The copolymerization of ethylene and substituted styrenes [RSt's; p-methylstyrene (MSt), p-tertbutylstyrene (BSt), 2-vinylnaphthalene (VN), and p-(tertbutyldimethylsilyloxy)styrene (BMSiOSt)] were investigated with dimethylsilylene(tetramethylcyclopentadienyl)(N-tert-butyl) titanium dichloride to yield the corresponding ethylene-RSt copolymers. The substituent on the styrene (St) monomers did not affect the monomer reactivity ratio. The effect of the substituent structure of RSt on the thermal and mechanical properties was studied with differential scanning calorimetry, dynamic mechanical thermal spectroscopy, and elongation testing. The glass-transition temperature (T g ) of the copolymers increased with increasing RSt content, and the order of T g was as follows: BSt > VN > MSt ¼ St. A copolymer with p-hydroxystyrene (HOSt) was successively synthesized by means of deprotection of the copolymer with BMSiOSt. The copolymer showed a much higher T g than the other copolymers because of the hydrogen connection of its OH groups. The mechanical properties of the copolymer in the glass state, at a lower temperature than T g , were almost independent of the nature of the RSt. The substituent of the St monomers affected the pattern of the stress-strain curve in the elongation testing in the amorphous state. An improvement in the shape memory effect was observed in poly(ethylene-co-BSt).

SEMG(Surface Electromyogram) is one of the bio-electric signals that is generated from the muscle. There are many kinds of muscles in a human body, and used muscles are different for each body movement. Therefore, any kind of body motions can be detected by analyzing generated SEMG patterns. Our objectives of this study are the development of a method that makes perfect detection of the hand motions possible using SEMG patterns and applying the method to the man-machine interface. In this paper, four channels SEMG signals which were measured from a right forearm of the subject were used to detect right hand motions. And a radio controlled vehicle was controlled as the results of detecting hand motions.In our system, suitable electrode positions are selected from analyzing results of 48 multi-channel SEMG patterns for each subject. Measured SEMG signals from electrodes are amplified, filtered and analog to digital converted. Digitized SEMG data are analyzed in a personal computer. The hand motion detection is done using the method of canonical discriminate analysis. In this study, five basic hand movements (wrist flexion, wrist extension, grasp, pronation, supination) were detected and used to control a vehicle. Three subjects were studied with our system. They were male and had not used our system before experiment. After few minutes training, they tried to control a radio controlled vehicle. In spite of first operation, they could control a vehicle almost perfectly and average recognition rate of hand movements were more than 90% for all subjects. From these results of our experiment, we have concluded that our new man-machine interface worked perfect and will be a valuable interface in future.

SEMG has many benefits. For example, measurement of SEMG is easy and non-invasive, and especially a characteristic pattern of SEMG is obtained for each body movement. In this research, our objective is the development of a new man-machine interface that is able to control carious equipments by using a characteristic pattern of forearm SEMG. In this paper, we will describe about our developed interface that is controlled by forearm SEMG.

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： SEMG ( Surface Electromyogram )has many benefits ， for example ， measurement of SEMG is easy and a characteristie pattern of SEMG is obtained f(｝r each different movement ． in this research ， it aims at the development of a new interface to be able to control various equipment by using a characteristic pattern of SEMG ln this paper， we will talk about our developed control system that works as diverse equipment ．