Research into thinking-support tools is commonly focused on how to develop and share ideas between participants or with others. In this paper, we propose and develop a communication system that stimulates the thought processes and inspires the creative ideas of participants by using a visual "" prompt within the framework of a communication pallet. Experiments have been conducted into methods of stimulating the thought process and inspiring ideas during conversation and the results have been analyzed. From the results, a tendency towards inspiring creative ideas by participants has been observed.

To uncover human‐system mismatches in system operation, a methodology is proposed for the analysis and classification of operators’ opinions about operation problems and their demands for system improvements. Previous methodologies had several limitations for dealing with human‐related accident reports, that is, human error data. To be able to process operators’ opinions, a clustering method, “the modified affinity diagram,” is used to analyze opinions. Clustered opinions are classified into eight categories based on Rasmussen's qualitative model of human behavior. The proposed methodology has several advantages because it uses the operators’ opinions as data—data that can be collected at any time even in the absence of reported accidents. These data are intended to include information related to human‐system mismatch situations. The methodology prevents unconscious or deliberate bias from influencing data collection. An application of the methodology to the analysis of network systems is presented. The proposed methodology is useful to clarify the subjective human‐system mismatch areas in terms of human behavior in system operation.

People faced with an unfamiliar product or service tend to fall back on mental models based on analogical relationships with familiar products or services. Two experiments on the analogical relationships or metaphors that people might use when operating a communications terminal are described. In the first experiment, the role previously acquired operating knowledge has in determining the mental models people use when directory dialing with novel equipment is examined. In a second experiment, it is shown that an explicit appeal to an analogy between conventional mail and electronic mail can help users learn to use an electronic mail system, and make it easier for them to remember how to use the system as long as 90 days after initial exposure. It is concluded that the mental model is constructed only from the user's operating knowledge acquired as a result of past experiences, and the metaphor method is effective when the instructions are metaphorically taught.>

It is proposed that electromyographic (EMG) patterns can be analyzed and classified by neural networks for EMG-controlled prosthetic members. The thrust of this work is that neural networks make EMG pattern recognition much easier and more efficient; thus, use of EMG control in a prosthetic arm/hand would involve much less physical and mental effort on the part of the subject. The FFT-analyzed pattern for a one-channel surface EMG of the flexor digitorium superficialis can be recognized by the standard back-propagation neural network. Classification of the five finger movements based on the recognition of their patterns is successfully accomplished.>

It is proposed that neural networks can be used to recognize electroencephalographic (EEG) information and so create a new man-machine interface for data input. Existing interfaces require the user to express the data, i.e. the user thinks of a datum and then has to perform either a mechanical action (keypress) or a vocal act. It is shown that just prior to the act of expressing a datum the readiness potential (RP) of the user's brain contains some information about the datum. A simple test was conducted in which the RPs of one subject were analyzed. For five Japanese syllables, high recognition rates were obtained from a trained neural network.>