Healthcare Monitoring Using Wireless Sensor Networks

Healthcare Monitoring Using Wireless Sensor Networks

• 1.
  HEALTH CARE MONITORINGUSING WIRELESS SENSOR NETWORKS Under the Supervision of, Dr. B Nagaraj, Professor/ECE Karpagam College of Engineering Presented By, Mr. Ebin Ephrem Elavathingal, Karpagam College of Engineering
• 2.
  Robert S. H.Istepanaian, Y.T. Zhang, “4G Health—The Long- Term Evolution of m-Health”, IEEE Transactions On Information Technology In Biomedicine, Vol. 16, No. 1, January 2012 • Introduced new and novel concept of 4G health • Presents snapshot of recent advances in these areas •Concepts that can go beyond the traditional “m-health ecosystem” of the existing systems. •Issues need to be addressed: -Globalization and the potential options of decreasing healthcare disparities and inequality levels. -The development of the best applicable 4G health ecosystem. -Social medicine challenges -Privacy and security challenges -Future mobile technologies beyond 4G and future networks.
• 3.
  Hariharasudhan Viswanathan, BaozhiChen, and Dario Pompili, “ Research Challenges in Computation, Communication, and Context Awareness for Ubiquitous Healthcare”, IEEE Communications Magazine , May 2012 •Proposed an autonomic resource provisioning framework •Also presented an innovative solution for reliable and continuous wireless transmission of vital signs as well as a window-based algorithm Future systems will be characterized by: • pervasive vital sign monitoring using non-invasive sensors • real time processing of monitored data
• 4.
  Vana Jelicic, MicheleMagno, Davide Brunelli, Giacomo Paci, Luca Benini, “Context-Adaptive Multimodal Wireless Sensor Network for Energy Efficient Gas Monitoring”, IEEE Sensors Journal, Vol. 13, No. 1, January 2013 •Presented WSN for monitoring indoor air quality. •To achieve the goal, the node consumes a very low sleep current (only 8 μA) and can perform dynamic gas sampling. •Also reduced the activity of the node and MOX gas sensor using the information about people •Future work: Calibration and validation of gas sensor • The issue of choosing a proper sampling rate set for the gas sensor
• 5.
  John A. Stankovic,“Research Directions for the Internet of Things”, IEEE Internet Of Things Journal, Vol. 1, No. 1, February 2014 •A vision for how IoT could change the world in the distant future is first presented • Insights about IoT in the healthcare •Vision of future: IoT becomes a utility with increased sophistication in sensing, actuation, communications, control, and in creating knowledge from vast amounts of data on healthcare.
• 6.
  Ya-Li Zheng, Xiao-RongDing, Carmen Chung Yan Poon, Benny Ping Lai Lo, Heye Zhang, Xiao-Lin Zhou, Guang-Zhong Yang, Yuan-Ting Zhang, “Unobtrusive Sensing and Wearable Devices for Health Informatics”, IEEE Transactions On Biomedical Engineering, Vol. 61, No. 5, May 2014 •Provides an overview of emerging unobtrusive and wearable technologies for healthcare The future directions includes: • To develop flexible, stretchable and printable devices for unobtrusive physiological and biochemical monitoring • To develop wearable physiological imaging platforms, especially unobtrusive ones • To develop wearable devices for disease intervention •To develop systematic data fusion framework
• 7.
  Honggang Wang, ZhaoyangZhang, Xiaodong Lin, and Hua Fang, “Socialized WBANs in Mobile Sensing Environments”, IEEE Network , September/October 2014 •Proposed new algorithms and theoretical models to build s-WBANs •With s-WBANs vital sign data collection and data fusion can be performed reliably and securely •An s-WBANs application of epidemic control is investigated by fusing the information of WBANs and social interaction via mobile gateway (i.e. smartphone). •In this system the social network information and vital signs can be automatically collected •Drawbacks includes: challenges for socialized body area networks include the data unavailability due to limited WBANs deployment or failure of sensors, uncertainty of social interactions, and economic cost.
• 8.
  Vojkan Mihajlovi, BernardGrundlehner, Ruud Vullers, Julien Penders, “Wearable, “Wireless EEG Solutions in Daily Life Applications: What are we Missing?”, IEEE Journal Of Biomedical And Health Informatics, Vol. 19, No. 1, January 2015. •Discussed state-of-the-art in wireless and wearable EEG solutions •Presented guidelines toward developing intelligent wearable, wireless, convenient, and comfortable lifestyle EEG solutions •Also discussed a number of aspects where existing solutions require improvements to facilitate further progress. •No accurate measurements and non-robust model
• 9.
  Jumadi Abd Sukor,Mas S. Mohktar, Stephen J. Redmond, Nigel H. Lovell, “Signal Quality Measures on Pulse Oximetry and Blood Pressure Signals Acquired from Self-Measurement in a Home Environment”, IEEE Journal Of Biomedical And Health Informatics, Vol. 19, No. 1, January 2015. •Consists algorithms for automated quality assessment for pulse oximetry and blood pressure(BP) signals . •The trial involved four aged subjects who performed pulse oximetry and BP measurements by themselves at their home for ten days, three times per day. •Developed algorithms have performed well at noise classification and identified which BP signals might provide accurate systolic and diastolic pressure measurements. •Indicates that the developed algorithms could be readily implemented in a DSS •Future work: the study will be extended to analyze the effect of home telehealth data quality
• 10.
  Marjorie Skubic, RainerDane Guevara, Marilyn Rantz, “Automated Health Alerts Using In-Home Sensor Data for Embedded Health Assessment”, IEEE Journal of Translational Engineering in Health and Medicine, Date of publication 10 April 2015 •Presented an example of unobtrusive, continuous monitoring in the home for the purpose of assessing early health changes. •Present the methodology for four classification approaches that fuse multi sensor data. •Presented studies that designed to investigate embedded health assessment. • Firstly investigated the feature space of embedded in-home sensors •Described prospective study using 1-D health alerts •The best 6-D performance was achieved by a FPT based on domain knowledge only. •Based on the study results-proposed a model for detecting health decline with in-home sensors.
• 11.
  Arsalan Mohsen Nia,Mehran Mozaffari-Kermani, Susmita Sur-Kolay, Anand Raghunathan, Niraj K. Jha, “Energy-Efficient Long-term Continuous Personal Health Monitoring”, IEEE Transactions On Multi-scale Computing Systems, Vol. 1, No. 2, April-June 2015 •Firstly quantify the energy and storage requirements of a continuous personal health monitoring system that uses eight biomedical sensors. •Discussed a secure energy-efficient system for long-term continuous health monitoring. •4 schemes are discussed and among these the: CS-based scheme provides the most computational energy savings (e.g., up to 724 for ECG sensors) , also allows us to reduce storage requirements. •Finally all the schemes were compared and discussed how a continuous long-term health monitoring system should be configured based on patients’ needs and physicians’ recommendations.
• 12.
  Mamta Puppala, TianchengHe, Shenyi Chen, Richard Ogunti, Xiaohui Yu, Fuhai Li, Robert Jackson, and Stephen T. C. Wong, “METEOR: An Enterprise Health Informatics Environment to Support Evidence-Based Medicine” , IEEE Transactions On Biomedical Engineering, Vol. 62, No. 12, December 2015. •Developed an integrated clinical informatics environment, i.e., Methodist environment for translational enhancement and outcomes research (METEOR). •METEOR is designed to help physicians, investigators, and researchers to meet the complex demands and opportunities of healthcare. •Data and usability analysis were performed on METEOR components as a preliminary evaluation. •METEOR EDW and informatics applications improved outcomes, enabled coordinated care, and support health analytics and clinical research at HMH.
• 13.
  Eleni Fotopoulou, AnastasiosZafeiropoulos, Dimitris Papaspyros, Panagiotis Hasapis, George Tsiolis, Thanassis Bouras, Spyros Mouzakitis, Norma Zanetti, “Linked Data Analytics in Interdisciplinary Studies: The Health Impact of Air Pollution in Urban Areas”, IEEE Access, Date of publication December 30, 2015. •A novel approach toward the production and consumption of linked data analytics in urban environments is presented. •The approach is based on the exploitation of linked data principles, enhancing the ability of managing and processing of data, in ways not available before.
• 14.
  Problem Statement • Norapid Medical sensor network has not been proposed • Need of a rapid diagnosis e-health care system • Doesn’t interrupt the human’s daily activities to predict and prevent diseases • No proper Systems which compliment health and patient’s environment
• 15.
  Healthcare Monitoring Using WirelessSensor Networks • Environment Sensor & Physiological sensor nodes can be seamlessly integrated into wireless personal or body networks (WPANs or WBANs) for health monitoring • WSNs are expected to be integrated into the “Internet of Things”, where these sensor nodes join the internet dynamically • To build a E-healthcare system that monitors, predicts and informs the medical to take proper prevention and precautions human health conditions from his environment •Healthy body from healthy environment and healthy habits
• 16.
  ROAD MAP FORRESEARCHJUNE 2019 Course Work Completion & Literature Survey 1st DC meeting JUNE 2016 March 2017 May 2017 Sept 2017 Tools & Methods Identification Thesis Submission NOV 2017 System Design Jan 2018 Implementation May 2018 & Writing paper Learning of Tools & Writing paper & Writing paper Analysis of Results Writing Thesis
• 17.
  TENURE ACTIVITY JUNE 2016- MARCH 2017 Course Work 1. Wireless Communication 2. MIC and RF System Design 3. Speech and Audio Signal Processing 4. Advanced Embedded Systems MARCH 2017 - MAY 2017 Literature Survey MAY 2017- SEPTEMBER 2017 Tools and Methods Identification and Learning SEPTEMBER 2017 - NOVEMBER 2017 Learning and Familiarising with Tools NOVEMBER 2017 - JANUARY 2018 System Design JANUARY 2018 - MAY 2018 Implementation and Analysing Results From MAY 2018 Writing papers and upgrading the system JUNE 2019 SUBMITING THESIS ROAD MAP FOR RESEARCH
• 18.
  REFERENCES [1]Robert S. H.Istepanaian, Y.T. Zhang, “Guest Editorial-Introduction to the Special Section: 4G Health—The Long-Term Evolution of m-Health”, IEEE Transactions On Information Technology In Biomedicine, Vol. 16, No. 1, January 2012. [2]Hariharasudhan Viswanathan, Baozhi Chen, and Dario Pompili, “Research Challenges in Computation, Communication, and Context Awareness for Ubiquitous Healthcare”, IEEE Communications Magazine , May 2012 [3]John A. Stankovic , “Research Directions for the Internet of Things”, IEEE Internet Of Things Journal, Vol. 1, No. 1, February 2014 [4]Ya-Li Zheng, Xiao-Rong Ding, Carmen Chung Yan Poon, Benny Ping Lai Lo, Heye Zhang, Xiao-Lin Zhou, Guang- Zhong Yang, Yuan-Ting Zhang, “Unobtrusive Sensing and Wearable Devices for Health Informatics”, IEEE Transactions On Biomedical Engineering, Vol. 61, No. 5, May 2014 [5]Honggang Wang, Zhaoyang Zhang, Xiaodong Lin, and Hua Fang, “Socialized WBANs in Mobile Sensing Environments”, IEEE Network , September/October 2014 [6]Vojkan Mihajlovi, Bernard Grundlehner, Ruud Vullers, Julien Penders, “Wearable, “Wireless EEG Solutions in Daily Life Applications: What are we Missing?”, IEEE Journal Of Biomedical And Health Informatics, Vol. 19, No. 1, January 2015. [7]Jumadi Abd Sukor, Mas S. Mohktar, Stephen J. Redmond, Nigel H. Lovell, “Signal Quality Measures on Pulse Oximetry and Blood Pressure Signals Acquired from Self-Measurement in a Home Environment”, IEEE Journal Of Biomedical And Health Informatics, Vol. 19, No. 1, January 2015. [8]Marjorie Skubic, Rainer Dane Guevara, Marilyn Rantz, “Automated Health Alerts Using In-Home Sensor Data for Embedded Health Assessment”, IEEE Journal of Translational Engineering in Health and Medicine, Date of publication 10 April 2015
• 19.
  [9]Arsalan Mohsen Nia,Mehran Mozaffari-Kermani, Susmita Sur-Kolay, Anand Raghunathan, Niraj K. Jha, “Energy-Efficient Long-term Continuous Personal Health Monitoring”, IEEE Transactions On Multi-scale Computing Systems, Vol. 1, No. 2, April- June 2015 [10]Ludovic Chevalier, Stephanie Sahuguede, Anne Julien-Vergonjanne, “Optical Wireless Links as an Alternative to Radio-Frequency for Medical Body Area Networks”, IEEE Journal On Selected Areas In Communications, Vol. 33, No. 9, September 2015 [11]Mamta Puppala, Tiancheng He, Shenyi Chen, Richard Ogunti, Xiaohui Yu, Fuhai Li, Robert Jackson, and Stephen T. C. Wong, “METEOR: An Enterprise Health Informatics Environment to Support Evidence-Based Medicine” , IEEE Transactions On Biomedical Engineering, Vol. 62, No. 12, December 2015. [12]Eleni Fotopoulou, Anastasios Zafeiropoulos, Dimitris Papaspyros, Panagiotis Hasapis, George Tsiolis, Thanassis Bouras, Spyros Mouzakitis, Norma Zanetti, “Linked Data Analytics in Interdisciplinary Studies: The Health Impact of Air Pollution in Urban Areas”, IEEE Access, Date of publication December 30, 2015.
• 20.
  THANK YOU