Paper Info
Title
Phase recognition during surgical procedures using embedded and body-worn sensors
Abstract
In Ubiquitous Computing (Ubicomp) research, substantial work has been directed towards sensor-based detection and recognition of human activity. This research has, however, mainly been focused on activities of daily living of a single person. This paper presents a sensor platform and a machine learning approach to sense and detect phases of a surgical operation. Automatic detection of the progress of work inside an operating room has several important applications, including coordination, patient safety, and context-aware information retrieval. We verify the platform during a surgical simulation. Recognition of the main phases of an operation was done with a high degree of accuracy. Through further analysis, we were able to reveal which sensors provide the most significant input. This can be used in subsequent design of systems for use during real surgeries.
Year
DOI
Venue
2011
10.1109/PERCOM.2011.5767594
PerCom
Keywords
Field
DocType
context-aware information retrieval,high degree,automatic detection,phase recognition,surgical procedure,surgical simulation,substantial work,sensor-based detection,sensor platform,body-worn sensor,daily living,ubiquitous computing,surgical operation,intelligent sensors,machine learning,ventilation,sensor fusion,pattern recognition,learning artificial intelligence,radiofrequency,surgery,anesthesia,sensors,activity recognition,activity of daily living
Computer vision,Activity recognition,Patient safety,Intelligent sensor,Computer science,Sensor fusion,Real-time computing,Artificial intelligence,Ubiquitous computing,Distributed computing
Conference
ISSN
Citations 
PageRank 
2474-2503
27
1.02
References 
Authors
22
6
Name
Order
Citations
PageRank
Jakob E. Bardram12136174.84
Afsaneh Doryab220114.09
Rune M. Jensen31749.27
Poul M. Lange4271.02
Kristian L. G. Nielsen5271.02
Soren T. Petersen6271.02