An IoT System for Remote Monitoring of Patients at Home

Application areas that utilize the concept of IoT can be broadened to healthcare or remote monitoring areas. In this paper, a remote monitoring system for patients at home in IoT environments is proposed, constructed, and evaluated through several experiments. To make it operable in IoT environments, a protocol conversion scheme between ISO/IEEE 11073 protocol and oneM2M protocol, and a Multiclass Q-learning scheduling algorithm based on the urgency of biomedical data delivery to medical staff are proposed. In addition, for the sake of patients’ privacy, two security schemes are proposed—the separate storage scheme of data in parts and the Buddy-ACK authorization scheme. The experiment on the constructed system showed that the system worked well and the Multiclass Q-learning scheduling algorithm performs better than the Multiclass Based Dynamic Priority scheduling algorithm. We also found that the throughputs of the Multiclass Q-learning scheduling algorithm increase almost linearly as the measurement time increases, whereas the throughputs of the Multiclass Based Dynamic Priority algorithm increase with decreases in the increasing ratio.

[1]  KeeHyun Park,et al.  A Smart Personal Activity Monitoring System Based on Wireless Device Management Methods , 2011 .

[2]  Abdulmotaleb El-Saddik,et al.  ECG Authentication for Mobile Devices , 2016, IEEE Transactions on Instrumentation and Measurement.

[3]  Peter Dayan,et al.  Q-learning , 1992, Machine Learning.

[4]  Tamma Bheemarjuna Reddy,et al.  Class based dynamic priority scheduling for uplink to support M2M communications in LTE , 2014, 2014 IEEE World Forum on Internet of Things (WF-IoT).

[5]  Yier Jin,et al.  Privacy and Security in Internet of Things and Wearable Devices , 2015, IEEE Transactions on Multi-Scale Computing Systems.

[6]  Johannes Sametinger,et al.  Secure and usable authentication on mobile devices , 2012, MoMM '12.

[7]  Hakima Chaouchi,et al.  The Internet of things : connecting objects to the web , 2013 .

[8]  Kunio Ito,et al.  Framework and Overview , 2014 .

[9]  Ivan Zuzak,et al.  A Methodology for SIP and SOAP Integration Using Application-Specific Protocol Conversion , 2012, TWEB.

[10]  Debnath Bhattacharyya,et al.  Biometric Authentication: A Review , 2009 .

[11]  Catherine Mulligan,et al.  From Machine-to-Machine to the Internet of Things - Introduction to a New Age of Intelligence , 2014 .

[12]  Kee Hyun Park,et al.  Advanced Pulse Oximetry System for Remote Monitoring and Management , 2012, Journal of biomedicine & biotechnology.

[13]  KeeHyun Park,et al.  A multipurpose smart activity monitoring system for personalized health services , 2015, Inf. Sci..

[14]  W. Kearns,et al.  Tortuosity in Movement Paths Is Related to Cognitive Impairment , 2010, Methods of Information in Medicine.

[15]  Kay Römer,et al.  Self-Description and Protocol Conversion for a Web of Things , 2010, 2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing.

[16]  Eleni Stroulia,et al.  International Journal of Medical Informatics , 2016 .

[17]  Bridgette Wessels,et al.  Examining the use of telehealth in community nursing: identifying the factors affecting frontline staff acceptance and telehealth adoption. , 2015, Journal of advanced nursing.

[18]  Mahdi Ben Alaya,et al.  Architecting information centric ETSI-M2M systems , 2014, 2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS).

[19]  Neil Charness,et al.  Remote Health Monitoring for Older Adults and Those with Heart Failure: Adherence and System Usability. , 2016, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[20]  Jiafu Wan,et al.  Security in the Internet of Things: A Review , 2012, 2012 International Conference on Computer Science and Electronics Engineering.

[21]  Mohamed Hamdi,et al.  Game-based adaptive security in the Internet of Things for eHealth , 2014, 2014 IEEE International Conference on Communications (ICC).

[22]  Kathryn H. Bowles,et al.  Utilizing Home Healthcare Electronic Health Records for Telehomecare Patients With Heart Failure: A Decision Tree Approach to Detect Associations With Rehospitalizations , 2016, Computers, informatics, nursing : CIN.

[23]  Simon S. Lam.  Protocol Conversion , 1988, IEEE Trans. Software Eng..

[24]  J. Pagán,et al.  Telehealth and hospitalizations for Medicare home healthcare patients. , 2011, The American journal of managed care.

[25]  Ashwin Sampath,et al.  Downlink Scheduling for Multiclass Traffic in LTE , 2009, EURASIP J. Wirel. Commun. Netw..

[26]  Steven Furnell,et al.  Surveying the Development of Biometric User Authentication on Mobile Phones , 2015, IEEE Communications Surveys & Tutorials.

[27]  W. Kearns,et al.  Path tortuosity in everyday movements of elderly persons increases fall prediction beyond knowledge of fall history, medication use, and standardized gait and balance assessments. , 2012, Journal of the American Medical Directors Association.

[28]  KeeHyun Park,et al.  UbiMMS: An Ubiquitous Medication Monitoring System Based on Remote Device Management Methods , 2012, Health information management : journal of the Health Information Management Association of Australia.