Citation: Communication Papers of the 2018 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 17, pages 3–10 (2018)
Abstract. In this research, we propose a method using vital signs, to estimate changes of the intimacy inside a team from interactions of team members in the same space. The method estimates both intimacy change between two members and that among whole members. The method facilitates team leaders to grasp the relationships and improve the team performance. Since various measurements representing features of the pulse wave are known to reflect personal emotion, we can expect to estimate the change of intimacy, providing the measurements with a machine learning algorithm. An experiment evaluating the proposed method showed high accuracy in the estimation among whole team members, but low accuracy in the estimation between two members. In both cases, the accuracy can be improved by choice of effective measurements. Through this experiment, we have found it is necessary to decide the effective measurements for each team to construct a model to estimate intimacy inside the team.
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