Open Lab Nursing Activity Recognition Challenge

Paula Lago, Shingo Takeda, Sayeda Shamma Alia, Tittaya Mairittha, Nattaya Mairittha, Sozo Inoue,
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Although activity recognition has been studied for a long time now, research and applications have been mainly focused on physical activity recognition. Even if many application domains require the recognition of more complex activities, for example daily living activities or work-related activities, research on such activities has attracted less attention. One reason for the gap in research for complex activities is the lack of datasets to evaluate and compare different methods. To promote research in such scenarios, we will organize the Open Lab Nursing Activity Recognition Challenge focusing on the recognition of complex activities related to the nursing domain. Nursing domain is one of the domains that can benefit enormously from activity recognition but has not been researched due to lack of datasets. The competition will use the Open Lab Nursing Activities Dataset, featuring 7 activities performed by 8 subjects in a controlled environment with accelerometer sensors, motion capture and in-door location sensor. The dataset was collected at the Smart Life Care Society Creation Unit in Kyutech, Japan, based on the collaboration between Kyutech and Carecom. Co., Ltd. In this paper, we describe the data collection experiments and the dataset.

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