SUMMARYFrequently interrupting someone who is busy will decrease his or her productivity. To minimize this risk, a number of interruptibility estimation methods based on PC activity such as typing or mouse clicks have been developed. However, these estimation methods do not take account of the effect of conversations in relation to the interruptibility of office workers engaged in intellectual activities such as scientific research. This study proposes an interruptibility estimation method that takes account of the conversation status. Two conversation indices, "In conversation" and "End of conversation" were used in a method that we developed based on our analysis of 50 hours worth of recorded activity. Experiments, using the conversation status as judged by the Wizard-of-OZ method, demonstrated that the estimation accuracy can be improved by the two indices. Furthermore, an automatic conversation status recognition system was developed to replace the Wizard-of-OZ procedure. The results of using it for interruptibility estimation suggest the effectiveness of the automatically recognized conversation status.

Frequent and uncontrolled interruptions by information systems that do not reflect the user's state can result in fragmented working times and decreased intellectual productivity. To avoid adverse interruptions, interruptibility estimation methods based on PC operation information have been proposed. However, workers who use PCs to accomplish their primary tasks occasionally engage in paperwork. Occasional paperwork activities, which are not reflected in the PC's operation information, can cause estimation errors. This study focuses on using the position of the head, posture, temporal motion, and continuity of the head position and posture while a worker is at his or her desk as indices to reflect engagement in the task at hand. Based on an analysis of the relationship between the head-related parameters and interruptibility, an interruptibility estimation algorithm is proposed using four head-related indices that reflect interruptibility during PC and non-PC work. Experiments indicate that estimation accuracy improves as a result of incorporating these indices in the algorithm.

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The chances of being interrupted by online communication systems, such as email, instant messenger, and micro-blog, are rapidly increasing. For the adequate control of interruption timing, the real-time estimation of the interruptibility of the user is required. In this study, we propose an interruptibility estimation method using PC activity and conversational voice detection based on the wavelet transform. The offline estimation was applied to a dataset of 50 hours obtained from 10 users. The results indicated the feasibility of improving the interruptibility estimation accuracy by the automatic detection of the existence and end of conversations.

To relieve the cognitive impact of interruptions caused by email delivery notifications, we propose an automatic email delivery mediation system based on the user interruptibility, which is estimated from the PC operation activity. A prototype system has been developed to be compatible with existing email clients and to deliver emails at higher estimated interruptibility times, especially at application switching moments that are considered as breakpoints in PC tasks. Trial use by eight participants in ordinary working environments suggested that email notifications were delivered at moments with lower levels of operation activity and the feelings of hindrance were decreased. Further study is to be conducted to investigate the effect of automatic email delivery mediation on the cognitive cost and work efficiency.