• 센서학회지
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• 제16권6호
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• pp.467-474
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• 2007

The real-time monitoring about the activity of the human provides useful information about the activity quantity and ability. The present study implemented a small-size and low-power acceleration monitoring system for convenient monitoring of activity quantity and recognition of emergent situations such as falling during daily life. For the wireless transmission of acceleration sensor signal, we developed a wireless transmission system based on a wireless sensor network. In addition, we developed a program for storing and monitoring wirelessly transmitted signals on PC in real-time. The performance of the implemented system was evaluated by assessing the output characteristic of the system according to the change of posture, and parameters and acontext recognition algorithm were developed in order to monitor activity volume during daily life and to recognize emergent situations such as falling. In particular, recognition error in the sudden change of acceleration was minimized by the application of a falling correction algorithm

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• 제43권4호
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• pp.256-261
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• 2017

Objectives: The concept of natural head position (NHP) was first introduced by Broca in 1862, and was described as a person's stable physiologic position "when a man is standing and his visual axis is horizontal." NHP has been used routinely for clinical examination; however, a patient's head position is random during cone-beam computed tomography (CBCT) acquisition. To solve this problem, we developed an accelerometer to record patients' NHP and reproduce them for CBCT images. In this study, we also tested the accuracy and reproducibility of our accelerometer. Materials and Methods: A total of 15 subjects participated in this study. We invented an accelerometer that measured acceleration on three axes and that could record roll and pitch calculations. Recorded roll and pitch data for each NHP were applied to a reoriented virtual image using three-dimensional (3D) imaging software. The data between the 3D models and the clinical photos were statistically analyzed side by side. Paired t-tests were used to statistically analyze the measurements. Results: The average difference in the angles between the clinical photograph and the 3D model was $0.04^{\circ}$ for roll and $0.29^{\circ}$ for pitch. The paired t-tests for the roll data (P=0.781) and the pitch data (P=0.169) showed no significant difference between the clinical photographs and the 3D model (P>0.05). Conclusion: By overcoming the limitations of previous NHP-recording techniques, our new method can accurately record patient NHP in a time-efficient manner. Our method can also accurately transfer the NHP to a 3D virtual model.

• 전자공학회논문지SC
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• 제48권6호
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• pp.63-70
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• 2011

자전거는 자동차와 달리 사용자인 탑승자가 외부 환경에 그대로 노출되므로, 주변 날씨, 대기, 주행 경로 등에 관한 정보를 자동차 보다 오히려 폭넓게 활용할 필요가 있다. 더욱이 자전거는 인간의 힘을 동력으로 사용하므로 도로의 경사, 굴곡, 노면 상태와 같은 주행 경로의 특성을 미리 파악할 수 있다면 최적 경로 추정 등을 통해 이동 효율을 획기적으로 높이는 데에 도움이 될 것이다. 최근의 모바일 정보 서비스와 함께 개발되는 각종 자전거용 애플리케이션들은 이러한 지능형 자전거를 위한 체계적인 연구 개발의 필요성을 일깨우고 있다. 본 연구에서는 무선 통신이 가능한 저전력 손목 시계형 임베디드 장치를 자전거에 간단히 장착하고, 여기에 내장된 가속도 센서를 이용하여 자전거의 주행 상황 (오르막, 내리막, 정지, 가 감속) 을 자동으로 인식할 수 있는 알고리듬을 개발하는 것을 목표로 하였다. 개발된 알고리듬의 신뢰성을 검사하기 위해 총 19 개의 실험 주행 데이터에 적용한 결과, 전체 실험 데이터의 83.3% 에서 95% 이상의 구간 인식 정확도를 얻을 수 있었다. 향후 임베디드 장치에 내장된 고도 센서, 온도 센서를 추가로 활용하여 탑승자의 신체 상태 및 운동 추정이 가능한 지능형 자전거를 개발할 계획이다. 개발된 주행 상황 인식 기술은 주행 중의 안전을 고려한 지능형 인터페이스 기술의 기반이 될 수 있을 것으로 기대한다.

• Imaging Science in Dentistry
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• 제32권3호
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• pp.159-165
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• 2002

Purpose: The aim of this study was to introduce a method of obtaining the oscillation graphs of the dental x-ray tube heads relative to time using an accelerometer. Materials and Methods: An Accelerometer, Piezotron type 8704B25 (Kistler Instrument Co., Amherst, NY, USA) was utilized to measure the horizontal oscillation of the x-ray tube head immediately after positioning the tube head for an intraoral radiograph. The signal from the sensor was transferred to a dynamic signal analyzer, which displayed the magnitude of the acceleration on the Y-axis and time lapse on the X -axis. The horizontal oscillation of the tube head was measured relative to time, and the settling time was also determined on the basis of the acceleration graphs for 6 wall type, 5 floor-fixed type, and 4 mobile type dental x-ray machines. Results : The oscillation graphs showed that tube head movement decreased rapidly over time. The settling time varied with x-ray machine types. Wall-type x-ray machines had a settling time of up to 6 seconds, 5 seconds for fixed floor-types, and 1 I seconds for the mobile-types. Conclusion: Using an accelerometer, we obtained the oscillation graphs of the dental x-ray tube head relative to time. The oscillation graph with time can guide the operator to decide upon the optimum exposure moment after x-ray tube head positioning for better radiographic resolution.

• 센서학회지
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• 제20권2호
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• pp.137-144
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• 2011

Wireless sensor network(WSN) has the potential to greatly effect many aspects of u-healthcare. By outfitting the potential with WSN, wearable sensor node can collects real-time data on physiological status and transmits through base station to server PC. However, there is a significant gap between WSN and healthcare. WSN has the limited resource about computing capability and data transmission according to bio-sensor sampling rates and channels to apply healthcare system. If a wearable node transmits ECG and accelerometer data of 4 channel sampled at 100 Hz, these data may occur high loss packets for transmitting human activity and ECG to server PC. Therefore current wearable sensor nodes have to solve above mentioned problems to be suited for u-healthcare system. Most WSN based activity and ECG monitoring system have been implemented some algorithms which are applied for signal vector magnitude(SVM) algorithm and ECG noise algorithm in server PC. In this paper, A wearable sensor node using integrated ECG and 3-axial accelerometer based on wireless sensor network is designed and developed. It can form multi-hop network with relay nodes to extend network range in WSN. Our wearable nodes can transmit 1-channel activity data processed activity classification data vector using SVM algorithm to 3-channel accelerometer data. ECG signals are contaminated with high frequency noise such as power line interference and muscle artifact. Our wearable sensor nodes can remove high frequency noise to clear original ECG signal for healthcare monitoring.

• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제55권9호
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• pp.456-460
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• 2006

This paper deals with a novel autocalibration method of three-axis micromachined accelerometers applied to a new digital intelligent putter for golfers. This putter can help golfers monitor and analyze their putting posture and therefore modify their putting action to get better score and enjoy their lives through golf. The micromachined accelerometers to get information of the motion are the essential part of the putter to measure the three-axis acceleration as accurately as possible. This paper presents an efficient autocalibration algorithm to find the offset and sensitivity of accelerometers by only using the static measurement data at six different positions. The experimental results on the developed putters show the validity of the proposed algorithm for the new smart putter.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권10호
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• pp.452-457
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• 2006

In this paper, an algorithm to detect steps in hemiplegic patients using a 3-axis accelerometer a紅ached on the trunk was proposed. The proposed algorithm consisted of the signal pre-processing, the step detector, the classification of steps and the calculation of stride time. Two FIR band-pass filters were designed and steps were measured by the combination of filtered signals in the vertical and the anteroposterior directions. In addition, the classification of steps and the calculation of stride time were computed by using the detected steps and lateral signals. For the experiment, fourteen hemiplegic patients were participated and the linear accelerations of the trunk and foot switch signals were measured synchronously. To evaluate the system performance, the detected steps and initial contacts by the foot switch were compared. The average error between the steps and initial contacts was 0.024ms and the difference of the average stride time was 0.01s. Finally, all gait events were detected exactly. Results showed that the accelerometry could use for the gait evaluation in clinical rehabilitation therapies.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2012년도 추계학술대회 논문집
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• pp.402-403
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• 2012

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2317-2319
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• 2001

This paper presents a sensor fusion algorithm for the RC helicopter which uses a complementary filter. To measure the attitude angle of the helicopter, 3rate gyroscopes and a 3-axis accelerometer are mounted on the helicopter. The signals from them are passed though a complementary filter to produce estimation outputs. Experiments show that designed system is effective for the attitude estimation.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.565-568
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• 2009

본 논문에서는 노약자의 관찰을 위하여 움직임 센서를 이용하여 움직인 정보를 이용하는 방식을 제안한다. 사람이 물체를 움직일 때에 물체에 부착된 3축 가속도 센서를 이용해 움직임 데이터를 전달받고 전달받은 움직인 데이터를 SVM을 이용하여 물체의 움직임을 추정한다. 제안한 시스템의 유용성을 확인하기 위하여 실험에 이용한 데이터들을 데이터베이스화 하여 신경회로망의 학습에 사용하였고, 일상적으로 걸어갈 때, 빠르게 뛰어갈 때, 넘어질 때의 3가기 경우의 움직임을 제대로 검출해 내는가에 대한 실험을 하였다. 실험 경과 80% 이상의 검출 성공률을 볼 수 있었다.