No abstract

This paper proposes a new brain-computer interface (BCI) design using fuzzy ARTMAP (FA) neural network, as well as an application of the design. The objective of this BCI-FA design is to classify the best three of the five available mental tasks for each subject using power spectral density (PSD) values of electroencephalogram (EEG) signals. These PSD values are extracted using the Wiener-Khinchine and autoregressive methods. Ten experiments employing different triplets of mental tasks are studied for each subject. The findings show that the average BCI-FA outputs for four subjects gave less than 6% of error using the best triplets of mental tasks identified from the classification performances of FA. This implies that the BCI-FA can be successfully used with a tri-state switching device. As an application, a proposed tri-state Morse code scheme could be utilized to translate the outputs of this BCI-FA design into English letters. In this scheme, the three BCI-FA outputs correspond to a dot and a dash, which are the two basic Morse code alphabets and a space to denote the end (or beginning) of a dot or a dash. The construction of English letters using this tri-state Morse code scheme is determined only by the sequence of mental tasks and is independent of the time duration of each mental task. This is especially useful for constructing letters that are represented as multiple dots or dashes. This combination of BCI-FA design and the tri-state Morse code scheme could be developed as a communication system for paralyzed patients.

This paper presents a useful tactile display method that can control multiple tactile sensations such as roughness, pressure, and friction sensations using simple vibratory stimulations. Our concepts are based on two points: frequency range selection for making selective stimulation on different tactile receptors types and timing control of the stimulation in response to hand movements. The selective stimulations were realized by selecting reactive frequencies of vibratory stimulation based on temporal response characteristics of tactile receptors. For representing roughness sensation, vibrating frequencies were modulated in response to hand velocity considered as a temporal coding perception of FA I type receptor. Two reactive frequencies were also selected for representing pressure sensation and friction sensation corresponding to SA I and FA II type receptors respectively. A wearable tactile display using ICPF (Ionic Conducting Polymer gel Film) actuators verified our proposed methods. Finally, we conducted a total texture feeling display combined with our methods for roughness, pressure, and friction sensations in a parameterized manner. Comparison with real clothes showed that some combinations of multiple tactile sensations could express texture feels of the expected materials.

This paper reparts our novel approach to developing a social robot The developed robot is able to identify relationships among humans from their physicnl behaviors as it establishes long-term relationships with humans. This interactive humanoid robot attracts humans to interact with it and, PS B result, induces them to perform their group behaviors io front of it. The robot recognizes friendly relationships among humans by simultaneously identifying each person io the Interacting group. We conducted a two-month experiment in an elementary school. As a result, the robot snecessfully continued friendly interaction with many children for the two months, and demonstrated ressonable performance in identifying friendships among children. We believe this a b l t y to maintain friendly relationships with humans and to identify human relationships is essential to behaving socially. Key"-human-robot interclctiontfield m'al; friendhisp estimation; long-rem interaction;I. INTRODUCTTON Recent progress in robotics has brought with it a new research direction known as "interaction-oriented robots," which are designed to communicate with humans and to be able to participate in buman society. We are trying to develop such an interaction-oriented robot that can function as a p m e r in ow daily lives. As well as providing physical support, these robots will supply communication support such as route-guidance.Several researchers are endeavoring to realize such interaction-oriented robots. Aibo was the first interactive robot to prove successful on the commercial market [I], since it behaves as if it were a real animal pet. Breazeal and her colleagues developed the face robot Kismet, and they are exploring the sociable aspects of robots produced throngh its learning ability [2]. Okuno and his colleagues developed a humanoid head that tracks a speaking person with visual and auditory data. In addition, they controlled the personality of the robot by changing the tracking parameter [3]. Bwgard and his colleagues developed a museum tour guide robot [4] that was equipped with robust navigational skills and behaved as a museum orientation twl. These research efforts also seem to he devoted to "social robots" that are embedded in human society.Humans have the natural ability to identify others' intentions, which is widely known as the joint-attention mechanism in developmental psychology [SI. We believe that this is an essential function of being social for both humans and robots to be social. Scassellati developed a This research was supported by the National lastiMe oflnfomtion and Communications T~hnology af Japan 0-7803-S4634/04620.00 02004 IEEE 2215robot with a joint-attention mechanism that follows others' gazes in order to share attention [6]. Kozima and his colleagues also developed a robot with a joint-attention mechanism [7]. In these systems, the robots identify humans' intentions from their behaviors. Furthermore, a robot system can estimate a human's subjective evaluation of the robot hy observing hisher body movements [SI...

No abstract