SPECIAL SECTION ON WEARABLE AND IMPLANTABLE DEVICES AND SYSTEMS Received April 3, 2018, accepted April 24, 2018, date of publication May 9, 2018, date of current version December 31, 2018. Digital Object Identifier 10.1109/ACCESS.2018.2831209 An Automated Remote Cloud-Based Heart Rate Variability Monitoring System AHMED FAEQ HUSSEIN 1 , (Member, IEEE), ARUN KUMAR N 2 , (Member, IEEE), MARLON BURBANO-FERNANDEZ 3 , GUSTAVO RAMÍREZ-GONZÁLEZ 3 , ENAS ABDULHAY 4 , AND VICTOR HUGO C. DE ALBUQUERQUE 5 , (Member, IEEE) 1 Bio-Medical Engineering Department, Faculty of Engineering, Al-Nahrain University, Baghdad 10072, Iraq 2 Department of Electronics and Instrumentation, SASTRA University, Thanjavur 613401, India 3 Telematics Department, University of Cauca, Popayán 76520000, Colombia 4 Department of Biomedical Engineering, Faculty of Engineering, Jordan University of Science and Technology, Irbid 22110, Jordan 5 Graduate Program in Applied Informatics, University of Fortaleza, Fortaleza 60811, Brazil Corresponding author: Gustavo Ramírez-González (gramirez@unicauca.edu.co) ABSTRACT The online telemedicine systems are helpful since they provide timely and effective healthcare services. Such online healthcare systems are usually based on sophisticated and advanced wearable and wireless sensor technologies. A rapid technological growth has improved the scope of many remote health monitoring systems. Here, the researchers employed a cloud-based remote monitoring system for observing the health status of the patients after monitoring their heart rate variability. This system was developed after considering many factors like the ease of application, costs, accuracy, and the data security. Furthermore, this system was also conceptualized to act as an interface between the patients and the healthcare providers, thus ensuring a two-way communication between them. The major aim of this paper was to provide the best healthcare monitoring services to the people living in the remote areas, which was otherwise very difficult owing to the small doctor-to-patient ratio. The researchers also analyzed their monitoring system using two different databases. First comes from MIT Physionet database i.e., the MIT-BIH sinus rhythm and the MIT-St. Petersburg. While the second database was collected after monitoring 30 people who were asked to use these wearable sensors. After analyzing the performance of the proposed scheme, the obtained results for accuracy, sensitivity, and specificity were 99.02%, 98.78%, and 99.17%, respectively. The achieved results concluded that the proposed system was quite reliable, robust, and valuable. Also, the data analysis revealed that this system was very convenient and ensured data security. In addition, this developed monitoring system generated warning messages, directed towards the patients and the doctors, during some critical situation. INDEX TERMS Telemedicine, cloud computing, IoT, ECG, HRV analyzing, QRS, homomorphic encryption. I. INTRODUCTION In the past few decades, researchers and scientists have made massive developments in the field of medical and healthcare services. Also, decrease in the costs of wireless communi- cation and integration of several health monitoring systems into the common devices such as smartphones, have also helped in tackling problems like scarce medical facilities and resources [1], [2]. The integration of the wearable sensors with the mobile communication systems has helped in shifting the pro- vision of the healthcare services from a clinic-centric level to a patient-centric level. This process is called as telemedicine [3], [4]. Based on the perspective, telemedicine is described using 2 different concepts: the first, live commu- nication concept requires the presence of the patient and the doctor, along with a high data quality. The second concept is the data storage and transfer concept, wherein the doc- tors can access and share the patient’s medical data like the acquired vital sign data, biomedical videos or images with the specialists in other hospitals [5]. However, an increased sharing of the vital patient data can lead to many secu- rity concerns associated with the patient’s privacy. Many factors were listed by the Health Insurance Portability and Accountability Act (HIPAA) for defining the measures that could be employed while protecting the health informa- tion of the patients. But, this list is still incomplete and VOLUME 6, 2018 2169-3536  2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. 77055