Smart-Monitor: Patient Monitoring System for IoT-Based Healthcare System Using Deep Learning

References

• S. Sagar, C. Keke, and S. Amit, “Toward practical privacy-preserving analytics for IoT and cloud-based healthcare systems,” IEEE Internet Comput., Vol. 22, no. 2, pp. 42–51, Jan. 2018. doi: 10.1109/MIC.2018.112102519
   Web of Science ®Google Scholar
• Z. Yin, Q. Meikang, W. T. Chun, M. H. Mohammad, and A. Atif, “Health-CPS: Healthcare cyber-physical system assisted by cloud and big data,” IEEE Syst. J., Vol. 11, no. 1, pp. 88–95, Jan. 2017. doi: 10.1109/JSYST.2015.2418680
   Web of Science ®Google Scholar
• H. Haiping, G. Tianhe, Y. Ning, W. Ruchuan, and D. Yi, “Private and secured medical data transmission and analysis for wireless sensing healthcare system,” IEEE Trans. Ind. Inform., Vol. 13, no. 3, pp. 1227–1237, Mar. 2017. doi: 10.1109/TII.2017.2687618
   Web of Science ®Google Scholar
• L.M. Braunstein, “Healthcare in the age of interoperability: The promise of fast healthcare interoperability resources,” IEEE Pul., Vol. 9, no. 6, pp. 24–27, Mar. 2018. doi: 10.1109/MPUL.2018.2869317
   PubMed Web of Science ®Google Scholar
• B. Andriy, C. Adam, H. Christopher, P. Dmitri, and R. S. Simon, “SlimFS: A thin and unobtrusive file system for embedded systems and consumer products,” IEEE Trans. Consumer Electron., Vol. 64, no. 3, pp. 334–338, Aug. 2018. doi: 10.1109/TCE.2018.2867826
   Web of Science ®Google Scholar
• J. Pandia Rajan, and S. Edward Rajan, “An internet of things based physiological signal monitoring and receiving system for virtual enhanced health care network,” Techn. Health Care, Vol. 26, no. 2, pp. 379–385, Apr. 2018. doi: 10.3233/THC-171173
   PubMed Web of Science ®Google Scholar
• H. Weigang, N. Zhaolong, H. Xiping, D. Lei Guo, Y. Yan, Y. Ricky, and K. Kwok, “On-chip hardware accelerator for automated diagnosis through human-machine interactions in healthcare delivery,” IEEE Trans. Autom. Sci. Eng., Vol. 16, no. 1, pp. 206–217, Mar. 2018.
   Web of Science ®Google Scholar
• A. S. Omar, and K. Prahald, “Dedicated real-time monitoring system for health care using ZigBee,” IET Health. Tech. Letters, Vol. 4, no. 4, pp. 142–144, Aug. 2017. doi: 10.1049/htl.2017.0030
   PubMed Web of Science ®Google Scholar
• Y. F. Lin, H. H. Shie, Y. C. Yang, and V. Tseng, “Design of a real-time and continua-based framework for care guideline recommendations,” Int. J. Environ. Res. Public Health, Vol. 11, no. 4, pp. 4262–4279, Apr. 2014. doi: 10.3390/ijerph110404262
   PubMed Web of Science ®Google Scholar
• M. Sumit, C. Leon, M. Ognian, C. Chih Hung, M. Tapas, and M. Jamal Deen, “Noncontact wearable wireless ECG systems for long-term monitoring,” IEEE Rev. Biomed. Eng., Vol. 11, no. 1, pp. 306–321, May. 2018.
   PubMedGoogle Scholar
• A. Ahmad, and L. Lina, “Patients adoption of WSN-based smart home healthcare systems: An integrated model of facilitators and barriers,” IEEE Trans. Prof. Commun., Vol. 60, no. 1, pp. 4–23, Jan. 2017. doi: 10.1109/TPC.2016.2632822
   Web of Science ®Google Scholar
• K. Ondrej, N. Jan, and S. Radislav, “Quality-based multiple-sensor fusion in an industrial wireless sensor network for MCM,” IEEE Trans. Ind. Electron., Vol. 61, no. 9, pp. 4903–4911, Sep. 2014. doi: 10.1109/TIE.2013.2293710
   Web of Science ®Google Scholar
• A. Atif, “Monitoring system for patients using multimedia for smart healthcare,” IEEE Access, Vol. 6, pp. 23271–23276, Apr. 2018. doi: 10.1109/ACCESS.2018.2826525
   Web of Science ®Google Scholar
• A. Stuhlsatz, C. Meyer, F. Eyben, T. Zielke, G. Meier, and B. Schuller, “Deep neural networks for acoustic emotion recognition: Raising the benchmarks,” in Proceedings of IEEE International Conference on Acoustic Speech Signal Processing (ICASSP), Prague, Czech Republic, 2011, pp. 5688–5691.
   Google Scholar
• M. Stefano, L. Antonio, V. Ramon, G. David, and M. Marco, “Wireless wearable magnetometer-based sensor for sleep quality monitoring,” IEEE Sensors J., Vol. 18, no. 5, pp. 2145–2152, Jan. 2018. doi: 10.1109/JSEN.2018.2791400
   Web of Science ®Google Scholar
• I. Mellal, M. Laghrouche, and H. T. Bui, “Field programmable gate array (FPGA) respiratory monitoring system using a flow microsensor and an accelerometer,” Meas. Sci. Rev., Vol. 17, no. 2, pp. 61–67, Mar. 2017. doi: 10.1515/msr-2017-0008
   Web of Science ®Google Scholar
• Y. Geng, J. Mingzhe, O. Wei, and J. Guangchao, “IoT-based remote pain monitoring system: From device to cloud platform,” IEEE J. Biomed. Health Inform., Vol. 22, no. 6, pp. 1711–1719, Nov. 2018.
   PubMed Web of Science ®Google Scholar
• S. J. Wu, R. D. Chiang, S. H. Chang, and W. T. Chang, “An interactive telecare system enhanced with IoT technology,” IEEE Pervasive Comput., Vol. 16, no. 3, pp. 62–69, Nov. 2017. doi: 10.1109/MPRV.2017.2940967
   Web of Science ®Google Scholar
• Y. Hongxu, and K. J. Niraj, “A health decision support system for disease diagnosis based on wearable medical sensors and machine learning ensembles,” IEEE Trans. Multi-Scale Comput. Syst., Vol. 3, no. 4, pp. 228–241, May. 2017. doi: 10.1109/TMSCS.2017.2710194
   Web of Science ®Google Scholar
• R. Daniele, W. Charence, L. Benny, and Y. Guang Zhong, “A deep learning approach to on-node sensor data analytics for mobile or wearable devices,” IEEE J. Bio. Health Inform., Vol. 21, no. 1, pp. 56–64, Dec. 2016.
   PubMed Web of Science ®Google Scholar
• J. Inigo, S. Hector, B. Andoni, Z. Ibon, J. Ainara, I. Galarraga, and B. Roc, “UHF RFID temperature sensor assisted with body-heat dissipation energy harvesting,” IEEE Sens. J., Vol. 17, no. 5, pp. 1471–1478, Feb. 2017. doi: 10.1109/JSEN.2016.2638473
   Web of Science ®Google Scholar
• P. Debajyoti, F. Suree, C. Nipon, and K. Prasert, “Internet-of-things and smart homes for elderly healthcare: An end user perspective,” IEEE Access, Vol. 6, pp. 10483–10496, Feb. 2018. doi: 10.1109/ACCESS.2018.2808472
   Web of Science ®Google Scholar
• C. Subin, K. Dae Jung, C. Yun Young, and P. Kyeonghwan, “A multisensor mobile interface for industrial environment and healthcare monitoring,” IEEE Trans. Ind. Electron., Vol. 64, no. 3, pp. 2344–2352, Nov. 2017.
   Web of Science ®Google Scholar
• P. S. Das, and J. Y. Park, “A flexible touch sensor based on conductive elastomer for biopotential monitoring applications,” Biomed. Signal. Process. Control, Vol. 33, pp. 72–82, Mar. 2017. doi: 10.1016/j.bspc.2016.11.008
   Web of Science ®Google Scholar
• L. Peng, C. Zhikui, Y. Laurence Tianruo, Z. Qingchen, and M. D. Jamal, “Deep convolutional computation model for feature learning on big data in internet of things,” IEEE Trans. Ind. Inform., Vol. 14, no. 2, pp. 790–798, Feb. 2018. doi: 10.1109/TII.2017.2739340
   Web of Science ®Google Scholar
• Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature, Vol. 521, no. 7553, pp. 436–444, May. 2015. doi: 10.1038/nature14539
   PubMed Web of Science ®Google Scholar
• L. He, O. Kaoru, and D. Mianxiong, “Learning IoT in edge: Deep learning for the internet of things with edge computing,” IEEE Netw., Vol. 32, no. 1, pp. 96–101, Jan. 2018. doi: 10.1109/MNET.2018.1700167
   Web of Science ®Google Scholar
• Z. Zhuoran, B. Kamyar Mirzazad, and G. Andreas, “Deepthings: Distributed adaptive deep learning inference on resource-constrained iot edge clusters,” IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst., Vol. 37, no. 1, pp. 2348–2359, Nov. 2018.
   Google Scholar
• L. Chung Chih, L. Ping-Yeh, and L. Po Kuan, “A healthcare integration system for disease assessment and safety monitoring of dementia patients,” IEEE Trans. Inf. Technol. Biomed., Vol. 12, no. 5, pp. 579–586, Sep. 2018. doi: 10.1109/TITB.2008.917914
   Google Scholar