Using casual reasoning for anomaly detection among ECG live data streams in ubiquitous healthcare monitoring systems

  • Uvais Qidwai
  • Junaid Chaudhry
  • Sohail JabbarEmail author
  • Hafiz Maher Ali Zeeshan
  • Naeem Janjua
  • Shehzad Khalid
Original Research


Anomalies in cardiac functionality can be fatal. Early detection of these anomalies, and in many cases their precursors, can save lives. The probability of the occurrence of these anomalies is extremely among people with a pre-diagnosed heart condition. In this research, we discovered that much remote Electrocardiography (ECG) monitoring systems do not convey “enough” information to the diagnosing doctor or the nominated caregiver. A few examples of this information can be the type of cardiac abnormality, the exact waveform of the ECG signal, time and frequency of the occurrence of the anomaly, machine-understandable part so that medical SCADA be alerted about the case, and immediate preventative urgent steps correlated to that emergency. It is also important to delivery surrounding context to the Health Information System so that the medical expert make his/her diagnosis with ample support data. The most important component in this communication is the security of contents from cybercrimes. We propose a cost-efficient and non-invasive health monitoring system that is secure and quickly deployable. The presented system embeds an intelligent wearable data acquisition system with unique identification algorithms requiring very little computational time and simple threshold-based classification.


Ubiquitous computing Embedded system Finite impulse response (FIR) filters Electrocardiogram (ECG) Healthcare WBAN 



  1. Ahmad M, Jabbar S, Ahmad A, Piccialli F, Jeon G (2018) A sustainable solution to support data security in high bandwidth health care remote locations by using TCP CUBIC mechanism. IEEE Trans Sustain Comput. CrossRefGoogle Scholar
  2. Ashraf R, Ahmed M, Ahmad U, Habib MA, Jabbar S, Naseer K (2018a) MDCBIR-MF: multimedia data for content-based image retrieval by using multiple features. Multimed Tools Appl. CrossRefGoogle Scholar
  3. Ashraf R, Ahmed M, Jabbbar S, Khalid S, Ahmad A, Din S, Jeon G (2018b) Content based image retrieval by using color descriptor and discrete wavelet transform. J Med Syst (SpringerLink) 42 (3):44CrossRefGoogle Scholar
  4. Buechley L, Eisenberg M (2008) The LilyPad Arduino: toward wearable engineering for everyone. IEEE Pervasive Comput (IEEE) 7(2):12–15CrossRefGoogle Scholar
  5. Cables BioMetric (2011) CardioSim Heartbeat simulator system. Accessed 18 Sep 2018
  6. Chen M, Gonzalez S, Vasilakos A, Cao H, Leung VC (2011) Body Area Networks: A Survey. Mob Netw Appl (MONET) 16(2):171–193CrossRefGoogle Scholar
  7. Chen KR, Lin Y–L, Yang M-C (2013) Medical communication device with a compact planar antenna and heterogeneous wireless resource for ubiquitous real-time healthcare monitoring. In: ICME international conference on complex medical engineering (CME), pp 224–227Google Scholar
  8. De D, Mukherjee A (2014) Femtocell based economic health monitoring scheme using mobile cloud computing. In: ieee international conference on advance computing conference (IACC), Gurgaon, India: IEEE, pp 385–390Google Scholar
  9. Gradl S, Kugler P, Lohmüller C, Eskofier B (2012) Real-time ECG monitoring and arrhythmia detection using android-based mobile devices. In: Annual international conference of the IEEE engineering in medicine and biology society, San Diego, CA, USA: IEEE, pp 2452–2455Google Scholar
  10. Grajales L, Nicolaescu IV (2006) “Wearable multisensor heart rate monitor.” International Workshop on Wearable and Implantable Body Sensor Networks. Cambridge, MA, USA: IEEE. 154–157Google Scholar
  11. Jabbar S, Ullah F, Khalid S, Khan M, Kijun, Han (2017) Semantic Interoperability in heterogeneous IoT infrastructure for healthcare. Wirel Commun Mobile Comput. CrossRefGoogle Scholar
  12. Lang M (2018) A low-complexity model-free approach for real-time cardiac anomaly detection based on singular spectrum analysis and nonparametric control charts. Technologies (MDPI) 6:26CrossRefGoogle Scholar
  13. Lemkaddem A, Proença M, Delgado-Gonzalo R, Renevey P, Oei I, Montano G, Martinez-Heras JA, Donati A, Bertschi M, Lemay M (2017) An autonomous medical monitoring system: Validation on arrhythmia detection. In: 39th annual international conference of the IEEE engineering in medicine and biology society (EMBC), Jeju Island, S. Korea: IEEE, pp 4553–4556Google Scholar
  14. Li S, Li Da Xu L, Wang X (2013) A continuous biomedical signal acquisition system based on compressed sensing in body sensor networks. IEEE Trans Ind Inf 9: 1764–1771CrossRefGoogle Scholar
  15. Luz EJDS, Schwartz WR, Cámara-Chávez G, Menotti D (2016) ECG-based heartbeat classification for arrhythmia detection: a survey. Comput Methods Progr Biomed (ScienceDirect, Elsevier) 127 144–164CrossRefGoogle Scholar
  16. Ma Y, Xiao D, Hang RRL, Zhao S, Zhao J, Zhang Y (2015) Android-based intelligent mobile robot for indoor healthcare. In: 17th international conference on e-health networking application & services (HealthCom), pp 472–474Google Scholar
  17. Milenkovic A, Otto C, Jovanov E (2006) Wireless Sensor Networks for Personal Health Monitoring: Issues and an Implementation. Comput Commun (Elsevier) 29:(13–14)Google Scholar
  18. Modarressi M, Yasoubi A, Modarressi M (2016) Low-power online ECG analysis using neural networks. In: Euromicro conference on digital system design (DSD). Limassol, Cyprus: IEEE, pp 547–552Google Scholar
  19. O’Donovan T, O’Donoghue J, Sreenan C, O’Reilly P, Sammon D, O’Connor K (2009) A context-aware wireless body area network. In: Proceedings of the pervasive health conference, London, UK: IEEEGoogle Scholar
  20. Otto C, Milenkovic A, Sanders C, Jovanov E (2005) System Architecture of a wireless body area sensor network for ubiquitous health monitoring. J Mob Multimedia (Rinton Press) 1(4):07–326Google Scholar
  21. Qidwai U, Shakir M (2011) Fuzzy detection of critical cardiac abnormalities using ECG data: a ubiquitous approach. In: 11th Hybrid Intelligent Systems Conference. Melacca, Malaysia: IEEEGoogle Scholar
  22. Qidwai U, Shakir M (2012) Embedded system design with filter bank and fuzzy classification approach to critical cardiac abnormalities detection. In: IEEE symposium on industrial electronics and applications, Bandung, Indonesia: IEEEGoogle Scholar
  23. Ullah S, Higgins H, Braem B, Latre B, Blondia C, Moerman I, Saleem S, Rahman Z, Kwak KS (2012) A comprehensive survey of wireless body area networks: On PHY, MAC, and network layers solutions. J Med Syst (PubMed SpringerLink) 36(3):1065–1094CrossRefGoogle Scholar
  24. Ullah F, Habib MA, Farhan M, Khalid S, Durrani MY, Jabbar S (2017) Semantic interoperability for big-data in heterogeneous IoT infrastructure for healthcare. Sustain Cities Soc (Elsevier) 34:90–96CrossRefGoogle Scholar
  25. Veeravalli B, Deepu CJ, Ngo D (2017) Real-time, personalized anomaly detection in streaming data for wearable healthcare devices. In: Khan SU, Zomaya AY, Abbas A (eds) Handbook of large-scale distributed computing in smart healthcare. Scalable computing and communications. Springer, Cham, pp 403–426CrossRefGoogle Scholar
  26. Xu H, Hua K, Zhu G-C, Huang J (2015) Adaptive forward error correction for ECG signal transmission for emotional stress assessment. In: 24th International Conference on computer communication and networks (ICCCN), Las Vegas, NV, USA: IEEE, pp 1–7Google Scholar
  27. Yuce MR (2010) Implementation of wireless body area networks for healthcare systems. Sens Actuators A Phys 162:116–129 (ScienceDirect Elsevier)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringQatar UniversityDohaQatar
  2. 2.Cyber Security Faculty, Cyber Intelligence and Security Department, College of Security and IntelligenceEmbry-Riddle Aeronautical UniversityPrescottUSA
  3. 3.Department of Computer ScienceNational Textile UniversityFaisalabadPakistan
  4. 4.Department of Pharmacology and New Drug Development Institute, School of MedicineChonbuk National UniversityChonbukSouth Korea
  5. 5.School of ScienceEdith Cowan UniversityPerthAustralia
  6. 6.Department of Computer EngineeringBahria UniversityIslamabadPakistan

Personalised recommendations