• Journal of Nutrition and Health
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• v.50 no.6
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• pp.552-564
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• 2017

Purpose: The purpose of this study was to measure energy expenditure (EE) the metabolic equivalents (METs) of 13 common physical activities by using a portable telemetry gas exchange system ($K4b^2$) and to assess the accuracy of the accelerometer (Actigraph $GT3X^+$) by gender in Korean adults. Methods: A total of 109 adults (54 males, 55 females) with normal BMI (body mass index) participated in this study. EE and METs of 13 selected activities were simultaneously measured by the $K4b^2$ portable indirect calorimeter and predicted by the $GT3X^+$ Actigraph accelerometer. The accuracy of the accelerometer was assessed by comparing the predicted with the measured EE and METs. Results: EE (kcal/kg/hr) and METs of treadmill walking (3.2 km/h, 4.8 km/h and 5.6 km/h) and running (6.4 km/h) were significantly higher in female than in male participants (p < 0.05). On the other hand, the accelerometer significantly underestimated the EE and METs for all activities except descending stairs, moderate walking, and fast walking in males as well as descending stairs in females. Low intensity activities had the highest rate of accurate classifications (88.3% in males and 91.3% females), whereas vigorous intensity activities had the lowest rate of accurate classifications (43.6% in males and 27.7% in females). Across all activities, the rate of accurate classification was significantly higher in males than in females (75.2% and 58.3% respectively, p < 0.01). Error between the accelerometer and $K4b^2$ was smaller in males than in females, and EE and METs were more accurately estimated during treadmill activities than other activities in both males and females. Conclusion: The accelerometer underestimated EE and METs across various activities in Korean adults. In addition, there appears to be a gender difference in the rate of accurate accelerometer classification of activities according to intensity. Our results indicate the need to develop new accelerometer equations for this population, and gender differences should be considered.

• Korean Journal of Applied Biomechanics
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• v.30 no.2
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• pp.145-154
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• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.187-192
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• 1992

There are several potential error sources that can affect the estimation of the position of an object using combined vision and acceleration measurements. Two of the major sources, accelerometer dynamics and random noise in both sensor outputs, are considered. Using a second-order model, the errors introduced by the accelerometer dynamics are reduced by the smaller value of damping ratio and larger value of natural frequency. A Kalman filter approach was developed to minimize the influence of random errors on the position estimate. Experimental results for the end-point movement of a flexible beam confirmed the efficacy of the Kalman filter algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.518-524
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• 2011

This paper presents a study on the calibration of accelerometer data in the gyroscope free inertial navigation system(GFINS) using fuzzy inference system(FIS). The conventional INS(inertial navigation system) which can measure yaw rate and linear velocity using inertial sensors as the gyroscope and accelerometer. However, the INS is difficult to design as small size and low power because it uses the gyroscope. To solve the problem, the GFINS which does not have the gyroscope have been studied actively. However, the GFINS has cumulative error problem still. Hence, this paper proposes Fuzzy-GFINS which can calibrate the data of an accelerometer using FIS consists of two inputs that are ratio between linear velocity of the autonomous ground vehicle(AGV) and the accelerometer and ratio between linear velocity of the encoders and the accelerometer. To evaluate the proposed Fuzzy-GFINS, we made the AGV with Mecanum wheels and applied the proposed Fuzzy-GFINS. In experimental result, we verified that the proposed method can calibrate effectively data of the accelerometer in the GFINS.

• Therapeutic Science for Rehabilitation
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• v.5 no.2
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• pp.57-69
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• 2016

Objective: The purpose of this study was to systematically review the articles using accelerometer to measure activity of daily living of patients with stroke. Methods: Depending on selection criteria, 13 studies were searched for PubMed, EMBASE, and Cochrane library database from February 2014 to March 2014. A total of 331 papers were searched, and 13 of these were selected. Results: In studies of 13 selected, acute, subacute, and chronic patients with stroke were enrolled. The kind of accelerometer was uniaxial, biaxial, and triaxial, activity monitor. Measurement activities were mainly arm activity, walking activity, and attachment sites were also various depending on the measurement activities. A measured variable was the total number of activities, the movement speed of the patients, ratio between affected and non-affected, and motion analysis. The result indicated that significant correlation with the other assessment tools in all studies. Conclusions: Accelerometer will be applied with a tool for measuring activity of daily living of patients with stroke, depending on activities characteristics. Further, we need accelerometer studies to apply with a variety of assessment in clinical practice or community settings.

• Journal of The Korean Association of Information Education
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• v.15 no.1
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• pp.147-154
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• 2011

In this Paper, we suggest the effective pre-correction algorithm on sensor values and the classification algorithm for gesture recognition that use values for each axis of the accelerometer to send data(a number or specific input data) to device. we know that creation of reliable preprocessed data in experimental results through the error rate of X-Axis and Y-Axis for pre-correction and post-correction. we can show high recognition rate through recognizer using the normalization and classification algorithm for the preprocessed data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1324-1330
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• 2007

In this paper, we propose pattern recognition algorithm for activities of daily living by adopting extreme learning machine based on single layer feedforward networks(SLFNs) to the signal from bidirectional accelerometer. For activity classification, 20 persons are participated and we acquire 6, types of signals at standing, walking, running, sitting, lying, and falling. Then, we design input vector using reduced model for ELM input. In ELM classification results, we can find accuracy change by increasing the number of hidden neurons. As a result, we find the accuracy is increased by increasing the number of hidden neuron. ELM is able to classify more than 80 % accuracy for experimental data set when the number of hidden is more than 20.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.875-880
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• 2012

According to the fixation detailed drawing and lightweight anger tendency of the product the vibration control of precision equipments is essential and establishes under the equipments. so It is important to know vibration characteristics of vibration isolator. For this reason the accelerometer attaches in vibration isolator and measures an acceleration response. The acceleration response which is measured will lead double integral and will be able to predict a displacement of vibration isolator. However, in compliance with the effect of the accelerometer can not be accurately. From this paper, mass, damping ratio and natural frequency of the accelerometers by changing the vibration isolator to predict the acceleration response and the results were compared.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.221-222
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• 2018

본 논문에서는 android의 accelerometer sensor를 활용하여 예기치 못한 상황에 사용자를 보호 할 수 있는 어플리케이션을 설계하고 구현한다. 이 어플리케이션은 스마트폰을 흔들 때 accelerometer sensor가 센싱하여 어플리케이션을 자동으로 실행한다. 또한 경광등 소리를 울리고 사용자의 위치정보를 어플리케이션에 저장된 지인의 연락처로 전송한다. 사용자는 자신이 빈번하게 다니는 경로를 저장할 수 있으며, 이 경로에 대한 정보를 연락처에 저장된 지인들에게 제공한다. 이 어플리케이션을 사용하는 사용자는 범죄로부터 자신을 지키고, 위험한 경우 주변 사람들에게 도움을 요청할 수 있는 기능을 제공한다.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.379-380
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• 2006

As a result of growth sensor-enabled mobile devices such as PDA, cellular phone and other computing devices, in recent years, users can utilize the diverse digital contents everywhere and anytime. However, the interfaces of mobile applications are often unnatural due to limited resources and miniaturized input/output. Especially, users may feel this problem in some applications such as the mobile game. Therefore, Novel interaction forms have been developed in order to complement the poor user interface of the mobile device and to increase the interest for the mobile game. In this paper, we describe the demonstration of the gesture and posture input supported by an accelerometer. The application example we created are AM-Fishing game on the mobile device that employs the accelerometer as the main interaction modality. The demos show the usability for the gesture and posture interaction.