• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.249-251
• /
• 2021

In this paper, we introduce the deep-learning system using Tensorflow for recognizing situations that can occur fall situations when the elderly are moving or standing. Fall detection uses the LSTM (long short-term memory) learned using Tensorflow to determine whether it is a fall or not by data measured from wearable accelerator sensor. Learning is carried out for each of the 7 behavioral patterns consisting of 4 types of activity of daily living (ADL) and 3 types of fall. The learning was conducted using the 3-axis acceleration sensor data. As a result of the test, it was found to be compliant except for the GDSVM(Gravity Differential SVM), and it is expected that better results can be expected if the data is mixed and learned.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.4
• /
• pp.510-516
• /
• 2019

In this paper, a snowboard simulator that measures the user's motion and makes the user feel physical changes and enjoy actual snowboarding was developed. The speed and direction of the snowboard are determined by the user's center of gravity. The developed simulator is equipped with four springs on the snowboard plate, so that the slope can change according to the change in the user's weight center and be felt directly. The slope due to the change in the center of gravity of the user is measured using a three-axis acceleration sensor. The friction of the slope generated by the rotation of the snowboard is made possible by the user using the BLDC motor, and the rotation of the snowboard is measured using the hole sensor. For rapid data processing of the simulator, two MCUs are used to transfer the measured data to the PC using the acceleration sensor and motor separately. The developed simulator can experience slopes and friction of the slope directly, and wear measured data and HMD to enjoy more realistic snowboarding.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.628-632
• /
• 2003

An intelligent miniature humanoid robot system is designed and implemented as a platform for researching walking algorithm. The robot system consists of a mechanical robot body, a control system, a sensor system, and a human interface system. The robot has 6 dofs per leg, 3 dofs per arm, and 2 dofs for a neck, so it has total of 20 dofs to have dexterous motion capability. For the control system, a supervisory controller runs on a remote host computer to plan high level robot actions based on the vision sensor data, a main controller implemented with a DSP chip generates walking trajectories for the robot to perform the commanded action, and an auxiliary controller implemented with an FPGA chip controls 20 actuators. The robot has three types of sensors. A two-axis acceleration sensor and eight force sensing resistors for acquiring information on walking status of the robot, and a color CCD camera for acquiring information on the surroundings. As an example of an intelligent robot action, some experiments on playing soccer are performed.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.5
• /
• pp.462-469
• /
• 2014

As a basic study on both engineering applications and representation methods of synesthesia, this paper aims at building basic system which converts a muscular sense into both visual and auditory elements. As for the building method, data of the muscular sense can be acquired through roll and pitch signals which are calculated from both three-axis acceleration sensor and the two-axis gyro sensor. The roll and pitch signals are then converted into both visual and auditory information as outputs. The roll signals are converted into both intensity elements of the HSI color model and octaves as one of auditory elements. In addition, the pitch signals are converted into both hue elements of the HSI color model and scales as another one of auditory elements. Each of the extracted elements of the HSI color model is converted into each of the three elements of the RGB color model respectively, so that the real-time output color signals can be obtained. Octaves and scales are also converted and synthesized into MIDI signals, so that the real-time sound signals can be obtained as anther one of output signals. In experiments, the results revealed that normal color and sound output signals were successfully obtained from roll and pitch values that represent muscular senses or physical movements, depending on the conversion relationship based on the similarity between color and sound.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.11 no.2
• /
• pp.215-222
• /
• 2016

Research on gait recognition and its use is actively underway. This study suggests a method to recognize abnormal gaits of pedestrians. The purposes of the existing research to recognize normal steps are to measure physical activities and to validate people by their walks, but the purpose to recognize abnormal steps in this study is to insure the safe life of pedestrians. There are situations in which pedestrians are unaware of themselves vulnerable and can not ask for help. The purpose of this research is that even if pedestrians are unaware of themselves and there are no spontaneous requests for helps, it is intended for them to escape from dangers and difficulties by adopting the recent IOT technology. Hence, this study analyzes normal pace of pedestrians using the triaxial acceleration sensors, and takes ranges of their normal walking. And then, the steps of pedestrians are measured using the triaxial acceleration sensors, contrasted with their normal walking ranges, and determine whether their steps are normal or not. When it is out of the state for normal paces, a method to determine as abnormal paces is suggested.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.7
• /
• pp.1533-1540
• /
• 2012

u-Life care device collect body bio formation, and classify and store them in exercise patterns. Afterwards, the devices send the data through bluetooth wireless communication to the smart phones which set Google Android operation system at regular intervals. The information is checked out through application. u-Life care device calculates calories spent a day after monitoring activity quantity with 3-axis acceleration sensor. The device judges the status of health through body data mining and consults tailored exercise treatment. When sending body data, the device sends them in smart phone through Blue Tooth wireless communication at once. So, as a strong point, the device doesn't need mobile gateway or home gateway used for sending to web server information sensed from exercise life care products.

• Journal of the Institute of Convergence Signal Processing
• /
• v.21 no.1
• /
• pp.21-28
• /
• 2020

In this paper, a new type of electric wheelbarrow is proposed and developed. The developed electric wheelbarrow is equipped with an attitude reference system(ARS) sensor, which consists of 3-axis acceleration sensor and 2-axis Gyro sensor so that it can estimate pitch angle and roll angle. When an operator tilts the wheelbarrow up and down, the pitch angle is detected. The sign of the pitch angle is interpreted as the operator's intention for moving the wheelbarrow forward or backward and the controller drives the wheel of the wheelbarrow with the velocity according to the magnitude of the detected pitch angle. A cargo box of the wheelbarrow is designed to rotate and is controlled to maintain level always, so an operator can handle the electric wheelbarrow easily and safely. The wheelbarrow consists of an in-wheel motor, a DC motor, motor drives, an ARS sensor considering economical use in industrial field. Three experiments are performed to verify the feasibility and stability of the electric wheelbarrow.

• Imaging Science in Dentistry
• /
• v.32 no.3
• /
• pp.159-165
• /
• 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.

• Journal of Korea Society of Industrial Information Systems
• /
• v.17 no.3
• /
• pp.35-42
• /
• 2012

The database for driving patterns can be utilized in various system such as automatic driving system, driver safety system, and it can be helpful to monitor driving style. Therefore, we propose a driving pattern recognition system in which the sensor streams from a smartphone are recorded and used for recognizing driving events. In this paper we focus on the driving pattern recognition that is an essential and preliminary step of driving style recognition. We divide input sensor streams into 7 driving patterns such as, Left-turn(L), U-turn(U), Right-turn(R), Rapid-Braking(RB), Quick-Start(QS), Rapid-Acceleration (RA), Speed-Bump(SB). To classify driving patterns, first, a preprocessing step for data smoothing is followed by an event detection step. Last the detected events are classified by DTW(Dynamic Time Warping) algorithm. For assisting drivers we provide the classified pattern with the corresponding video stream which is recorded with its sensor stream. The proposed system will play an essential role in the safety driving system or driving monitoring system.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2011.04a
• /
• pp.30-32
• /
• 2011

본 연구는 보다 직관적이고 체감적인 인터페이스를 구현하기 위한 디바이스로서의 데이터 글로브를 제시한다. 검지부터 소지까지 총 4개의 손가락 움직임을 감지하고 3-Axis Acceleration Sensor를 통하여 움직임을 감지, 전송하는 데이터 글로브 디바이스를 설계하고, 본 디바이스에서 전송된 값을 처리하여 어플리케이션에 적용 가능한 데이터로 전환하는 방법에 대하여 제안하였다. 또한 이를 통한 실제 체감형 어플리케이션의 구현을 통하여 효율적인 인터페이싱 방안의 사례를 제시하였다.