Arman Anzanpour
PhD Candidate
Department of Computing arman.anzanpour@utu.fi Vesilinnantie 5 Turku : 452D |
Internet of Things; Fog computing; Remote health monitoring; Wearables; Biosignals acquisition and analysis; Embedded electronics
Internet of Things, remote health monitoring, wearables, and resource management in IoT systems
Arman Anzanpour is a researcher at the “Health Technology” group, Department of Computing, University of Turku. He is currently a Ph.D. candidate studying IoT-based remote health monitoring systems with a focus on resource management. He received his Master in Biomedical Engineering from Amirkabir University of Technology. His research fields include medical early warning systems, Internet of Things, fog computing, remote patient monitoring, medical wearables, and embedded electronics. Collaborating with several projects and research groups, he is practically engaged with the engineering design and implementation of wireless sensor networks, wearable devices, IoT system architectures, mobile/web application development, and biosignals acquisition systems.
A patient monitoring procedure, named Early Warning Score, is in-use in hospitals for the prevention of most sudden deterioration and has been proven to reduce the risk of consequential death or disability by 75%. The aim of this research is to implement the same life-saving technique for chronic in-home patients which requires performing the same in-hospital medical measurements via a wearable device worn by in-home patients during their daily activities. Out of the hospital, the main challenges are the management of the resources and the accuracy of the measurements. A certain level of intelligence, self-awareness, and context-awareness is required in a remote patient monitoring system to maximize the continuity of the monitoring and deal with such challenges. This research is based on an IoT technology that enables biomedical and context sensing in the sensor layer, local processing and notifications in the fog layer, and data storage, processing, and artificial intelligence in the cloud layer.
- System Engineering Labs, Teacher for the IoT section, University of Turku, 2021
- Medical Instrumentation, Teaching Assistant of Tero Koivisto, University of Turku, 2020 & 2021
- IoT Systems: Design And Applications, Teaching Assistant of Dr. Matti Kaisti, University of Turku, 2019
- IoT Systems: Design And Applications, Teaching Assistant of Prof. Pasi Liljeberg, University of Turku, 2019
- Embedded IoT Programming, Teaching Assistant of Prof. Pasi Liljeberg, University of Turku, 2017
- Cyber-Physical Systems, Teaching Assistant of Prof. Amir Mohammad Rahmani, University of Turku, 2015 & 2016
- Introduction to Raspberry Pi board, University of Turku, 2015
- DELTA 2015 Summer School on Internet of Things for Health, Teaching Assistant of Prof. Amir Mohammad Rahmani and Dr. Rajeev Kumar Kanth, University of Turku, 2015
- Fundamentals of Web Design, Ferdowsi University of Mashhad, Art Faculty, 2010
- PHP: Web Programming Language, College of Ferdowsi University of Mashhad, 2004
- Visual Basic Programming, College of Ferdowsi University of Mashhad, 2003
- MATLAB Programming, College of Ferdowsi University of Mashhad, 2003
- Application of Computer in Material Science, Teaching Assistant of Prof. Ahad Zabet, Ferdowsi University of Mashhad, Engineering Faculty, 2003
- Bed sensor ballistocardiogram for non-invasive detection of atrial fibrillation: a comprehensive clinical study (2025)
- Physiological Measurement
- Continuous Radar-based Heart Rate Monitoring using Autocorrelation-based Algorithm in Intensive Care Unit (2025)
- IEEE Journal of Biomedical and Health Informatics
- Dynamic Resource Management in IoT-Enabled Health Monitoring Systems (2025) Anzanpour, Arman
- Evaluating Piezoelectric Ballistocardiography for Post-Surgical Heart Rate Monitoring (2024)
- Computing in Cardiology
- An energy-efficient semi-supervised approach for on-device photoplethysmogram signal quality assessment (2023)
- Smart Health
- Confidence-Enhanced Early Warning Score Based on Fuzzy Logic (2022)
- Mobile Networks and Applications
- Detecting Atrial Fibrillation With a Wearable Device (2022)
- Computing in Cardiology
- Exploring computation offloading in IoT systems (2022)
- Information Systems
- Identification of Myocardial Infarction by High Frequency Serial ECG Measurement (2022)
- Computing in Cardiology
- Personal mental health navigator: Harnessing the power of data, personal models, and health cybernetics to promote psychological well-being (2022)
- Frontiers in Digital Health
- Context-Aware Sensing via Dynamic Programming for Edge-Assisted Wearable Systems (2020)
- ACM Transactions on Computing for Healthcare
- Edge-Assisted Control for Healthcare Internet of Things: A Case Study on PPG-Based Early Warning Score (2020)
- ACM Transactions on the Internet of Things
- Optimizing Energy Efficiency of Wearable Sensors Using Fog‐assisted Control (2020) Fog Computing: Theory and Practice Delaram Amiri, Arman Anzanpour, Iman Azimi, Amir M. Rahmani, Pasi Liljeberg, Nikil Dutt, Marco Levorato
- Acute pain intensity monitoring with the classification of multiple physiological parameters (2019)
- Journal of Clinical Monitoring and Computing
- Analysis of performance and energy consumption of wearable devices and mobile gateways in IoT applications (2019) COINS '19 Proceedings of the International Conference on Omni-Layer Intelligent Systems Nakhkash M., Gia T., Azimi I., Anzanpour A., Rahmani A., Liljeberg P.
- Dynamic Computation Migration at the Edge: Is There an Optimal Choice? (2019) GLSVLSI '19: Proceedings of the 2019 on Great Lakes Symposium on VLSI Sina Shahhosseini, Iman Azimi, Arman Anzanpour, Axel Jantsch, Pasi Liljeberg, Nikil Dutt, Amir M. Rahmani
- Energy-efficient and reliable wearable internet-of-things through fog-assisted dynamic goal management (2019)
- Procedia Computer Science
- Edge-Assisted Sensor Control in Healthcare IoT (2018) IEEE GLOBECOM 2018 Amiri Delaram, Anzanpour Arman, Azimi Iman, Levorato Marco, Rahmani Amir M., Liljeberg Pasi, Dutt Nikil
- Empowering Healthcare IoT Systems with Hierarchical Edge-based Deep Learning (2018) 2018 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) Iman Azimi, Janne Takalo-Mattila, Arman Anzanpour, Amir M. Rahmani, Juha-Pekka Soininen, Pasi Liljeberg
- Enhancing the Self-Aware Early Warning Score System through Fuzzified Data Reliability Assessment (2018)
- Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering