Name
Abstract | ||
|---|---|---|
Although activity recognition has been studied for a long time now, research and applications have focused on physical activity recognition. Even if many application domains require the recognition of more complex activities, research on such activities has attracted less attention. One reason for this gap is the lack of datasets to evaluate and compare different methods. To promote research in such scenarios, we organized 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 used the CARE-COM Nurse Care Activity Dataset, featuring 7 activities performed by 8 subjects in a controlled environment with accelerometer sensors, motion capture and indoor location sensor. In this paper, we summarize the results of the competition.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3341162.3345577 | Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers |
Keywords | Field | DocType |
accelerometer, activity recognition, datasets, motion capture, nurse care | Nursing,Computer science,Care activity | Conference |
ISBN | Citations | PageRank |
978-4503-6869-8 | 0 | 0.34 |
References | Authors | |
0 | 11 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paula Lago | 1 | 3 | 4.76 |
| Sayeda Shamma Alia | 2 | 0 | 1.69 |
| Shingo Takeda | 3 | 0 | 1.35 |
| Tittaya Mairittha | 4 | 1 | 4.74 |
| Nattaya Mairittha | 5 | 2 | 4.77 |
| Farina Faiz | 6 | 0 | 0.34 |
| Yusuke Nishimura | 7 | 1 | 1.71 |
| Kohei Adachi | 8 | 1 | 1.69 |
| Tsuyoshi Okita | 9 | 53 | 13.37 |
| François Charpillet | 10 | 448 | 54.11 |
| Sozo Inoue | 11 | 176 | 58.17 |