The Transactions of The Korean Institute of Electrical Engineers
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v.64
no.6
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pp.940-947
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2015
A Sitting posture is a very important issue for moderns who is mostly sedentary. Also, a wrong sitting posture causes back-pain and spinal disease. Many researchers have been proposed numerous approaches that classifying and monitoring for a sitting posture. In this paper, we proposed a real-time sitting posture monitoring system that was developed to measure pressure distribution in the human body. The proposed system consists of a pressure sensing module (six pressure sensors), data acquisition and processing module, a communication module and a display module for an individual sitting posture monitoring. The developed monitoring system can classify into five sitting postures, such as a correct sitting, sitting on forward inclination, leaning back sitting, sitting with a right leg crossed and a left leg crossed. In addition, when a user deviates from the correct posture, an alarm function is activated. We selected two kinds of chairs, one is rigid material and fixed form, the other one is a soft material and can adjust the height of a chair. In the experiments, we observed appearance changes for subjects in consequence of a comparison between before the correction of posture and after the correction of posture when using the proposed system. The data from twenty four subjects has been classified with a proposed classifier, achieving an average accuracy of 83.85%, 94.56% when the rigid chair and the soft chair, respectively.
Journal of information and communication convergence engineering
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v.17
no.1
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pp.74-83
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2019
This study designs a squat posture recognition system that can provide correct squat posture guidelines. This system comprises two modules: a Kinect camera for monitoring users' body movements and a Wii Balance Board(WBB) for measuring balanced postures with legs. Squat posture recognition involves two states: "Stand" and "Squat." Further, each state is divided into two postures: correct and incorrect. The incorrect postures of the Stand and Squat states were classified into three and two different types of postures, respectively. The factors that determine whether a posture is incorrect or correct include the difference between shoulder width and ankle width, knee angle, and coordinate of center of pressure(CoP). An expert and 10 participants participated in experiments, and the three factors used to determine the posture were measured using both Kinect and WBB. The acquired data from each device show that the expert's posture is more stable than that of the subjects. This data was classified using a support vector machine (SVM) and $na{\ddot{i}}ve$ Bayes classifier. The classification results showed that the accuracy achieved using the SVM and $na{\ddot{i}}ve$ Bayes classifier was 95.61% and 81.82%, respectively. Therefore, the developed system that used Kinect and WBB could classify correct and incorrect postures with high accuracy. Unlike in other studies, we obtained the spatial coordinates using Kinect and measured the length of the body. The balance of the body was measured using CoP coordinates obtained from the WBB, and meaningful results were obtained from the measured values. Finally, the developed system can help people analyze the squat posture easily and conveniently anywhere and can help present correct squat posture guidelines. By using this system, users can easily analyze the squat posture in daily life and suggest safe and accurate postures.
Many reaearchers have reproted that poor body postures are associated with pains or symptoms of musculoskeletal dissoders. Therefore, the ergonomic evaluation of postural stresses as well as biomechanical stresses is important when a job such as automobile assembly tasks involves highly repetitive and/or prolonged poor body postures. A macropostural classification shema was developed to characterise various body postures occurring in automobile assembly tasks in the study. To specify a postural code and stress level to each body posture, perceived joint discomforts were subjectively evaluated in the lab experiments for the full range of motion in five human body joints. Based on the reaults, a postural classification scheme was developed where the full range of motion in each body joint was classified into several codes repressenting different stress levels. The automobile tasks were clustered into 12 types based on the result walk-in-surveillance and the possible posture codes for each task type are defined. I was exposed that the poor postural problems in automobile assembly tasks were concerned in most part with arms, trunk and neck. Application of te developed schema to seven operations in automobile assembly tasks showed that the schema can be used as a tool to identify the operations and tasks involving highly stressful body postures. The schema can also be utilised as a basis to prioritise the candidate assembly operations for redesign of work methods.
This study aims to investigate effect of external load and motion repetitiveness on perceived discomfort. An experiment was performed for measuring discomfort scores at varying conditions, in which external load, motion repetitiveness and arm posture were employed as experimental variables. The arm posture was controlled by shoulder flexion and abduction, and by elbow flexion. Fifteen healthy college-age students without history of musculoskeletal disorders voluntarily participated in the experiment. The results showed that the effect of external load, motion repetitiveness and shoulder posture on discomfort were statistically significant, but that elbow posture did not significantly affect discomfort ratings. The effect of external load was much larger than that of any other variables, and that of repetitiveness was second only to external load. Discomfort scores significantly increased linearly as the levels of external load and motion repetitiveness increased. This implies that although they were not fully reflected in the existing posture classification scheme such as OWAS, RULA, etc., the effect of external load and motion repetitiveness should be taken into consideration for precisely quantifying work load in industry. Based on regression analysis, equivalent values of external load and motion repetitiveness in terms of discomfort scores were provided, which would be useful for better understanding the degree of their effect on work load.
Recently, screen climbing contents such as sports climbing learning program and screen climbing games. Especially, there are many researches on screen climbing games. In this paper, we propose the skeleton correction method based on the body area of a climber to improve the posture recognition accuracy. The correction method consists of the modified skeletal frame normalization with abnormal skeleton joint filtering, the classification of body area into joint parts, and the final skeleton joint correction. The skeletal information obtained by the proposed method can be used to compare the climber's posture and the ideal climbing posture.
Journal of the Korea Society of Computer and Information
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v.26
no.6
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pp.129-135
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2021
The purpose of this study was to investigate the relationship of the head posture with the tone and stiffness of the cervical extensor muscles. Eighty adults in their twenties were chosen as subjects, and the tone and stiffness of the cervical extensor muscles were measured, with their usual head posture in the sagittal plane. For the measured head posture, the craniovertebral angle (CVA), craniorotation angle (CRA), and forward shoulder angle (FSA) were analyzed using Image J. It was observed that the tone and stiffness of the upper trapezius muscle increased significantly with a decrease in the CVA as well as with an increase in the CRA (p < 0.05). As a result of further classification into the normal and forward head postures based on the CVA of the subjects, the forward head posture was characterized by a significant increase in the tone and stiffness of the upper trapezius muscle (p<.05). The results of this study are expected to be used as basic data for the evaluation of the forward head posture and posture education in clinical practice.
In this paper, a problem of Thai sign language recognition using a neural network is considered. The paper addresses the problem in classifying certain signs conveying quantitative meaning, e.g., large or small. By treating those signs corresponding to different quantities as derived from different classes, the recognition error rate of the standard multi-layer Perceptron increases if the precision in recognizing different quantities is increased. This is due the fact that, to increase the quantitative recognition precision of those signs, the number of (increasingly similar) classes must also be increased. This leads to an increase in false classification. The problem is due to misinterpreting the amount of quantity the quantitative signs convey. In this paper, instead of treating those signs conveying quantitative attribute of the same quantity type (such as 'size' or 'amount') as derived from different classes, here they are considered instances of the same class. Those signs of the same quantity type are then further divided into different subclasses according to the level of quantity each sign is associated with. By using this two-level classification, false classification among main gesture classes is made independent to the level of precision needed in recognizing different quantitative levels. Moreover, precision of quantitative level classification can be made higher during the recognition phase, as compared to that used in the training phase. A standard multi-layer Perceptron with a back propagation learning algorithm was adapted in the study to implement this two-level classification of quantitative gesture signs. Experimental results obtained using an electronic glove measurement of hand postures are included.
Somatotype is human body shape and physique type which can be classified not only by the size, but also by the shape or posture of the body. Postural variations in the alignment of the back, shoulder, and neck can have an adverse effect on the fit of garments designed to hang from the shoulders. There have been some previous studies about the lateral upper torso by analyzing photographic measurements. In this study, 3D body scan images were used to classify the side somatotype of upper lateral method even though they are major data in the classification of upper torso. This study focused on following objective.; 1) To apply new and developing technology into the apparel industry analyzing 3D body scan images. 2) To classify upper laterla torso using the data through the new improver technology, 3D body scanner. 3) To propose basic materials for well fitted garments for each type of figure. The test subjects for this study were two hundreds nine female aged 19 years and up who were recruited in Cornell university body scan research team. Seventeen Variables(12 angles, 5 lengths) out of 3D body scan data were measured based on these landmarks and applied to analyze. The result of factor analysis indicated that 6 factors were extracted through factor analysis and orthogonal rotation by the method of Varimax and those factors comprise 62.5% of total variance. And the somatotype of upper body is classified into 3 types of figures according to cluster analysis; Bent forward posture, Straight posture, Swayback posture. Future study could be addressed about the somatotype of body by the age group based on the large database with wide variety of age.
Park, Jangwoon;Choi, Younggeun;Lee, Baekhee;Jung, Kihyo;Sah, Sungjin;You, Heecheon
Journal of the Ergonomics Society of Korea
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v.33
no.2
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pp.87-96
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2014
Objective: The present study is intended to objectively classify upper- & lower-body sitting strategies and identify the effects of gender and OPL type on the sitting strategies. Background: A sitting strategy which statistically represents comfortable driving posture can be used as a reference posture of a humanoid in virtual design and evaluation of a driver's seat. Although previous research has classified sitting strategies for driving postures in various occupant package layout (OPL) types, the existing classification methods are not objective and the factors affecting sitting strategies have not been identified. Method: Forty drivers' preferred driving postures in three different OPL types (coupe, sedan, and SUV) were measured by a motion capture system. Next, the measured driving postures were classified by K-means cluster method. Results: Sitting strategies of upper-body were classified as erect (33%), slouched (41%), and reclined (26%) postures, and those of lower-body were classified as knee bent (42%), knee extended (32%), and upper-leg lifted (26%) postures. Significant differences at ${\alpha}$ = 0.05 in the upper-body sitting strategy by gender and lower-body sitting strategy by OPL type were found. Application: Both the classified sitting strategies and the identified factors would be of use in ergonomic seat design and evaluation.
This study was performed to investigate the clinical features of internal derangement of temporomandibular joint. For this study, 117 patients with temporomandibular disorders and 81 dental students without any signs and symptoms of temporomandibular disorders were selected as the patients group and as the control group, respectively. Preferred chewing side, Angle's classification, lateral guidance pattern, maximal mouth opening range, and affected side were recorded clinically. Head and shouldeer posture was measured in a groundplate on which square diagram of five centimeters each had been drawn, and cephalograph was also taken for measurement of head and neck posture. Sonopak of Biopak system (Bioresearch inc., USA) was used to record joint vibration for evaluation of internal healthy status of temporomandibular joint. The data collected were analyzed by SAS statistical program. The results of this study were as follows : 1. Frequency of left side chewing subjects was higher in patients than in control group, but there was no difference in distribution of subjects by Angle's classification. Other types was prvalent in patients whereas group function was more in control group for lateral guidance pattern. 2. As to lateral guidance pattern by clinical diagnosis, patients with internal derangement and/or degenerative joint disease showed higher frequency was consistent with the result by Sonopak impression. 3. There was no difference for shoulder height between the two groups, however, tilting of head and backward extension of cervical spine was more frequent in control group. 4. Acromion was positioned more anteriorly in patients with internal derangement and/or degenerative joint disease than in control group and angle between eye and tragus was larger in patients. Patients with degenerative joint disease showed more flexed head posture than control group did in cephalometric profile. 5. Maximal mouth opening range in patients with internal derangement was the least in all subgroups in patients classified by Sonopak impression.
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