Human activity recognition in pervasive health-care: Supporting efficient remote collaboration

被引:71
作者
Osmani, Venet [1 ]
Balasubramaniam, Sasitharan [1 ]
Botvich, Dmitri [1 ]
机构
[1] Waterford Inst Technol, Telecommun Software & Syst Grp, Waterford, Ireland
关键词
Human activity recognition; Activity inferences; Collaborative environments; Pervasive health-care; Pervasive Computing; Ubiquitous computing;
D O I
10.1016/j.jnca.2007.11.002
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Technological advancements, including advancements in the medical field have drastically improved our quality of life, thus pushing life expectancy increasingly higher. This has also had the effect of increasing the number of elderly population. More than ever, health-care institutions must now care for a large number of elderly patients, which is one of the contributing factors in the rising health-care costs. Rising costs have prompted hospitals and other health-care institutions to seek various cost-cutting measures in order to remain competitive. One avenue being explored ties in the technological advancements that can make hospital working environments much more efficient. Various communication technologies, mobile computing devices, micro-embedded devices and sensors have the ability to support medical staff efficiency and improve health-care systems. In particular, one promising application of these technologies is towards deducing medical staff activities. Having this continuous knowledge about health-care staff activities can provide medical staff with crucial information of particular patients, interconnect with other supporting applications in a seamless manner (e.g. a doctor diagnosing a patient can automatically be sent the patient's lab report from the pathologist), a clear picture of the time utilisation of doctors and nurses and also enable remote virtual collaboration between activities, thus creating a strong base for establishment of an efficient collaborative environment. In this paper, we describe our activity recognition system that in conjunction with our efficiency mechanism has the potential to cut down health-care costs by making the working environments more efficient. Initially, we outline the activity recognition process that has the ability to infer user activities based on the self-organisation of surrounding objects that user may manipulate. We then use the activity recognition information to enhance virtual collaboration in order to improve overall efficiency of tasks within a hospital environment. We have analysed a number of medical staff activities to guide our simulation setup. Our results show all accurate activity recognition process for individual users with respect to their behaviour. At the same time we support remote virtual collaboration through tasks allocation process between doctors and nurses with results showing maximum efficiency within the resource constraints. (C) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:628 / 655
页数:28
相关论文
共 38 条
[1]  
[Anonymous], 2002, P AAAI 02 WORKSH AUT
[2]   Activity recognition from user-annotated acceleration data [J].
Bao, L ;
Intille, SS .
PERVASIVE COMPUTING, PROCEEDINGS, 2004, 3001 :1-17
[3]   Pervasive computing support for hospitals: An overview of the activity-based computing project [J].
Bardram, Jakob E. ;
Christensen, Henrik B. .
IEEE PERVASIVE COMPUTING, 2007, 6 (01) :44-51
[4]  
BARDRAM JE, 2004, P 1 INT WORKSH COMP
[5]  
BARDRAM JE, 2006, LNCS, V4206
[6]   A keyhole plan recognition model for Alzheimer's patients: First results [J].
Bouchard, Bruno ;
Giroux, Sylvain ;
Bouzouane, Abdenour .
APPLIED ARTIFICIAL INTELLIGENCE, 2007, 21 (07) :623-658
[7]  
Cabral L, 2004, LECT NOTES COMPUT SC, V3053, P225
[8]   A simulation-ILP based tool for scheduling ER staff [J].
Centeno, MA ;
Giachetti, R ;
Linn, R ;
Ismail, AM .
PROCEEDINGS OF THE 2003 WINTER SIMULATION CONFERENCE, VOLS 1 AND 2, 2003, :1930-1938
[9]  
*CREATEASOFT I, HEALTHC PROC SIM
[10]  
Crespo A., 2002, Semantic Overlay Networks for P2P Systems