• Therapeutic Science for Rehabilitation
• /
• v.11 no.4
• /
• pp.55-68
• /
• 2022

Objective : This review aimed to provide information for clinical application by confirming the principles and characteristics of the tool through a review of tongue movement and measurement tools for patients with swallowing disorders. Results : We identified 15 tools used as tongue exercises and measurement tools in the field of dysphagia. According to principle, the tools were classified as either a bulb sensor, resistive sensor sheet, mouthpiece with sensor, or other techniques. The bulb sensor was easy to use but had limitations in fixing the position when measuring tongue pressure. The resistive sensor sheet could be measured at a more stable position than the bulb sensor. A mouthpiece with a sensor could be used in an individual's oral cavity such that the position was fixed when measuring the tongue pressure. Other techniques had the advantage of being wireless and capable of sensing light. Conclusion : Based on this literature review, it is necessary to facilitate the selection of the best tool for quantitative tongue measurement in dysphagia. The review can also be used to develop a Korean tongue movement tool model that can be used in hospitals and community centers.

• Journal of Sensor Science and Technology
• /
• v.25 no.5
• /
• pp.310-319
• /
• 2016

Three types of gap sensors, a capacitive gap sensor, an eddy current gap sensor, and a Hall effect gap sensor are described and evaluated through experiments for the purpose of precise gap sensing for micrometer scale movement, and a novel type of differential hall effect gap sensor is proposed. Each gap sensor is analyzed in terms of resolution and environment dependency including temperature dependency. Furthermore, a transport system for AMOLED deposition is introduced as a typical application of gap sensors, which are recently receiving considerable attention. Based on the analyses, the proposed differential Hall effect gap sensor is found to be the most suitable gap sensor for precise gap sensing, especially for application to a transport system for AMOLED deposition. The sensor shows resolution of $0.63mV/{\mu}m$ for the overall range of the gap from 0 mm to 2.5 mm, temperature dependency of $3{\mu}m/^{\circ}C$ from $20^{\circ}C$ to $30^{\circ}C$, and a monotonic characteristic for the gap between the sensor and the target.

• Korean Journal of Computational Design and Engineering
• /
• v.18 no.4
• /
• pp.290-298
• /
• 2013

A walking navigation system (usually known as a locomotion interface) is an interactive platform which gives simulated walking sensation to users using sensed bipedal motion signals. This enables us to perform navigation tasks using only bipedal movement. Especially, it is useful for the certain VR task which emphasizes on physical human movement, or accompanies understanding of the size and complexity of building structures. In this work, we described system components of VR walking system and investigated several types of walking platform by literature survey. We adopted a MS Kinect depth sensor for the motion recognition and a treadmill which includes directional turning mechanism for the walking platform. Through the integration of these components with a VR navigation scenario, we developed a simple VR walking navigation system. Finally several technical issues were found during development process, and further research directions were suggested for the system improvement.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.5
• /
• pp.496-504
• /
• 2009

This paper presents a recognition performance of VOR (Vestibular-Ocular Reflex) based vision tracking system for mobile robot. The VOR is a reflex eye movement which, during head movements, produces an eye movement in the direction opposite to the head movement, thus maintaining the image of interested objects placed on the center of retina. We applied this physiological concept to the vision tracking system for high recognition performance in mobile environments. The proposed method was implemented in a vision tracking system consisting of a motion sensor module and an actuation module with vision sensor. We tested the developed system on an x/y stage and a rate table for linear motion and angular motion, respectively. The experimental results show that the recognition rates of the VOR-based method are three times more than non-VOR conventional vision system, which is mainly due to the fact that VOR-based vision tracking system has the line of sight of vision system to be fixed to the object, eventually reducing the blurring effect of images under the dynamic environment. It suggests that the VOR concept proposed in this paper can be applied efficiently to the vision tracking system for mobile robot.

• ETRI Journal
• /
• v.44 no.2
• /
• pp.286-299
• /
• 2022

Human activity recognition in real time is a challenging task. Recently, a plethora of studies has been proposed using deep learning architectures. The implementation of these architectures requires the high computing power of the machine and a massive database. However, handcrafted features-based machine learning models need less computing power and very accurate where features are effectively extracted. In this study, we propose a handcrafted model based on three-dimensional sequential skeleton data. The human body skeleton movement over a frame is computed through joint positions in a frame. The joints of these skeletal frames are projected into two-dimensional space, forming a "movement polygon." These polygons are further transformed into a one-dimensional space by computing amplitudes at different angles from the centroid of polygons. The feature vector is formed by the sampling of these amplitudes at different angles. The performance of the algorithm is evaluated using a support vector machine on four public datasets: MSR Action3D, Berkeley MHAD, TST Fall Detection, and NTU-RGB+D, and the highest accuracies achieved on these datasets are 94.13%, 93.34%, 95.7%, and 86.8%, respectively. These accuracies are compared with similar state-of-the-art and show superior performance.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.5
• /
• pp.544-549
• /
• 2006

This research is to introduce about Judgment System for Intelligent Movement(JSIM) that can perform assistance work of human brain. JSIM can order autonomous command and also it can be directly controlled by user. This research assumes that control object is limited to Mobile Robot(MR) Mobile robot offers image and ultrasonic sensor information to user carrying JSIM and it performs guide to user. JSIM having PDA and Sensor-box controls velocity and direction of the mobile robot by soft-computing method that inputs user's command and information that is obtained to mobile robot. Also it controls mobile robot to achieve various movement. This paper introduces wearable JSIM that communicates with around devices and that can do intelligent judgment. To verify the possibility of the proposed system, in real environment, the simulation of control and application problem lot mobile robot will be introduced. Intelligent algorithm in the proposed system is generated by mixed hierarchical fuzzy and neural network.

• Journal of the Korean Solar Energy Society
• /
• v.21 no.4
• /
• pp.55-62
• /
• 2001

A parabolic dish concentrator used in a high temperature application of solar energy tracks the sun's movement by two axis sun tracking system. In such a system, sun tracking performance affects the system efficiency directly. Generally the higher the tracking accuracy is, the better the system performance is. A large number of parabolic dish type concentrators has been developed and implemented in the world. However none of them clearly provided a qualitative method of how the accuracy of the sun tracking system can be evaluated. The work presented here is the evaluation of sun tracking performance of parabolic dish concentrator, which follows the sun's movement by the sensor, using a computer vision system. We install a camera on the parabolic dish concentrator. While the concentrator follows the sun, sun's images are captured continuously. Then the performance of sun tracking system was evaluated by analyzing the variation of the position of the sun in the captured images.

• The Journal of Korea Robotics Society
• /
• v.7 no.4
• /
• pp.276-283
• /
• 2012

Due to the low localization accuracy and the requirement of special infrastructure, current LBS(Localization Based Service) is limited to show P.O.I.(Point of Interest) nearby. Improvement of IMU(Inertial Measurement Unit) based deadreckoning is presented in this paper. Additional sensors such as the magnetic compass and magnetic flux sensors are used as well as the accelerometer and the gyro for getting more information of movement. Based on the pedestrian movement, appropriate sensor information is selected and the complementary filter is used in order to enhance the accuracy of the localization.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.2
• /
• pp.108-115
• /
• 2011

This paper describes a new sensor system for mobile robot motion estimation using stereo infrared light sources and a camera. Visibility is being applied to robotic obstacle avoidance path planning and localization. Using simple visibility computation, the environment is partitioned into many visibility sectors. Based on the recognized edges, the sector a robot belongs to is identified and this greatly reduces the search area for localization. Geometric modeling of the vision system enables the estimation of the characteristic pixel position with respect to the robot movement. Finite difference analysis is used for incremental movement and the error sources are investigated. With two characteristic points in the image such as vertices, the robot position and orientation are successfully estimated.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2000.11a
• /
• pp.647-652
• /
• 2000

This paper presents a study on the position tracking control of robot system on the uncertain elastic base. The elastic base is modeled as a virtual robot which has passive joints and the control strategy is using approximate Jacobian operators. Jacobian operators represent the overall robot system including base movement. However, because we don't know the base movement we can't estimate the jacobian operators directly. The control algorithm is proposed which uses only Jacobian operators of a real robot as approximate Jacobian operators. The measured errors from external sensor are compensated by approximate Jacobian operators. The simulation results of a single-axis robot system show that the control strategy can be used for position tracking.