• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1735-1736
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• 2008

In this research, a riding robot system named as "RideBot" is developed for health-care and entertainments. The developed riding robot can follow the intention of horseman and can simulate the motion of horse. The riding robot mechanisms are used for many functions of attitude detection, motion sensing, recognition, common interface and motion-generations. This riding robot can react on health conditions, bio-signals and intention informations of user. One of the objectives of this research is that the riding robot could catch user motion and operate spontaneous movements. In this paper, we develope the saddle mechanism which can generate 3 degrees-of-freedom riding motion based on the intention of horseman. Also, we develope reins and spur mechanism for the recognition of the horseman's intention estimation and the bio-signal monitoring system for the health care function of a horseman. In order to evaluate the performance of the riding robot system, we tested several riding motions including slow and normal step motion, left and right turn motion.

• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.21-28
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• 2016

The aim of this research is to analyze Perceived Usefulness(PU) and Perceived Ease of Use(PEOU) based on Technology Acceptance Model in , and how viewing experiences and knowledge of motion graphics have an impact on attitude toward using and behavioral intention to use. Both usability for learning and usability for appreciation in terms of PU have significant correlations with the degree of satisfaction and immersion, and behavioral intention to use. On the other hand, PEOU has an influence on degree of exhibition satisfaction and immersion, and onto behavioral intention to use with the exception of intention to revisiting . Unlike PU or PEOU, previous viewing experiences do not have correlation with attitude toward using and behavioral intention to use. Only previous knowledge of motion graphics has a correlation with degree of satisfaction and immersion, and behavioral intention to use. As the influence on PU and PEOU's attitude toward using and and behavioral intention to use has been verified, our findings show that two variables of TAM enable the prediction of user's technology acceptance on digital exhibitions and as a result prove the suitability for TAM as an evaluation model for digital exhibition of remediating the originals. This study offers a fresh understanding of the importance of motion graphic effects which influence attitude toward using and behavioral intention to use from the perspective of curating methodology.

• Korean Journal of Cognitive Science
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• v.25 no.3
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• pp.259-276
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• 2014

Artists such as Duchamp and Balla tried to portray moving objects on static canvases by superimposing snapshots of moving objects. Previously, our group showed the influence of prior experience on brain responses within a motion-sensitive area MT+ to abstr act paintings with or without implied motion. In the present study, we went further to investigate whether the differential MT+activation between observers is originated from differential eye movement patterns. Prior experience was defined operationally with major in art. In addition, we examined whether perceiver's awareness of artist's intention concerning the implied motion, as well as expertise in art, affects the way he/she views the artwork. Results showed that the number and the duration of fixation on the abstract paintings tended to differ between participants based on art major. The awareness of artist's intention was not related to such differences. In contrast, observers' awareness of artist's intention of implying motion affected eye movement patterns in specific regions of the abstract paintings where the motion was portrayed. In other words, observers with awareness focused more on the parts of paintings portraying motion and moved their eyes in the direction corresponding to the direction of moving objects than observers without awareness. Expertise was not related to such specific eye movement patterns. The present study implies that art expertise and awareness of artist's intention play differential roles in observers' perception of paintings with implied motion. Namely, it suggests that expertise is related to the overall perception of paintings, while awareness of implied motion is related to perception of the specific spatial information in those paintings.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.10
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• pp.927-932
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• 2010

Estimation methods of motion intention from bio-signal present challenges in man machine interaction(MMI) to offer user's command to machine without control of any devices. Measurements of meaningful bio-signals that contain the motion intention and motion estimation methods from bio-signal are important issues for accurate and safe interaction. This paper proposes a novel motion estimation sensor based on a geometrical muscle changes, and a motion estimation method using the sensor. For estimation of the motion, we measure the circumference change of the muscle which is proportional to muscle activation level using a flexible piezoelectric cable (pMAS, piezo muscle activation sensor), designed in band type. The pMAS measures variations of the cable band that originate from circumference changes of muscle bundles. Moreover, we estimate the elbow motion by applying the sensor to upper limb with least square method. The proposed sensor and prediction method are simple to use so that they can be used to motion prediction device and methods in rehabilitation and sports fields.

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.124-131
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• 2017

This paper present a novel approach to control the lower body power assistive exoskeleton system of a HEXAR-CR35 aimed at improving a muscular strength. More specifically the control of based on the human intention is crucial of importance to ensure intuitive and dexterous motion with the human. In this contribution, we proposed the detection algorithm of the human intention using the MCRS which are developed to measure the contraction of the muscle with variation of the circumference. The proposed algorithm provides a joint motion of exoskeleton corresponding the relate muscles. The main advantages of the algorithm are its simplicity, computational efficiency to control one joint of the HEXAR-CR35 which are consisted knee-active type exoskeleton (the other joints are consisted with the passive or quasi-passive joints that can be arranged by analyzing of the human joint functions). As a consequence, the motion of exoskeleton is generated according to the gait phase: swing and stance phase which are determined by the foot insole sensors. The experimental evaluation of the proposed algorithm is achieved in walking with the exoskeleton while carrying the external mass in the back side.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.4
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• pp.191-197
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• 2022

This study proposes an image-based Pose Intention Network (PIN) algorithm for rehabilitation via patients' intentions. The purpose of the PIN algorithm is for enabling an active rehabilitation exercise, which is implemented by estimating the patient's motion and classifying the intention. Existing rehabilitation involves the inconvenience of attaching a sensor directly to the patient's skin. In addition, the rehabilitation device moves the patient, which is a passive rehabilitation method. Our algorithm consists of two steps. First, we estimate the user's joint position through the OpenPose algorithm, which is efficient in estimating 2D human pose in an image. Second, an intention classifier is constructed for classifying the motions into three categories, and a sequence of images including joint information is used as input. The intention network also learns correlations between joints and changes in joints over a short period of time, which can be easily used to determine the intention of the motion. To implement the proposed algorithm and conduct real-world experiments, we collected our own dataset, which is composed of videos of three classes. The network is trained using short segment clips of the video. Experimental results demonstrate that the proposed algorithm is effective for classifying intentions based on a short video clip.

• Journal of Korea Multimedia Society
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• v.19 no.1
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• pp.68-79
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• 2016

Electromyographic (EMG) signals have been widely used as motion commands of prosthetic arms. Although EMG signals contain meaningful information including the movement intentions of human body, it is difficult to predict the subject's motion by analyzing EMG signals in real-time due to the difficulties in extracting motion information from the signals including a lot of noises inherently. In this paper, four Ag/AgCl electrodes are placed on the surface of the subject's major muscles which are in charge of four upper arm movements (wrist flexion, wrist extension, ulnar deviation, finger flexion) to measure EMG signals corresponding to the movements. The measured signals are sampled using DAQ module and clustered sequentially. The Fuzzy C-Means (FCMs) method calculates the center values of the clustered data group. The fuzzy system designed to detect the upper arm movement intention utilizing the center values as input signals shows about 90% success in classifying the movement intentions.

• The Journal of Korea Robotics Society
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• v.18 no.4
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• pp.496-504
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• 2023

This paper recognizes the motion intention of the wearer using a muscle stiffness sensor and proposes a control system for a wearable robot based on this. The proposed system recognizes the onset time of the motion using sensor data, determines the assistance mode, and provides assistive torque to the hip flexion/extension motion of the wearer through the generated reference trajectory according to the determined mode. The onset time of motion was detected using the CUSUM algorithm from the muscle stiffness sensor, and by comparing the detection results of the onset time with the EMG sensor and IMU, it verified its applicability as an input device for recognizing the intention of the wearer before motion. In addition, the stability of the proposed method was confirmed by comparing the results detected according to the walking speed of two subjects (1 male and 1 female). Based on these results, the assistance mode (gait assistance mode and muscle strengthening mode) was determined based on the detection results of onset time, and a reference trajectory was generated through cubic spline interpolation according to the determined assistance mode. And, the practicality of the proposed system was also confirmed by applying it to an actual wearable robot.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.7
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• pp.15-21
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• 2009

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2685-2688
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• 2003

A PC-based system for both monitoring and controlling SAUV is developed. The developed system is located on a ship and communicate with the SAUV through optical link through which the system sends motion command and receives video data, SSBL and Digital I/O data. The motion command includes velocity data and direction data. The overall system is developed with the intention of easy operation for operator and safe motion of SAUV. The easy operation is realized by GUI-based interface and the safe motion is realized by fault tolerant capability.