 가능한 웨어러블 디바이스를 개발하였다. 피험자 59명을 대상으로 트레드밀에서 Actical 과 본 연구에서 개발된 디바이스를 착용 후 36분 동안 테스트 프로토콜에 따라 느리게 걷기, 걷기, 빠르게 걷기, 천천히 뛰기, 뛰기, 빠르게 뛰기 등의 다양한 걸음 속력에서 테스트를 진행하였다. 3축 가속도 센서의 X, Y, Z축 출력 값을 하나의 대표 값으로 처리하는 신호벡터크기(Signal Vector Magnitude : SVM)를 사용하였다. 또한 정확한 걸음 수를 검출하기 위해 휴리스틱 알고리즘(Heuristic Algorithm : HA)을 제안하고 적응적인 임계값 알고리즘(Adaptive Threshold Algorithm : ATA), 적응적인 잠금 구간 알고리즘(Adaptive Locking Period Algorithm : ALPA)을 제안한다. 실험결과 제안하는 알고리즘의 걸음 수 인식률은 97.34%로 Actical의 인식률(91.74%)보다 5.6%향상 되었다.

• 제어로봇시스템학회논문지
• /
• 제20권2호
• /
• pp.149-156
• /
• 2014

A magnetic compass module must be calibrated accurately before use. Moreover, the calibration process must be performed taking into account any magnetic dip if the magnetic compass module has tilt angles. For this, a calibration method for a magnetic compass module is explained. Tilt error of the magnetic compass module is compensated using a biaxial accelerometer generally. The accelerometer error causes a tilt angle calculation error that gives rise to an azimuth calculation error. For error property analysis, error equations are derived and simulations are performed. In the simulation results, the accuracy of derived error equations is verified. If a biaxial magnetic compass module is used instead of a triaxial one, the magnetic dip and z-axis magnetic compass data must be estimated for tilt compensation. Lastly, estimation equations for the magnetic dip and z-axis magnetic compass data are derived, and the performance of the equations is verified based on a simulation.

• 한국운동역학회지
• /
• 제18권4호
• /
• pp.109-114
• /
• 2008

본 연구의 목적은 신체활동 시에 간단하고 실용적인 방법으로 에너지 소비를 예측하는데 있다. 신체활동은 허리에 부착된 3축 가속도계 센서를 사용하여 가속도의 함으로써 정량화하였다. 에너지 소비량과 가속도계 데이터의 관계를 찾기 위하여 11명(남성 6명, 여성 5명)의 피험자를 상대로 1.5, 3.0, 4.5, 6.0, 6.5, 7.0, 8.5km/hr의 속도로 트레드밀에서 걷거나 달리는 동작을 시행하였다. 각 피험자는 트레드밀 속도가 6.0km/hr 일 경우에는 걷는 동작을 6.5km/hr 이상일 경우께는 달리는 동작을 수행하였다. 실제 에너지 소비량은 가스분석기를 통하여 측정되었다. 예측 식은 피험자의 성, BMI(Body Mass Index), 가속도 데이터로 이루어졌으며 걷기, 달리기로 총 2개의 다중회귀식으로 구현되었다. 실제 측정된 에너지 소비량과 예측된 에너지 소비량 간의 상관계수와 결정계수는 걷기와 달리기에서 각각 R=0.956, R2=0.876와 R=0.881, R2=0.776를 나타내었다. 추후의 연구에서는 보다 많은 피험자의 데이터를 이용하여 보다 신뢰성 있는 에너지 소비량 예측의 회귀식을 구현하고자 한다.

• Smart Structures and Systems
• /
• 제21권4호
• /
• pp.407-420
• /
• 2018

In structural health monitoring, it is meaningful to comprehensively utilize accelerometers and strain gauges to obtain the modal information of a structure. In this paper, a modal estimation theory is proposed, in which the displacement modes of the locations without accelerometers can be estimated by the strain modes of selected strain gauge measurements. A two-stage sensor placement method, in which strain gauges are placed together with triaxial accelerometers to obtain more structural displacement mode information, is proposed. In stage one, the initial accelerometer locations are determined through the combined use of the modal assurance criterion and the redundancy information. Due to various practical factors, however, accelerometers cannot be placed at some of the initial accelerometer locations; the displacement mode information of these locations are still in need and the locations without accelerometers are defined as estimated locations. In stage two, the displacement modes of the estimated locations are estimated based on the strain modes of the strain gauge locations, and the quality of the estimation is seen as a criterion to guide the selection of the strain gauge locations. Instead of simply placing a strain gauge at the midpoint of each beam element, the influence of different candidate strain gauge positions on the estimation of displacement modes is also studied. Finally, the modal assurance criterion is utilized to evaluate the performance of the obtained multitype sensor placement. A bridge benchmark structure is used for a numerical investigation to demonstrate the effectiveness of the proposed multitype sensor placement method.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.28-28
• /
• 2000

Low-cost solid-state inertial sensors of three rate Gyroscopes and a triaxial Accelerometer are evaluated in static and dynamic environments. As a interim result, error models of each inertial sensors are generated. Model parameters with respect to temperature are acquired in static environment. These error models are included in an Extended Kalman Filter(EKF) to compensate bias error due to temperature variation. Experimental results in dynamic environment are included to show the validity of the each error model and the performance improvement of a compensated low cost inertial sensors for a navigational application

• 전기학회논문지
• /
• 제61권6호
• /
• pp.851-858
• /
• 2012

In this paper, we design a seismic data acquisition system(SDAS) and implement it. This system is essential for development of a noble local earthquake disaster preventing system in population center. In the system, we choose a proper MEMS-type triaxial accelerometer as a sensor, and FPGA and ARM processor are used for implementing the system. In the SDAS, each module is realized by Verilog HDL and C Language. We carry out the ModelSim simulation to verify the performances of important modules. The simulation results show that the FPGA-based data acquisition module can guarantee an accurate time-synchronization for the measured data from each axis sensor. Moreover, the FPGA-ARM based embedded technology in system hardware design can reduce the system cost by the integration of data logger, communication sever, and facility control system. To evaluate the data acquisition performance of the SDAS, we perform experiments for real seismic signals with the exciter. Performances comparison between the acquired data of the SDAS and the reference sensor shows that the data acquisition performance of the SDAS is valid.

• ETRI Journal
• /
• 제45권6호
• /
• pp.1079-1089
• /
• 2023

Stroke is one of the leading causes of long-term disability worldwide, placing huge burdens on individuals and society. Further, automatic human activity recognition is a challenging task that is vital to the future of healthcare and physical therapy. Using a baseline long short-term memory recurrent neural network, this study provides a novel dataset of stretching, upward stretching, flinging motions, hand-to-mouth movements, swiping gestures, and pouring motions for improved model training and testing of stroke-affected patients. A MATLAB application is used to output textual and audible prediction results. A wearable sensor with a triaxial accelerometer is used to collect preprocessed real-time data. The model is trained with features extracted from the actual patient to recognize new actions, and the recognition accuracy provided by multiple datasets is compared based on the same baseline model. When training and testing using the new dataset, the baseline model shows recognition accuracy that is 11% higher than the Activity Daily Living dataset, 22% higher than the Activity Recognition Single Chest-Mounted Accelerometer dataset, and 10% higher than another real-world dataset.

• 한국운동역학회지
• /
• 제30권2호
• /
• pp.145-154
• /
• 2020

Objective: The purpose of this study was to determine the relationship between impact and shear peak force, and tibia-accelerometer variables during running. Method: Twenty-five male heel strike runners (mean age: 23.5±3.6 yrs, mean height: 176.3±3.3 m/s, mean mass: 71.8±9.7 kg) were recruited in this study. The peak impact and anteroposterior shear forces during treadmill running (Bertec, USA) were collected, and impact shock variables were computed by using a triaxial accelerometer (Noraxon, USA). One-way ANOVA was used to test the influence of the running speed on the parameters. Pearson's partial correlation was used to investigate the relationship between the peak impact and shear force, and accelerometer variables. Results: The running speed affected the peak impact and posterior shear force, time, slope, and peak vertical and resultant tibial acceleration, slope at heel contact. Significant correlations were noticed between the peak impact force and peak vertical and resultant tibia acceleration, and between peak impact average slope and peak vertical and resultant tibia acceleration average slope, and between posterior peak (FyP) and peak vertical tibia acceleration, and between posterior peak instantaneous slop and peak vertical tibial acceleration during running at 3 m/s. However, it was observed that correlations between peak impact average slope and peak vertical tibia acceleration average slope, between posterior peak time and peak vertical and resultant tibia acceleration time, between posterior peak instantaneous slope and peak vertical tibial acceleration instantaneous slope during running at 4 m/s. Conclusion: Careful analysis is required when investigating the linear relationship between the impact and shear force, and tibia accelerometer components during relatively fast running speed.