Category Archives: Research

Pseudo-haptic feedback on softness:柔らかさの錯触覚に関する研究

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In most of the research on pseudo-haptic feedback, subjects’ hands are on the desk and the visual image is provided from a monitor placed in front of them. The setup easily induces sensory conflicts for pseudo-haptic feedback between visual and haptic perception. However, subjects rarely see simultaneously their hand in motion and in a visual display. We report here our preliminary study on pseudo-haptic feedback related to tactile perception of softness. In the study, subjects hold a hand-held display with pressure sensors. A virtual object shown on the display screen changes shape according to pressures from the subject’s squeezing of the device. In this configuration, subjects are able to see

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SITA(A tongue training system and its application):舌運動検出とその福祉応用

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Children with Down syndrome have a variety of symptoms including speech and swallowing disorders. To improve these symptoms, tongue training is thought to be beneficial. However, inducing children with Down syndrome to do such training is not easy because tongue training can be an unpleasant experience for children. In addition, with no supporting technology for such training, teachers and families around such children must make efforts to induce them to undergo the training. In this research, we develop an interactive tongue training system especially for children with Down syndrome using SITA (Simple Interface for Tongue motion Acquisition) system. In this paper, we describe in detail our preliminary evaluations of SITA,

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MMG-based Gesture Recognition:筋肉の振動を利用したジェスチャ検出手法

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We propose a novel hand gesture recognition method based on MMG (mechanomyogram). Skeletal muscles generate sounds specific to their activity. MMG is the technology to evaluate muscles’ activity by recording and analyzing those sounds. In previous researches, microphones and accelerometers are often used to sense the sounds of muscles. However those sensors are easily obstructed by environmental condition such as acoustic noise and human motion itself. In this paper, we propose to use a piezo-based MMG to improve robustness to environmental condition. The preliminary evaluation shows that the proposed method is able to classify several hand gestures correctly at high accuracy at a certain situation. 我々は，MMGを用いた新たなジェスチャ認識手法を提案する．MMGとは，筋繊維の収縮に伴って発生する微細な振動や機械的な変位を皮膚表面上にて記録したもので，加速度センサやマイクロフォンで観測される．電気的な活動を記録したEMGと比べて，MMGは筋繊維の機械的な側面を反映するとされる．筋肉の機械的な活動とはつまり身体運動であり，ゆえにMMGの検出・認識は身体運動の推定につながると期待される．そこで我々は，MMGによってジェスチャ認識が行えるのではないかと考えた．従って本研究の目的は，MMGによって筋活動推定を行い，ジェスチャ認識へと応用することにある．本稿ではMMGの検出方法と，その解析のために行った実験結果を報告する． Publications: Shumpei Yamakawa, Takuya

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Vection field:ベクション場による歩行誘導手法

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  Along public pathways, visual signs and audio cues are used by pedestrians to guide them into forming smoother pedestrian flows. However, often ignored or neglected, these signals require greater pedestrian attentiveness and appropriate conscious effort. To solve this problem, we have proposed the concept of “vection field”. This is a field of optical flow that cues movement according to a pedestrian’s motion. Visual stimulus within this optical flow leads pedestrians innately in specific directions without requiring direct interventions. We have implemented such a field by covering the ground with a lenticular lens screen; in this setup, neither power supply nor position tracking of pedestrians is necessary. An experimental result from

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Ego-motion analysis:運動計測システムの開発

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In this paper, we present a new method to perform ego-motion analysis using intensity averaging of image data. The method can estimate general motions from two sequential images on pixel plane by calculating cross correlations. With distance information between camera and objects, this method also enables estimates of camera motion. This method is sufficiently robust even for out of focus image and the calculational overhead is quite low because it uses a simple averaging method. In the future, this method could be used to measure fast motions such as human head tracking, or robot movement. We present a detailed description of the proposed method, and experimental results demonstrating its basic

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