Health Monitoring and Management Using Internet-of-Things (IoT) Sensing with Cloud-Based Processing: Opportunities and Challenges

Among the panoply of applications enabled by the Internet of Things (IoT), smart and connected health care is a particularly important one. Networked sensors, either worn on the body or embedded in our living environments, make possible the gathering of rich information indicative of our physical and mental health. Captured on a continual basis, aggregated, and effectively mined, such information can bring about a positive transformative change in the health care landscape. In particular, the availability of data at hitherto unimagined scales and temporal longitudes coupled with a new generation of intelligent processing algorithms can: (a) facilitate an evolution in the practice of medicine, from the current post facto diagnose-and-treat reactive paradigm, to a proactive framework for prognosis of diseases at an incipient stage, coupled with prevention, cure, and overall management of health instead of disease, (b) enable personalization of treatment and management options targeted particularly to the specific circumstances and needs of the individual, and (c) help reduce the cost of health care while simultaneously improving outcomes. In this paper, we highlight the opportunities and challenges for IoT in realizing this vision of the future of health care.

[1]  Roderick J. A. Little,et al.  Statistical Analysis with Missing Data: Little/Statistical Analysis with Missing Data , 2002 .

[2]  P. Fayers,et al.  The Visual Display of Quantitative Information , 1990 .

[3]  Jorge Werner,et al.  A Cloud Computing Solution for Patient's Data Collection in Health Care Institutions , 2010, 2010 Second International Conference on eHealth, Telemedicine, and Social Medicine.

[4]  G. Nalinipriya,et al.  Extensive medical data storage with prominent symmetric algorithms on cloud - A protected framework , 2013, INTERNATIONAL CONFERENCE ON SMART STRUCTURES AND SYSTEMS - ICSSS'13.

[5]  Yixin Chen,et al.  Medical Data Mining for Early Deterioration Warning in General Hospital Wards , 2011, 2011 IEEE 11th International Conference on Data Mining Workshops.

[6]  Wei Zhao,et al.  Medical application on Internet of Things , 2011 .

[7]  J. Couderc The telemetric and holter ECG warehouse initiative (THEW): A data repository for the design, implementation and validation of ECG-related technologies , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[8]  Dae-Hyeong Kim,et al.  Multifunctional wearable devices for diagnosis and therapy of movement disorders. , 2014, Nature nanotechnology.

[9]  Dirk Fox,et al.  Advanced Encryption Standard (AES) , 1999, Datenschutz und Datensicherheit.

[10]  P. Ray Home Health Hub Internet of Things (H3IoT): An architectural framework for monitoring health of elderly people , 2014, 2014 International Conference on Science Engineering and Management Research (ICSEMR).

[11]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[12]  Wenye Wang,et al.  The unheralded power of cloudlet computing in the vicinity of mobile devices , 2013, 2013 IEEE Globecom Workshops (GC Wkshps).

[13]  R. Bharat Rao,et al.  The role of medical data analytics in reducing health fraud and improving clinical and financial outcomes , 2013, CBMS.

[14]  Wendi Heinzelman,et al.  COMBAT: mobile-Cloud-based cOmpute/coMmunications infrastructure for BATtlefield applications , 2012, Defense, Security, and Sensing.

[15]  Vijanth S. Asirvadam,et al.  Development of private cloud storage for medical image research data , 2014, 2014 International Conference on Computer and Information Sciences (ICCOINS).

[16]  Aníbal R. Figueiras-Vidal,et al.  Pattern classification with missing data: a review , 2010, Neural Computing and Applications.

[17]  Wendi B. Heinzelman,et al.  Cloud-Vision: Real-time face recognition using a mobile-cloudlet-cloud acceleration architecture , 2012, 2012 IEEE Symposium on Computers and Communications (ISCC).

[18]  Hiroshi Morita,et al.  The QT syndromes: long and short , 2008, The Lancet.

[19]  Mehrdad Nourani,et al.  Reducing leakage power in wearable medical devices using memory nap controller , 2014, 2014 IEEE Dallas Circuits and Systems Conference (DCAS).

[20]  Edward Rolf Tufte,et al.  The visual display of quantitative information , 1985 .

[21]  Bernice E. Rogowitz,et al.  A rule-based tool for assisting colormap selection , 1995, Proceedings Visualization '95.

[22]  Matlab Matlab (the language of technical computing): using matlab graphics ver.5 , 2014 .

[23]  Wen Hu,et al.  Energy efficient information collection in wireless sensor networks using adaptive compressive sensing , 2009, 2009 IEEE 34th Conference on Local Computer Networks.

[24]  Jiye Shi,et al.  Use of Network Latency Profiling and Redundancy for Cloud Server Selection , 2014, 2014 IEEE 7th International Conference on Cloud Computing.

[25]  Fang Hu,et al.  On the Application of the Internet of Things in the Field of Medical and Health Care , 2013, 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing.

[26]  H. Bazett,et al.  AN ANALYSIS OF THE TIME‐RELATIONS OF ELECTROCARDIOGRAMS. , 1997 .

[27]  John C. Platt,et al.  Fast training of support vector machines using sequential minimal optimization, advances in kernel methods , 1999 .

[28]  Simon Heron,et al.  Encryption: Advanced Encryption Standard (AES) , 2009 .

[29]  Yoram Singer,et al.  Pegasos: primal estimated sub-gradient solver for SVM , 2011, Math. Program..

[30]  Pieter Abbeel,et al.  Max-margin Classification of Data with Absent Features , 2008, J. Mach. Learn. Res..

[31]  Hassan Ghasemzadeh,et al.  WANDA: an end-to-end remote health monitoring and analytics system for heart failure patients , 2012, Wireless Health.

[32]  Sushmita Ruj,et al.  Privacy Preserving Access Control with Authentication for Securing Data in Clouds , 2012, 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012).

[33]  Ying Bai,et al.  An ultra-wearable, wireless, low power ECG monitoring system , 2006, 2006 IEEE Biomedical Circuits and Systems Conference.

[34]  C. Tanner,et al.  Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030 , 2007, Neurology.

[35]  Rita Paradiso,et al.  A wearable health care system based on knitted integrated sensors , 2005, IEEE Transactions on Information Technology in Biomedicine.

[36]  L. S. Fridericia Die Systolendauer im Elektrokardiogramm bei normalen Menschen und bei Herzkranken , 2009 .

[37]  Samee Ullah Khan,et al.  > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 1 , 2008 .

[38]  Jean-Philippe Couderc,et al.  Cloud‐Based Privacy‐Preserving Remote ECG Monitoring and Surveillance , 2015, Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc.

[39]  Yaser Jararweh,et al.  Cloudlet-based for big data collection in body area networks , 2013, 8th International Conference for Internet Technology and Secured Transactions (ICITST-2013).

[40]  王漪 apple Watch 把苹果戴在手上 , 2014 .

[41]  Aleksandar Milenkovic,et al.  Wireless sensor networks for personal health monitoring: Issues and an implementation , 2006, Comput. Commun..

[42]  Christopher G. Healey,et al.  Choosing effective colours for data visualization , 1996, Proceedings of Seventh Annual IEEE Visualization '96.

[43]  Mohamed Adel Serhani,et al.  Novel Cloud and SOA-Based Framework for E-Health Monitoring Using Wireless Biosensors , 2014, IEEE Journal of Biomedical and Health Informatics.

[44]  Radford M. Neal Pattern Recognition and Machine Learning , 2007, Technometrics.

[45]  Sabine Süsstrunk,et al.  An interactive app for color deficient viewers , 2015, Electronic Imaging.

[46]  Dae-Hyeong Kim,et al.  Flexible and stretchable electronics for biointegrated devices. , 2012, Annual review of biomedical engineering.

[47]  Michael C. Huang,et al.  Assessment of cloud-based health monitoring using Homomorphic Encryption , 2013, 2013 IEEE 31st International Conference on Computer Design (ICCD).

[48]  Matti Siekkinen,et al.  How low energy is bluetooth low energy? Comparative measurements with ZigBee/802.15.4 , 2012, 2012 IEEE Wireless Communications and Networking Conference Workshops (WCNCW).

[49]  Sanat S Bhole,et al.  Soft Microfluidic Assemblies of Sensors, Circuits, and Radios for the Skin , 2014, Science.

[50]  H. T. Mouftah,et al.  Accelerating Mobile-Cloud Computing : A Survey , 2013 .

[51]  Vladyslav Ukis,et al.  Architecture of Cloud-Based Advanced Medical Image Visualization Solution , 2013, 2013 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM).

[52]  M. N. Giriprasad,et al.  ENERGY EFFICIENT COVERAGE PROBLEMS IN WIRELESS Ad Hoc SENSOR NETWORKS , 2011 .

[53]  C. Van Hoof,et al.  Body-Heat Powered Autonomous Pulse Oximeter , 2006, 2006 5th IEEE Conference on Sensors.

[54]  Yu-Wei Su,et al.  A Comparative Study of Wireless Protocols: Bluetooth, UWB, ZigBee, and Wi-Fi , 2007, IECON 2007 - 33rd Annual Conference of the IEEE Industrial Electronics Society.

[55]  Michele Zorzi,et al.  Health care applications: a solution based on the internet of things , 2011, ISABEL '11.

[56]  Yao Zheng,et al.  Scalable and Secure Sharing of Personal Health Records in Cloud Computing Using Attribute-Based Encryption , 2019, IEEE Transactions on Parallel and Distributed Systems.

[57]  Li Wei,et al.  A Practical Tool for Visualizing and Data Mining Medical Time Series , 2005, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05).

[58]  Yaser Jararweh,et al.  Resource Efficient Mobile Computing Using Cloudlet Infrastructure , 2013, 2013 IEEE 9th International Conference on Mobile Ad-hoc and Sensor Networks.

[59]  Reinhard Schneider,et al.  Visualizing time-related data in biology, a review , 2013, Briefings Bioinform..

[60]  Falko Dressler,et al.  On the lifetime of wireless sensor networks , 2009, TOSN.

[61]  Jason Weston,et al.  Fast Kernel Classifiers with Online and Active Learning , 2005, J. Mach. Learn. Res..

[62]  Chao Yu,et al.  Camera Scheduling and Energy Allocation for Lifetime Maximization in User-Centric Visual Sensor Networks , 2010, IEEE Transactions on Image Processing.

[63]  Marco Bazzani,et al.  Enabling the IoT Paradigm in E-health Solutions through the VIRTUS Middleware , 2012, 2012 IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications.

[64]  Tao Zhang,et al.  Collaborative sensing using uncontrolled mobile devices , 2005, 2005 International Conference on Collaborative Computing: Networking, Applications and Worksharing.

[65]  Yu-Chee Tseng,et al.  The Coverage Problem in a Wireless Sensor Network , 2003, WSNA '03.

[66]  Nikolaos G. Bourbakis,et al.  A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[67]  Hillol Kargupta,et al.  Graphical Models: Foundations of Neural Computation , 2016, Pattern Analysis and Applications.

[68]  Jennifer C. Hou,et al.  Maintaining Sensing Coverage and Connectivity in Large Sensor Networks , 2005, Ad Hoc Sens. Wirel. Networks.

[69]  Nicole A. Lazar,et al.  Statistical Analysis With Missing Data , 2003, Technometrics.

[70]  V. Vaidehi,et al.  Cloud-enabled remote health monitoring system , 2013, 2013 International Conference on Recent Trends in Information Technology (ICRTIT).