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Titlebook: Symbiotic Interaction; 4th International Wo Benjamin Blankertz,Giulio Jacucci,Jonathan Freeman Conference proceedings 2015 Springer Interna

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31#
發(fā)表于 2025-3-27 00:32:19 | 只看該作者
A Closed-Loop Perspective on Symbiotic Human-Computer Interaction,nd behaviour of the user. The current relationship between people and computer is characterised as asymmetrical and static. The closed-loop dynamic of physiological computing systems is used as an example of a symmetrical and symbiotic HCI, where the central nervous system of the user and an adaptiv
32#
發(fā)表于 2025-3-27 02:33:48 | 只看該作者
Developing a Symbiotic System for Scientific Information Seeking: The MindSee Project,dopt a query-based information-seeking paradigm. Our approach is to use a symbiotic system paradigm, exploiting central and peripheral physiological data along with eye-tracking data to adapt to users’ ongoing subjective relevance and satisfaction with search results. The system described, along wit
33#
發(fā)表于 2025-3-27 08:11:00 | 只看該作者
34#
發(fā)表于 2025-3-27 10:23:35 | 只看該作者
Applying Psychology Research to Shopper Mindsets with Implications for Future Symbiotic Search Systderstanding people’s behaviours, thoughts and emotions to different messages in different contexts at different times, can inform the strategic planning and design of systems promoting positive customer experiences and increasing retail sales. Using theory combined with applied insights from our pro
35#
發(fā)表于 2025-3-27 16:14:36 | 只看該作者
36#
發(fā)表于 2025-3-27 20:58:20 | 只看該作者
37#
發(fā)表于 2025-3-27 23:14:58 | 只看該作者
38#
發(fā)表于 2025-3-28 05:31:44 | 只看該作者
39#
發(fā)表于 2025-3-28 09:40:32 | 只看該作者
,Brain–Robot Interfaces Using Spatial Tactile BCI Paradigms,e to utilize two previously developed by our team stimulus driven BCI paradigms, which are based on tactile pin pressure and full body vibrotactile modalities. The user intentions are decoded from the brainwaves in real time and translated to a symbiotic humanoid robot NAO navigation. A communicatio
40#
發(fā)表于 2025-3-28 12:03:10 | 只看該作者
Joint Stiffness Tuning of Exoskeleton Robot H2 by Tacit Learning,iffness tuning algorithm using the bio-mimetic learning method called tacit learning. We experimentally showed that the proposed controller can tune the joint stiffness of the exoskeleton robot by tuning the integral gain in the controller. The walking experiment wearing the exoskeleton robot sugges
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