• Physical Therapy Rehabilitation Science
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• v.5 no.3
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• pp.155-161
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• 2016

Objective: This study aimed to investigate the reliability and validity of a personal computer-based muscle viewer (PC-BMW) compared with that of a portable ultrasound (P-US) for measuring upper trapezius (UT) and transversus abdominis (TrA) muscle thickness at rest and during contraction. Design: Observational inter-rater reliability study. Methods: Fifty-five healthy participants (25 men, 30 women) participated in this study. PC-BMW and P-US were randomly measured at the UT and TrA muscles. Two examiners randomly obtained the images of all participants in 3 test sessions lasting 2 days. Intra-class correlation coefficients (ICCs), standard error of measurement, contraction ratio, and correlation were used to estimate reliability and validity. Pearson's correlation coefficients were used to analyze the relationship between muscle thickness measures taken from PC-BMW and P-US. Results: The intra-rater reliability ICCs of UT and TrA muscle thickness for the PC-BMW were >0.995, indicating excellent reliability. Inter-rater reliability ICCs for the PC-BMW ranged from 0.963 to 0.987. The P-US also exhibited high reliability. A high correlation was found between the measurements of the two muscles in PC-BMW and P-US (p<0.01). Conclusions: PC-BMW provides clear and excellent images, is pocket-sized and less expensive than a conventional ultrasound imaging system. PC-BMW can be utilized variously and has the advantage of rehabilitative ultrasound imaging. More research is needed to evaluate the utility of PC-BMW for rehabilitation.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.2
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• pp.87-92
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• 2006

This paper supplements shortcoming of radioactivity check by detecting defect of SWP weld zone using ultrasonic wave. Manufacture 2 stage robot detection systems that can follow weld bead of SWP by method to detect weld defects of SWP that shape of weld bead is complex for this as quantitative. Also, through signal processing ultrasonic wave defect signal system of GUI environment that can grasp easily existence availability of defect because do videotex compose. Ultrasonic wave signal of weld defects develops artificial intelligence style sightseeing system to enhance pattern recognition of weld defects and the classification rate using neural net. Classification of weld defects that do fan Planar defect and that do volume defect of by classify.