Design framework for unobtrusive patient location recognition using passive RFID and particle filtering

The remarkable growth in wireless communication technologies in recent times has motivated the synergy between wireless systems and medical sciences for improved healthcare services. Several emerging wireless technologies and approaches have therefore been proposed to achieve various efficient monitoring systems for health-related activities. In this paper, localisation of a patient using the ranging approach of received signal strength from passive RFID was proposed in the form of smart room. The proposed system is modelled based on a three-level intelligent model of transition, signal measurement and location sensing. The measured RSS is analysed using particle filtering algorithm as a means of localising the position of the target in indoor environments. The system was simulated in a test bed environment using wireless insite with satisfactory results. The system is aimed at achieving a non-wearable sensor approach that is unobtrusive and non-invasive for recognition of activity and location of critically-ill patients and the elderly for timely and reliable healthcare intervention.

[1]  Ivor Loobas,et al.  Medical and context data acquisition system for patient home monitoring , 2010, 2010 12th Biennial Baltic Electronics Conference.

[2]  Bunthit Watanapa,et al.  Smart bedroom for elderly using kinect , 2014, 2014 International Computer Science and Engineering Conference (ICSEC).

[3]  Rubén Usamentiaga,et al.  Unobtrusive health monitoring system using video-based physiological information and activity measurements , 2015, 2015 International Conference on Computer, Information and Telecommunication Systems (CITS).

[4]  N. Ashida,et al.  A method for supporting at-home fitness exercise guidance and at-home nursing care for the elders, video-based simple measurement system , 2008, HealthCom 2008 - 10th International Conference on e-health Networking, Applications and Services.

[5]  Tapio Heikkilä,et al.  Low intrusive Ehealth monitoring: human posture and activity level detection with an intelligent furniture network , 2013, IEEE Wireless Communications.

[6]  Unai Bilbao,et al.  In-bed Patients Behaviour Monitoring System , 2008, 2008 International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies.

[7]  Ahmed Alahmadi,et al.  A smart approach towards a mobile e-health monitoring system architecture , 2011, 2011 International Conference on Research and Innovation in Information Systems.

[8]  Hadi Aliakbarpour,et al.  Probabilistic LMA-based classification of human behaviour understanding using Power Spectrum technique , 2010, 2010 13th International Conference on Information Fusion.

[9]  Hongming Cai,et al.  Architecture of M-Health Monitoring System Based on Cloud Computing for Elderly Homes Application , 2014, 2014 Enterprise Systems Conference.

[10]  Mu Qiao,et al.  Interactive Games to Improve Quality of Life for the Elderly: Towards Integration into a WSN Monitoring System , 2010, 2010 Second International Conference on eHealth, Telemedicine, and Social Medicine.

[11]  Dmitry B. Goldgof,et al.  Understanding Transit Scenes: A Survey on Human Behavior-Recognition Algorithms , 2010, IEEE Transactions on Intelligent Transportation Systems.

[12]  Yuji Higashi,et al.  Development and clinical evaluation of a home healthcare system measuring in toilet, bathtub and bed without attachment of any biological sensors , 2010, Proceedings of the 10th IEEE International Conference on Information Technology and Applications in Biomedicine.

[13]  Qing Zhang,et al.  Unsupervised daily routine and activity discovery in smart homes , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[14]  S. Kyriazakos,et al.  Delivery of eHealth and eInclusion services for elderly people with mild dementia , 2011, 2011 2nd International Conference on Wireless Communication, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology (Wireless VITAE).

[15]  J. O'Brien,et al.  Behavior disorders of dementia: recognition and treatment. , 2006, American family physician.

[16]  Long Xu,et al.  Video-based tracking and quantified assessment of spontaneous limb movements in neonates , 2015, 2015 17th International Conference on E-health Networking, Application & Services (HealthCom).

[17]  Rodolfo Ipolito Meneguette,et al.  A Health Smart Home System to Report Incidents for Disabled People , 2015, 2015 International Conference on Distributed Computing in Sensor Systems.

[18]  Sabine Van Huffel,et al.  Automatic video detection of body movement during sleep based on optical flow in pediatric patients with epilepsy , 2010, Medical & Biological Engineering & Computing.