Management of Behavioral and Psychological Symptoms of Dementia (BPSD) is a key challenge in geriatric dementia care. A multimodal comprehensive care methodology, Humanitude, with eye contact, verbal communication, and touch as its elements, was provided to three geriatric dementia patients for whom conventional nursing care failed in an acute care hospital. Each episode was evaluated by video analysis. All patients had advanced dementia with BPSD. Failure of care was identified by patient's shouting, screaming, or abrupt movements of limbs. In this case series, conventional care failed for all three patients. Each element of care communication was much shorter than in Humanitude care, which was accepted by the patients. The average of the elements performed during the care was eye contact 0.6%, verbal communication 15.7%, and touch 0.1% in conventional care and 12.5%, 54.8%, and 44.5% in Humanitude care, respectively. The duration of aggressive behavior of each patient during care was 25.0%, 25.4%, and 66.3% in conventional care and 0%, 0%, and 0.3% in Humanitude, respectively. In our case series, conventional care was provided by less eye contact, verbal communication, and touch. The multimodal comprehensive care approach, Humanitude, decreased BPSD and showed success by patients' acceptance of care.

The purpose of this paper is to describe the way to represent the skills in dementia care based on the multimodal communication analysis by a computational approach. With the rapid growth of an aging population, it is becoming extremely important to elucidate communication skills for improving the quality of life of the elderly. Focusing on the dementia care method by HUMANITUDE, we have analyzed dementia care skills to evaluate their effectiveness. We designed three layers for representing skills and named them "Intra-modality," "Inter-modality" and "Multimodal-interaction." These results are a part of the findings of empirical analysis of building human relationships.

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Supporting deaf and hard of hearing (D/HH) people to understand natural conversation is one of the important activities of social welfare. However, currently the communication support for D/HH people is not enough in Japan. Although existing communication methods, such as sign language and lipreading, are effective in one-to-one conversation, they have several disadvantages in one-to-many conversation such as meetings or conventions. In order to support D/HH people in understanding conversation, this paper proposes a multi-modal visualization application which provides many aspects of information about speech contents. Concrete examples of visualization modes include displaying subtitles by voice recognition and showing speaker's mouth to assist lip-reading.