• Science of Emotion and Sensibility
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• v.14 no.3
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• pp.459-466
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• 2011

Sleep diseases such as snoring and sleep apnea are physically, mentally harmful and results serious health problems. Snoring, known as breathing noise, is caused by coupled oscillation of the airway when the air passes through the trachea, and sleep apnea is caused by upper airway blockage. In order to solve these problems, many attempts have been made to detect the snoring during sleep and alleviate it. In this study, a new sensing system and analysis algorithm were developed in order to detect snoring sounds correctly under various sleep environments. Two polyvinylidene fluoride (PVDF) vibration sensors were used inside the pillow. The first PVDF sensor detects vibration transmitted through skull caused by snoring. And the second PVDF sensor detects both snoring sounds and ambient noises. The signals of two sensors were acquired through the designed analog circuits, and analyzed for snoring detection. Ten volunteers were participated for the experiment under five different conditions. Data from two PVDF sensors were processed by the established analysis algorithm, and snoring sounds were compared to noises. The results indicated that the energy of snoring is 70% bigger than that of ambient noise, which proves effectiveness of sensing system and analysis algorithm. Further study would be continued for more wide clinical studies with various environment noises. Based on this study, development of anti-snore pillow and sleep monitoring system for comfort sleep could be developed.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.207-214
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• 2010

The aim of this study was to investigate upper and lower limb muscle activity using EMG(electromyogram) sensors while walking and identify normal gait pattern using FSR(force sensing resistor) sensor. Fifteen college students participated in this study and their EMG and FSR signal were measured during stopping and walking trials. EMG signals from upper(pectoralis major and trapezius) and lower limbs(rectus femoris, biceps femoris, vastus medialis, vastus lateralis, semimembranosus, semitendinosus, soleus, peroneus longus, gastrocnemius medialis, and gastrocnemius lateralis) were obtained using the surface electrodes. FSR measured pressures on 8 areas of the sole of the foot during walking. EMG results showed that all muscle activities except for vastus lateralis and semimembranosus during walking had higher amplitudes than stopping. Additionally, muscle activities associated with stance and swing phase during walking were identified. Results on FSR showed that stance and swing phases were detected by FSR signals during a gait cycle. Eight gait phases－initial contact, loading response, mid stance, terminal stance, pre swing, initial swing, mid swing, and terminal swing- were classified.

• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.17-30
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• 2017

Lots of interdisciplinary studies for fusion of high technologes and the other areas of research had been tried in these days. In sports training area, high technologies like a vital sign sensor or an accelerometer were adopted as training tools to improve the performance of the sports players. The purpose of this study is finding the proper locations on the human body for attaching the motion sensors in order to develop a smart sportswear which could be helpful in training players. The rowing was selected as a subject sport as lots of movements of the joint on human body could be seen in rowing motions. The players of rowing could be devided into two weight divisions, the lightweight and the heavyweight. In this study, the change rates of distance between markers on human skin as the players moved were took on the back, the elbow, the hip and the knee area on human body by 3D motion capturing system. The distances between markers and the differences between the lightweight and heavyweight were analyzed. Finally, this study provided the guide lines for designing a motion sensing smart sportswear.

• Science of Emotion and Sensibility
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• v.24 no.2
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• pp.65-74
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• 2021

With recent innovations in the ICT industry, the demand for wearable sensing devices to recognize and respond to biological signals has increased. In this study, a three-dimensional (3D) spacer fabric was embedded in a single-wall carbon nanotube (SWCNT) dispersive solution through a simple penetration process to develop a monolayer piezoresistive pressure sensor. To induce electrical conductivity in the 3D spacer fabric, samples were immersed in the SWCNT dispersive solution and dried. To determine the electrical properties of the impregnated specimen, a universal testing machine and multimeter were used to measure the resistance of the pressure change. Moreover, to examine the changes in the electrical properties of the sensor, its performance was evaluated by varying the concentration, number of penetrations, and thickness of the specimen. Samples that penetrated twice in the SWCNT distributed solution of 0.1 wt% showed the best performance as sensors. The 7-mm thick sensors showed the highest GF, and the 13-mm thick sensors showed the widest operating range. This study confirms the effectiveness of the simple process of fabricating smart textile sensors comprising 3D spacer fabrics and the excellent performance of the sensors.

• Journal of the Ergonomics Society of Korea
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• v.34 no.2
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• pp.191-198
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• 2015

Objective: As a cue for desired mood, we attempted to identify types of sitting postures when people are involved in various tasks during their working hours. Background: Physical behaviors in reaction to user contexts were studied, such as automated posture analysis for detecting a subject's emotion. Sitting postures have high feasibility and can be detected robustly with a sensing chair, especially when it comes to an office. Method: First, we attached seven sensors, including six pressure sensors and one distance sensor, to an office chair. In Part 1, we recorded participants' postures while they took part in four different tasks. From the seven sensors, we gathered five sets of data related to the head, the lumbar, the hip, thigh pressure and the distance between the backrest and the body. We classified them into four postures: leaning forward, upright, upright with the lumbar supporting, and leaning backward. In part 2, we requested the subjects to take suitable poses for the each of the four task types. In this way, we compared the matches between postures and tasks in a natural setting to those in a controlled situation. Results: We derived four types of sitting postures that were mapped onto the different tasks. The comparison yielded no statistical significance between Parts 1 and 2. In addition, there was a significant association between the task types and the posture types. Conclusion: The users' sitting postures were related to different types of tasks. This study demonstrates how human emotion can interact with lighting, as mediated through physical behavior. Application: We developed a posture-based lighting system that manipulates the quality of office lighting and is operated by changes in one's posture. Facilitated by this system, color temperatures ranging between 3,000K and 7,000K and illuminations ranging between 300lx and 700lx were modulated.

• Science of Emotion and Sensibility
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• v.8 no.3
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• pp.213-220
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• 2005

The purpose of this study is to develop a modular model of smart clothing which can integrate various digital devices in clothing, maintaining the inherent attribute of clothing. For achieving this purpose, several technological devices for the smart clothing for listening to music, bio-monitoring, and environment monitoring were developed, through multidisciplinary cooperation. As the result, total four design prototypes of smart sportswear(trekking wear, jogging wear) for the application of entertainment and health care were suggested.

• Science of Emotion and Sensibility
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• v.14 no.1
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• pp.137-146
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• 2011

The purpose of the present study was to investigate personality type with evoked potentials. Teenage students(121 males, 69 females) tested Myers Briggs Type Indicator and raven like discrimination task by evoked potential. Raven like discrimination tasks were made of low, medium and high levels. Conclusively extraversion and introversion while accomplishing the raven like discrimination tasks, showed the significant difference between two groups in the power of concentration. M-Beta(middle beta), Gamma and H-Beta(high beta) were also appeared significant differences between two groups. The sensing and intuition type partially appeared the different tendency of two groups while accomplishing easy and medium of difficulty tasks. Thinking and Feeling type while accomplishing raven like discrimination tasks, showed difference of the concentration power and H-Beta at Fp1. But judgment and perception type did not appear the difference between two groups while accomplishing raven like discrimination tasks of low, medium, and high. These results implied that the personality type can be affected brain wave by evoked potentials.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.157-163
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• 2014

User's sensitivity is recognized as a very important parameter for communication between company, government and personnel. Especially in many studies, researchers use voice tone, voice speed, facial expression, moving direction and speed of body, and gestures to recognize the sensitivity. Multiplex modality is more precise than single modality however it has limited recognition rate and overload of data processing according to multi-sensing also an excellent algorithm is needed to deduce the sensing value. That is as each modality has different concept and property, errors might be happened to convert the human sensibility to standard values. To deal with this matter, the sensibility expression modality is needed to be extracted using technologies like analyzing of relational network, understanding of context and digital filter from multiplex modality. In specific situation to recognize the sensibility if the priority modality and other surrounding modalities are processed to implicit values, a robust system can be composed in comparison to the consuming of computer resource. As a result of this paper, it is proposed how to assign the weight of multiplex modality using implicit data.

• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.149-160
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• 2023

This study develops a time-varying system-based noncontact fabric sensor that can measure cerebral blood-flow signals to explore the possibility of brain blood-signal detection and emotional evaluation. The textile sensor was implemented as a coil-type sensor by combining 30 silver threads of 40 deniers and then embroidering it with the computer machine. For the cerebral blood-flow measurement experiment, subjects were asked to attach a coil-type sensor to the carotid artery area, wear an electrocardiogram (ECG) electrode and a respiration (RSP) measurement belt. In addition, Doppler ultrasonography was performed using an ultrasonic diagnostic device to measure the speed of blood flow. The subject was asked to wear Meta Quest 2, measure the blood-flow change signal when viewing the manipulated image visual stimulus, and fill out an emotional-evaluation questionnaire. The measurement results show that the textile-sensor-measured signal also changes with a change in the blood-flow rate signal measured using the Doppler ultrasonography. These findings verify that the cerebral blood-flow signal can be measured using a coil-type textile sensor. In addition, the HRV extracted from ECG and PLL signals (textile sensor signals) are calculated and compared for emotional evaluation. The comparison results show that for the change in the ratio because of the activation of the sympathetic and parasympathetic nervous systems due to visual stimulation, the values calculated using the textile sensor and ECG signals tend to be similar. In conclusion, a the proposed time-varying system-based coil-type textile sensor can be used to study changes in the cerebral blood flow and monitor emotions.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.103-110
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• 2010

TPR(Total Physical Response) is a new representative learning method for children's education. Today's approach to TPR has focused on signals from a user which becomes input data in a human-computer interaction, but the accuracy of sensing from body signals(e. g. motion and voice) isn't so perfect that it seems difficult to apply on an education system. To overcome these limits, we suggest a mediating interface device which can detect the user's motion using correct numerical values such as acceleration and angular speed. In addition, we suggest new design requirements for the mediating device through analyzing children's behavior as human factors by ethnography research and protocol analysis. As a result, we found that; children are unskilled in physical control when they use objects; tend to lean on an object unconsciously with touch. Also their behaviors are restricted, when they use objects. Therefore a mediating device should satisfy new design requirements which are make up for unskilled handling, support familiar and natural physical activity.