Smart Healthcare System Design

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The purpose of this book is to help achieve a better integration between the work of researchers and practitioners in a single medium for capturing state-of-the-art IoT solutions in healthcare applications to address how to improve the proficiency of wireless sensor networks (WSNs) in healthcare. It explores possible automated solutions in everyday life, including the structures of healthcare systems built to handle large amounts of data, thereby improving clinical decisions; which is why this book will prove invaluable to professionals who want to increase their understanding of recent challenges in the IoT-enabled healthcare domain. The 14 chapters address various aspects of the IoT system, such as design challenges, theory, various protocols, and implementation issues, and also include several case studies.
Smart Healthcare System: Security and Privacy Aspects

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1.6.1 Future Scope

This proposal, seizure prediction has been reduced to less than 10 variables. Improving the method of optimizing all the necessary variables would make the system work more efficiently and would result in less time with a specialist. Lastly, research must be done on the transition from the ictal state back to the interictal state to see how long after a seizure the EEG returns completely back to normal, allowing the system to learn to reset itself accurately and automatically. These additions would help reduce the number of false positives and make the implementation more robust and reliable.

References

1. Carrasquilla-Batista, Quirós-Espinoza, K., Gómez-Carrasquilla, C., An Internet of Things (IoT) application to control a wheelchair through EEG signal processing. 2017 International Symposium on Wearable Robotics and Rehabilitation (WeRob) , Houston, TX, pp. 1–1, 2017.

2. Khajehei, M. and Etemady, F., Data Mining and Medical Research Studies. 2010 Second International Conference on Computational Intelligence, Modelling and Simulation , Tuban, pp. 119–122, 2010.

3. Kumar, T.S., Kanhangad, V., Pachori, R.B., Classification of seizure and seizurefree EEG signals using multi-level local patterns. 2014 19th International Conference on Digital Signal Processing , Hong Kong, pp. 646–650, 2014.

4. Polyakov, K. and Zhukova, L., Comparative Analysis of Predictive Analytics Models in Classification Problems. 2019 Actual Problems of Systems and Software Engineering (APSSE) , Moscow, Russia, pp. 162–169, 2019.

5. Arefin, M.S., Surovi, T.H., Snigdha, N.N., Mridha, M.F., Adnan, M.A., Smart healthcare system for underdeveloped countries. 2017 IEEE International Conference on Telecommunications and Photonics (ICTP) , Dhaka, pp. 28–32, 2017.

6. Roibu Crucianu, P.A., The Implications of Big Data in Healthcare. 2019 E-Health and Bioengineering Conference (EHB) , Iasi, Romania, pp. 1–4, 2019.

7. Reena, J.K. and Parameswari, R., A Smart Healthcare Monitor System in IoT Based Human Activities of Daily Living: A Review. 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon) , Faridabad, India, pp. 446–448, 2019.

8. Sahu, S. and Sharma, A., Detecting brainwaves to evaluate mental health using LabVIEW and applications. 2016 International Conference on Emerging Technological Trends (ICETT) , Kollam, pp. 1–4, 2016.

9. Rghioui, L’aarje, A., Elouaai, F., Bouhorma, M., The Internet of Things for healthcare monitoring: Security review and proposed solution. 2014 Third IEEE International Colloquium in Information Science and Technology (CIST) , Tetouan, pp. 384–389, 2014.

10. Mansour, and Ouda, H.T., On The Road to A Comparative Car Racing EEG-based Signals for Mental and Physical Brain Activity Evaluation. 2019 9th Annual Information Technology, Electromechanical Engineering and Microelectronics Conference (IEMECON) , Jaipur, India, pp. 43–48, 2019.

11. Abualsaud, K., Mohamed, A., Khattab, T., Yaacoub, E., Hasna, M., Guizani, M., Classification for Imperfect EEG Epileptic Seizure in IoT applications:

A Comparative Study. 2018 14th International Wireless Communications & Mobile Computing Conference (IWCMC) , Limassol, pp. 364–369, 2018.

12. Selvathi, D. and Meera, V.K., Realization of epileptic seizure detection in EEG signal using wavelet transform and SVM classifier. 2017 International Conference on Signal Processing and Communication (ICSPC) , Coimbatore, pp. 18–22, 2017.

13. Vaitheeshwari, R. and SathieshKumar, V., Performance Analysis of Epileptic Seizure Detection System Using Neural Network Approach. 2019 International Conference on Computational Intelligence in Data Science (ICCIDS) , Chennai, India, pp. 1–5, 2019.

14. Gurunath, R., Agarwal, M., Nandi, A., Samanta, D., An Overview: Security Issue in IoT Network. 2018 2nd International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) , Palladam, India, pp. 104–107, 2018.

15. Gope, P. and Hwang, T., BSN-Care: A Secure IoT-Based Modern Healthcare System Using Body Sensor Network. IEEE Sens. J. , 16, 5, 1368–1376, March 1, 2016.

16. Satija, U., Ramkumar, B., Sabarimalai Manikandan, M., Real-Time Signal Quality-Aware ECG Telemetry System for IoT-Based Healthcare Monitoring. IEEE Internet Things J. , 4, 3, 1–7, June 2017.

17. Sundaravadivel, Prabha, Saraju, P., Exploring Human Body Communications for IoT Enabled Ambulatory Health Monitoring Systems. IEEE International Symposium on Nano-electronic and Information Systems .

18. Sahu, S. and Sharma, A., Detecting Brainwaves to evaluate mental health using LabVIEW and applications. International Conference on Emerging Technological Trends [ICETT] .

19. Pavitra, V., Rao, Padmashree, V., Gagana, M.D., Samanta, D., Internet of Things (IoT): An Assessment. Proc. of The International Conference on Emerging Trends in Engineering and Management (ICETEM 2015) , Bangalore, India, 27 October, 2015.

20. Tyagi, S., Agarwal, A., Maheshwari, P., A Conceptual Framework for IoT-Based Healthcare System using Cloud Computing , Amity University, Uttar Pradesh, India, IEEE, 2016.

21. Lau, T.M., Gwin, J.T., Ferris, D.P., How Many Electrodes are Really Needed For EEG-Based Mobile Brain Imaging , IEEE, USA, 2012.

22. Patnaik, L.M. and Manyam, O.K., Epileptic EEG detection using neural networks and post-classification. Comput. Methods Prog. Biomed. , 91, 2, 100–109, 2008.

23. Chan, A., Sun, F., Boto, E., Wingeier, B., Automated seizure onset detection for accurate onset time determination in intracranial EEG. Clin. Neurophysiol. , 119, 12, 2687–2696, 2008.

24. Gupta, D., James, C., Gray, W., Phase Synchronization with ICA for Epileptic Seizure Onset Prediction in the Long Term EEG. 4th IET International Conference on Advances in Medical, Signal and Information Processing , MEDSIP 2008, pp. 1–4, Jun 2008.

25. Haas, S., Frei, M., Osorio, I., Strategies for adapting automated seizure detection algorithms. Med. Eng. Physics , 29, 8, 895–909, Oct 2007.

26. Molteni, E., Perego, P., Zanotta, N., Reni, G., Entropy analysis on EEG signal in a case study of focal myoclonus. 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS’08 , pp. 4724–4727, Jul. 2008.

27. Nagaraj, S., Shah, A., Shah, P., Szeto, V., Bergen, M., Ambulatory Preseizure Detection Device. Proceedings of the IEEE 32nd Annual Northeast in Bioengineering Conference , pp. 41–42, 2006.

28. Sackellares, J., Seizure Prediction, in: Epilepsy Currents , vol. 8, no. 3, pp. 55–9, American Epilepsy Society, USA, 2008.

29. Sanei, S. and Chambers, J., EEG Signal Processing , Wiley-Inter Science, 2007.

30. Sharkawy, G., Newton, C., Hartley, S., Attitudes and practices of families and healthcare personnel toward children with epilepsy in Kilifi, Kenya. Epilepsy Behav. , 8, 1, 201–212, 2006.

31. Shlens, J., A Tutorial on Principal Component Analysis, in: Systems Neurobiology Laboratory, Salk Institute for Biological Studies , Dec 2005.

32. Shneker, B. and Fountain, N., Epilepsy, in: Disease-a-Month , vol. 49, pp. 426–478, Jul. 2003.

33. Ghosh, A.M., Halder, D., Hossain, S.K.A., Remote Health Monitoring System through IoT. 5th (ICIEV) , 2016.

34. Hameed, R.T., Abdulwahabe, O., M., N., Health Monitoring System Based on Wearable Sensors and Cloud Platform. 20th (ICSTCC) , Sinaia, Romania, October, pp. 13–15, 2016.

35. Abdullah, A., Ismael, A., Rashid, A., Abou-ElNour, A., Tarique, M., Real time wireless health monitoring application using mobile devices. IJCNC , vol. 7, no.3, May 2015.

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