• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.65-70
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• 2001

We consider a hyper-redundant system that consists of many uniform units. The hyper-redundant system has many degrees of freedom and it can accomplish various tasks. Applysing the reinforcement learning to the hyper-redundant system is very attractive because it is possible to acquire various behaviors for various tasks automatically. In this paper we present a new reinforcement learning algorithm "Q-learning with propagation of motion". The algorithm is designed for the multi-agent systems that have strong connections. The proposed algorithm needs only one small Q-table even for a large scale system. So using the proposed algorithm, it is possible for the hyper-redundant system to learn the effective behavior. In this algorithm, only one leader agent learns the own behavior using its local information and the motion of the leader is propagated to another agents with time delay. The reward of the leader agent is given by using the whole system information. And the effective behavior of the leader is learned and the effective behavior of the system is acquired. We apply the proposed algorithm to a snake-like hyper-redundant robot. The necessary condition of the system to be Markov decision process is discussed. And the computer simulation of learning the locomotion is demonstrated. From the simulation results we find that the task of the locomotion of the robot to the desired point is learned and the winding motion is acquired. We can conclude that our proposed system and our analysis of the condition, that the system is Markov decision process, is valid.

• The Journal of Korean Physical Therapy
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• v.31 no.6
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• pp.333-338
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• 2019

Purpose: Although previous studies on the screw-home movement (SHM) for autopsy specimen and walking of living persons conducted, the possibility of acquiring SHM based on inertial measurement units received little attention. This study aimed to investigate the possibility of measuring SHM for the non-weighted bearing using a micro-electro-mechanical system-based wearable motion capture system (MEMSS). Methods: MEMSS and camera-based motion analysis systems were used to obtain kinematic data of the knee joint. The knee joint moved from the flexion position to a fully extended position and then back to the start point. The coefficient of multiple correlation and the difference in the range of motion were used to assess the waveform similarity in the movement measured by two measurement systems. Results: The waveform similarity in the sagittal plane was excellent and the in the transverse plane was good. Significant differences were found in the sagittal plane between the two systems (p<0.05). However, there was no significant difference in the transverse plane between the two systems (p>0.05). Conclusion: The SHM during the passive motion without muscle contraction in the non-weighted bearing appeared in the entire range. We thought that the MEMSS could be easily applied to the acquisition of biomechanical data on the knee related to physical therapy.

• Journal of the Korean Society of Clothing and Textiles
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• v.39 no.3
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• pp.369-378
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• 2015

Various forms of wearable bio-signal monitoring systems have been developed recently. Acquisition of stable bio-signal data for health care purposes needs to be unconscious and continuous without hindrance to the users' daily activities. The garment type is a suitable form of a wearable bio-signal monitoring system; however, motion artifacts caused by body movement degrade the signal quality during the measurement of bio-signals. It is crucial to stabilize the electrode position to reduce motion artifacts generated when in motion. The problems with motion artifacts remain unresolved despite their significant effect on bio-signal monitoring. This research creates a foundation for the design of garment-type wearable systems for everyday use by finding a method to reduce motion artifacts through modular design. Two distinct garment-type wearable systems (tee-shirt with a motion artifact-reducing module (MARM) and tee-shirt without a MARM) were designed to compare the effects of modular design on the measurement of heart activity in terms of electrode position displacement, signal quality index value, and morphological quality. The tee-shirt with MARM showed superior properties and yielded higher quality signals than the tee-shirt without MARM. In addition, the tee-shirt with MARM showed a better repeatability of the heart activity signals. Therefore, a garment design with MARM is an efficient way to acquire stable bio-signals while in motion.

• ETRI Journal
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• v.32 no.6
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• pp.881-890
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• 2010

Conventional fire detection systems use physical sensors to detect fire. Chemical properties of particles in the air are acquired by sensors and are used by conventional fire detection systems to raise an alarm. However, this can also cause false alarms; for example, a person smoking in a room may trigger a typical fire alarm system. In order to manage false alarms of conventional fire detection systems, a computer vision-based fire detection algorithm is proposed in this paper. The proposed fire detection algorithm consists of two main parts: fire color modeling and motion detection. The algorithm can be used in parallel with conventional fire detection systems to reduce false alarms. It can also be deployed as a stand-alone system to detect fire by using video frames acquired through a video acquisition device. A novel fire color model is developed in CIE $L^*a^*b^*$ color space to identify fire pixels. The proposed fire color model is tested with ten diverse video sequences including different types of fire. The experimental results are quite encouraging in terms of correctly classifying fire pixels according to color information only. The overall fire detection system's performance is tested over a benchmark fire video database, and its performance is compared with the state-of-the-art fire detection method.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.5 no.1
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• pp.111-115
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• 2011

In this paper, we present a novel time-synchronization method for distributed systems to measure the body motion. The distributed system scheme is considered because human data acquisition systems tend to have a centralized controller with sensors connected with a long range of electric wires running through the subject's body, which results in inconvenience. Utilizing simple key switches and digital input ports for reading the key, the proposed method requires a very simple hardware structure, which means less power consumption compared with the well-known ubiquitous sensor network. After measuring the motion data as well as the synchronization pulses, the proposed method compensates, in offline, the difference of the sampling instance between the two systems by scaling the time difference. The paper presents experimental results to show the validity of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.332-339
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• 2014

Face classification has wide applications in security and surveillance. However, this technique presents various challenges caused by pose, illumination, and expression changes. Face recognition with long-distance images involves additional challenges, owing to focusing problems and motion blurring. Multiple frames under varying spatial or temporal settings can acquire additional information, which can be used to achieve improved classification performance. This study investigates the effectiveness of multi-frame decision-level fusion with photon-counting linear discriminant analysis. Multiple frames generate multiple scores for each class. The fusion process comprises three stages: score normalization, score validation, and score combination. Candidate scores are selected during the score validation process, after the scores are normalized. The score validation process removes bad scores that can degrade the final output. The selected candidate scores are combined using one of the following fusion rules: maximum, averaging, and majority voting. Degraded facial images are employed to demonstrate the robustness of multi-frame decision-level fusion in harsh environments. Out-of-focus and motion blurring point-spread functions are applied to the test images, to simulate long-distance acquisition. Experimental results with three facial data sets indicate the efficiency of the proposed decision-level fusion scheme.

• Journal of Information Technology Services
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• v.10 no.1
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• pp.65-72
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• 2011

In this paper, we consist of three dimensional acceleration sensor as a small-sized sensor module to acquire base technologies that need to estimate exhibition audience' moving distance. and that we developed algorism and device that can calculate acceleration in gravity direction with attaching it to people's body part without regard to three dimensional direction. By making use of the sensor module, we have to process the data that let it quantitatively process possible to measure people's walk and movement by computer system. We normalized sensor output data in the process of change from sensor module to acquisition of data, rectangular coordinates and single scalar acceleration value in gravity direction. Printed out sensor data attaching sensor module to people's body part is used for motion pattern detection after normalization, Motion sensor devised mode change algorism because it print data of other pattern according to attached position of body. For algorism design, we collected data occurring during walking about subject and we also defined occurring problem domain after analyzing the data. We settle defined problem domain and that we simulated the walking number measuring instrument with highly efficient in restricted environment.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.1-5
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• 2021

Sleep apnea refers to a condition in which a person does not breathe during sleep, and is a dangerous symptom that blocks oxygen supply in the body, causing various complications, and the elderly and infants can die if severe. In this paper, we present an algorithm that classifies sleep breathing by analyzing the intensity of breathing with images alone in preparation for the risk of sleep apnea. Only the chest of the person being measured is set to the Region of Interest (ROI) to determine the breathing strength by the differential image within the corresponding ROI area. The adult was selected as the target of the measurement and the breathing strength was measured accurately, and the difference in breathing intensity was also distinguished using depth information. Two videos of sleeping babies also show that even microscopic breathing motions smaller than adults can be detected, which is also expected to help prevent infant death syndrome (SIDS).

• Investigative Magnetic Resonance Imaging
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• v.16 no.1
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• pp.55-66
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• 2012

Purpose : During brain MRI scanning, subject's head motion can adversely affect MRI images. To minimize MR image distortion by head movement, we developed an optical tracking system to detect the 3-D movement of subjects. Materials and Methods: The system consisted of 2 CCD cameras, two infrared illuminators, reflective sphere-type markers, and frame grabber with desktop PC. Using calibration which is the procedure to calculate intrinsic/extrinsic parameters of each camera and triangulation, the system was desiged to detect 3-D coordinates of subject's head movement. We evaluated the accuracy of 3-D position of reflective markers on both test board and the real MRI scans. Results: The stereo system computed the 3-D position of markers accurately for the test board and for the subject with glasses with attached optical reflective marker, required to make regular head motion during MRI scanning. This head motion tracking didn't affect the resulting MR images even in the environment varying magnetic gradient and several RF pulses. Conclusion: This system has an advantage to detect subject's head motion in real-time. Using the developed system, MRI operator is able to determine whether he/she should stop or intervene in MRI acquisition to prevent more image distortions.

• Progress in Medical Physics
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• v.24 no.1
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• pp.76-83
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• 2013

Previous studies about effect of respiratory motion on diagnostic imaging and radiation therapy have been performed by monitoring external motions but these can not reflect internal organ motion well. The aim of this study was to develope the artificial pulmonary nodule able to perform non-invasive implantation to dogs in the thorax and to evaluate applicability of the model to respiratory motion studies on PET image acquisition and radiation delivery by phantom studies. Artificial pulmonary nodule was developed on the basis of 8 Fr disposable gastric feeding tube. Four anesthetized dogs underwent implantation of the models via trachea and implanted locations of the models were confirmed by fluoroscopic images. Artificial pulmonary nodule models for PET injected $^{18}F$-FDG and mounted on the respiratory motion phantom. PET images of those acquired under static, 10-rpm- and 15-rpm-longitudinal round motion status. Artificial pulmonary nodule models for radiation delivery inserted glass dosemeter and mounted on the respiratory motion phantom. Radiation delivery was performed at 1 Gy under static, 10-rpm- and 15-rpm-longitudinal round motion status. Fluoroscpic images showed that all models implanted in the proximal caudal bronchiole and location of models changed as respiratory cycle. Artificial pulmonary nodule model showed motion artifact as respiratory motion on PET images. SNR of respiratory gated images was 7.21. which was decreased when compared with that of reference images 10.15. However, counts of respiratory images on profiles showed similar pattern with those of reference images when compared with those of static images, and it is assured that reconstruction of images using by respiratory gating improved image quality. Delivery dose to glass dosemeter inserted in the models were same under static and 10-rpm-longitudinal motion status with 0.91 Gy, but dose delivered under 15-rpm-longitudinal motion status was decreased with 0.90 Gy. Mild decrease of delivered radiation dose confirmed by electrometer. The model implanted in the proximal caudal bronchiole with high feasibility and reflected pulmonary internal motion on fluoroscopic images. Motion artifact could show on PET images and respiratory motion resulted in mild blurring during radiation delivery. So, the artificial pulmonary nodule model will be useful tools for study about evaluation of motion on diagnostic imaging and radiation therapy using laboratory animals.