• Asia Marketing Journal
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• 제26권2호
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• pp.90-103
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• 2024

This study investigates the influences of the head movement (nodding vs. head shaking vs. nothing) on consumer attitude and purchase intention toward the product in an online shopping context and introduces the consumer motivation (need vs. want) as a moderating factor for this relationship. Through two studies, this article finds that nodding, as opposed to head shaking or no movement, leads to more positive attitudes and higher purchase intentions toward the product, and this effect is strengthened when the shopping is pursued with a need compared to a want motivation. The effect is found specifically in the fashion industry, where online shopping is most prevalent. Both theoretical and practical implications are discussed.

• 한국의류학회지
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• 제36권2호
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• pp.179-193
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• 2012

The development of modern transportation technology has required many people in spaces (such as vehicle seats, airports, and train stations) for long periods. The public seats provided in these places are manufactured in a standard size; however, fatigue sets in if the seats are unsuitable for the person's physical size. For this reason, this study developed an air cushion vest that would enhance the comfort of vehicle seats. Passengers in vehicles, trains, airplanes, and buses were observed and surveyed to understand the demand for seat comfort. Our analysis found that the greatest source of discomfort was involuntary nodding of the head while asleep and discomfort around the waist area. For this reason, the air cushion vest was designed to support the head and the waist. The neck cushion of this vest was designed to strengthen head support to counter forward nodding because existing commercial neck cushions had no support for forward nodding. For the waist cushion, at lumbar and below-lumbar parts were chosen as the key parts to be supported, the cushion was designed to contain air at those parts. To cover the embedded waist cushion, the vest was designed to be long. The closure was constructed with zippers from the neck to waistline, and with invisible snaps from the waistline to the hemline so that the wearer could open them easily while seated. A subjective comfort evaluation was conducted to verify the effectiveness of the developed vest. In the test, the developed cushions received a better evaluation than cushions currently available on the market. The volume of the vest could be adjusted by the inflow and outflow of air. It was proven that the vest was effective in terms of comfort and portability. This shows that the developed vest could enhance passenger comfort while sitting on vehicle seats.

• 한국정보전자통신기술학회논문지
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• 제9권1호
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• pp.32-37
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• 2016

다른 사람이 차 문에 손가락을 찧는 것을 보면 마치 내게 일어난 일처럼 움찔하지 않는가? 소설을 읽고 감정을 느끼는 것은 왜일까? 이는 공감하기 때문이다. 공감이란 "다른 사람이 느끼는 감정을 목격하거나 기대하는 순간에 정서적으로 반응하는 것"이다. 즉, 공감은 함께 느끼는 것이다. 본 논문에서는 이러한 공감을 측정하는 방법에 대해서 기술하고자 한다. 사람의 감정을 측정하는 것은 쉽지가 않다. 사람들이 소통하는 방식이 다양하기 때문이다. 사람마다 공감을 표현하는 것과 느끼는 감정이 다 다르기 때문에 다양한 방법의 데이터 분석이 필요하다. 이를 위해 본 논문에서는 짧은 단위(1초 단위: 응, 좋아, 아하 등)의 음성과 Head Nodding을 이용한 새로운 공감 측정방법을 제안하려고 한다.

• 성인간호학회지
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• 제21권1호
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• pp.105-116
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• 2009

Purpose: The purpose of the study was to describe nonverbal behaviors of nurses in communication with patients with dementia in an elderly care institution in Korea. Methods: Conversation analysis was utilized to analyze the data which were collected using video camera to capture non-verbal as well as verbal behaviors. A total of 66 episodes of everyday conversations were analyzed using seven nonverbal categories: affirmative head nodding; illustrative gestures; patient-directed eye gaze; smiling and/or laughing; forward leaning; affective touch; and instrumental touch. Results: Among seven categories, patient-directed eye gaze(94%) was the most frequently utilized among nurses followed by affirmative head nodding(67%) and forward leaning(67%), while smiling was the least used(32%). Affective touch was identified in 39 episodes(59%). Among them, the most frequently touched area was hand or handshaking(59%) followed by shoulder or back, arm, and face. There were wide differences among nurses in terms of using affective touch, ranging from 0% to 98%. Nonverbal behaviors were more frequently identified in effective episodes than in ineffective episodes. Conclusion: Actively utilizing effective nonverbal behaviors may help geriatric nurses in promoting communication and in establishing rapport with patients with dementia.

• 대한인간공학회지
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• 제19권1호
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• pp.91-100
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• 2000

In this paper the intent recognition system which recognizes the human's head movements as a simple non-verbal intent representation is presented. The system recognizes five basic intent representations. i.e., strong/weak affirmation. strong/weak negation, and ambiguity by image processing of nodding or shaking movements of head. The vision system for tracking the head movements is composed of CCD camera, image processing board and personal computer. The modified template matching method which replaces the reference image with the searched target image in the previous step is used for the robust tracking of the head movements. For the improvement of the processing speed, the searching is performed in the pyramid representation of the original image. By inspecting the variance of the head movement trajectories. we can recognizes the two basic intent representations - affirmation and negation. Also, by focusing the speed of the head movements, we can see the possibility which recognizes the strength of the intent representation.

• 로봇학회논문지
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• 제10권3호
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• pp.171-177
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• 2015

A telerobot offers a more engaging and enjoyable interaction with people at a distance by communicating via audio, video, expressive gestures, body pose and proxemics. To provide its potential benefits at a reasonable cost, this paper presents a telepresence robot system for video communication which can deliver speaker's head motion through its display stanchion. Head gestures such as nodding and head-shaking can give crucial information during conversation. We also can assume a speaker's eye-gaze, which is known as one of the key non-verbal signals for interaction, from his/her head pose. In order to develop an efficient head tracking method, a 3D cylinder-like head model is employed and the Harris corner detector is combined with the Lucas-Kanade optical flow that is known to be suitable for extracting 3D motion information of the model. Especially, a skin color-based face detection algorithm is proposed to achieve robust performance upon variant directions while maintaining reasonable computational cost. The performance of the proposed head tracking algorithm is verified through the experiments using BU's standard data sets. A design of robot platform is also described as well as the design of supporting systems such as video transmission and robot control interfaces.

• 대한간호학회지
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• 제20권3호
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• pp.381-398
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• 1990

Nursing involves deep human interpersonal relationships between nurses and patients. But in modem Korea, the nurse - patient relationship tends to be ritualistic and mechanestic. Patients usually express the hope that nurses be more tender and kind. Patients expect nurses to express their warmth especially through nonverbal behaviour. This study was conducted to identify patients' preferences for nurse's nonverbal expressions of warmth. Through the confirmation of these preferences, nurses may learn how to enhance their interpersonal relationships with patients. Subjects for the study were 73 patients who had been admitted to a university teaching hospital for at least three days and agreed to be interviewed by the investigator. The interactions were studied nonverbal expressions of warmth during nursing rounds and administration of oral medication. The interview schedule was expecially designed by the investigator to measure the nurse's posture, the distance between the nurse and the patient, the nurse's eye contact, facial expression, hand motion and head nodding. Data analysis included frequencies, percentages and X²-test. The results of this study may be summerized as follows : 1. Patient's preferences for nurse's nonverbal expressions of warmth during nursing rounds. Preferred nurse's posture was sitting(50.7%) or standing(49.3%) opposite the patient. Preferred distance between the nurse and the patient was close to the bed(93.2%), less than 1m. Preferred eye contact was directed to the patient's eyes or their affected part (41.1%). Preferred facial expression was a smile(97.3%). Preferred hand motions were light gestures(41.1%). Patients preferred head nodding which approved their own opinions(69.9%). 2. Patient's preferences for nurse's nonverval expressions of warmth during administration of oral medication. Preferred nurse's posture was standing and waiting to confirm that the medication had been taken(58.9%). Preferred distance from the patient was at arm's length, 0.5-1m(64.4%). Patients preferred direct eye contact(58.9%) and a smile(94.5%). Patients preferred that the nurse put the medicine directly the patient's hand(64.4%). Whether the nurse nodded her head or not was not considered important. 3. The relation of general characteristics and patient's preferences for nurse's nonverbal expressions of warmth during nursing rounds and administration of oral medication. During nursing rounds, the age of subjects(p＝0.010) and the standard of education(p＝0.026) related to the distance between the nurse and the patient. The sick hospital ward related to the eye contact(p＝0.017) and facial expression(p＝0.010). During administration of oral medication, the age of subjects(p＝0.044) and days of hospital treatment (p＝0.043) and the sick hospital ward(p＝0.0004) related to the facial expression. From this study, nurses can learn what kind nonverbal expressions of warmth are preferred by patients during rounds and administration and thus will enhance nurse- patient interpersonal relationships.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권4호
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• pp.256-261
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• 2007

Electroencephalographic(EEG) is used to record activities of human brain in the area of psychology for many years. As technology developed, neural basis of functional areas of emotion processing is revealed gradually. So we measure fundamental areas of human brain that controls emotion of human by using EEG. Hands gestures such as shaking and head gesture such as nodding are often used as human body languages for communication with each other, and their recognition is important that it is a useful communication medium between human and computers. Research methods about gesture recognition are used of computer vision. Many researchers study Emotion Recognition method which uses one of EEG signals and Gestures in the existing research. In this paper, we use together EEG signals and Gestures for Emotion Recognition of human. And we select the driver emotion as a specific target. The experimental result shows that using of both EEG signals and gestures gets high recognition rates better than using EEG signals or gestures. Both EEG signals and gestures use Interactive Feature Selection(IFS) for the feature selection whose method is based on the reinforcement learning.

• 제어로봇시스템학회논문지
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• 제13권9호
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• pp.832-837
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• 2007

Electroencephalographic(EEG) is used to record activities of human brain in the area of psychology for many years. As technology develope, neural basis of functional areas of emotion processing is revealed gradually. So we measure fundamental areas of human brain that controls emotion of human by using EEG. Hands gestures such as shaking and head gesture such as nodding are often used as human body languages for communication with each other, and their recognition is important that it is a useful communication medium between human and computers. Research methods about gesture recognition are used of computer vision. Many researchers study Emotion Recognition method which uses one of EEG signals and Gestures in the existing research. In this paper, we use together EEG signals and Gestures for Emotion Recognition of human. And we select the driver emotion as a specific target. The experimental result shows that using of both EEG signals and gestures gets high recognition rates better than using EEG signals or gestures. Both EEG signals and gestures use Interactive Feature Selection(IFS) for the feature selection whose method is based on a reinforcement learning.

• Journal of Chest Surgery
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• 제14권3호
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• pp.254-259
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• 1981

This is a case of successfully surgically treated RVOT obstruction caused by projection of the herniated aortic cusp through subpulmonic supracristal VSD at Department of Thoracic and Cardiovascular Sugery, Hanyang University Hospital. The patient was a 17 year old boy. Congenital heart anomaly was suspected at 2 years of his age. He had palpitation, dyspnea on exertion and epistaxis for 2 years prior to admission to our hospital. On examination, the blood pressure was 170/0mmHg. And the pulse rate was 100/rain. Widening of pulse pressure, water hammer pulse [bounding pulse]. To and fro murmur and head nodding were noted. Cardiomegaly was seen in chest x-ray. EKG, Echocardiography, Cardiac catheterization and angiocardiography were performed. On April 27, 81. Open heart surgery was performed under the impression of VSD combined with AI. On Rt. ventriculotomy, we noticed RVOT obstruction caused by prolapsed rt coronary cusp through a VSD. The subpulmonic supracristal VSD measuring 2.5 x 3 Cm in diameter was closed with Teflon patch graft and then the prolapsed aortic leaflet was plicated by placing three 8-figure suture between the free edge and the base of the leaflet through transverse aortotomy. After operation, excellent result was obtained: B.P, was 110/50mmHg and any sign of AI or residual shunt was not found at discharge.