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.

Keywords:
Activity recognition Computer science Domain (mathematical analysis) Accelerometer Human–computer interaction Nursing care Competition (biology) Artificial intelligence Nursing Medicine

Metrics

40
Cited By
2.78
FWCI (Field Weighted Citation Impact)
13
Refs
0.92
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Context-Aware Activity Recognition Systems
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Technology Use by Older Adults
Social Sciences →  Social Sciences →  Demography
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