Sensor networking is key technology to emerge ubiquitous information supporting environment. This paper developed armrest-mounted electrocardiograph, one of unconstrained biological sensors, key devices for ubiquitous health monitoring. As such unconstrained biological sensors require filtering noise caused by unexpected actions of targeting person, as the person monitored unconsciously can perform any activities. This paper introduced simple signal-based algorithm to detect noise caused by typing. The result indicates the introduced criterion can mask irregular noise to harm R-R interval measurement appropriately. Although the introduced simple method works properly, the filter may filter irregular signal caused by health trouble. To increase reliability of detection, additional context detection criteria from other information sources should be introduced.

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In this study, we developed "Haptic Canvas" which enables users to blend, draw and feel haptic sensations. Especially, we used the haptic device which controls the dilatant fluid to present unique haptic sensation according to the viscosity and stiffness of the fluid. Users wear the haptic glove which consists of the filters of the starch particle and sucking or ejecting components and have experience of the haptic interaction within the shallow pool filled with the dilatant fluid. The generating and blending interaction of the haptic sensation was achieved by introducing the haptic primary colors, including "stickiness", "hardness" and "roughness" sensations.