Arman Anzanpour
Postdoctoral Researcher
Department of Computing arman.anzanpour@utu.fi Vesilinnantie 5 Turku Työhuone: 452D ORCID-tunniste: https://orcid.org/0000-0002-7614-0232 |
Healthcare IoT; Remote Patient Monitoring; Wireless Biosignal Data Acquisition; Biosignal Processing; Edge Computing; IoT-based Early Warning Score Systems
Healthcare IoT; Wearable Electronics; Biosignal Processing; Remote Patient Monitoring; Energy Optimization; Embedded Systems; Edge Computing; Medical Device Design; Predictive Healthcare;
I am a Postdoctoral Researcher in the Health Technology Lab within the Department of Computing at the University of Turku. I completed my PhD in Information and Communication Technology at the same university. My work lies at the intersection of computer science, electronic engineering, and clinical healthcare, with a focus on developing practical technologies for real-world health monitoring.
My primary research centers on IoT-based health monitoring systems, edge and fog computing architectures, and remote patient monitoring solutions for home environments. I am particularly motivated by the engineering aspects of this work, specializing in the design and implementation of complete IoT system loops, from raw data acquisition and secure data transmission to real-time analysis and response.
Over the past decade, I have contributed to research, development, and system design across several major projects: NewLife, RM4Health, Moore4Medical, APPLAUSE, SAFE, IoCT-CARE, and SPA. My current work focuses on the EU-funded NewLife project, where I develop smart IoT-based data systems tailored for maternal and newborn health monitoring.
To date, my research has resulted in more than 40 peer-reviewed publications, which have collectively received over 3,000 citations. I have been honored with three Best Paper Awards at international conferences, as well as Research Excellence Awards from the Nokia Foundation and the Finnish Foundation for Technology Promotion (TES), recognizing my contributions to remote health monitoring system design and development.
- Healthcare Internet of Things (IoT) and Internet of Medical Things (IoMT)
- Edge and fog computing architectures for real-time medical data processing
- Medical Early Warning Systems (EWS) and predictive healthcare algorithms
- Design and development of medical wearables and wireless sensor networks
- Bio-signal acquisition and processing
- Energy optimization and resource management in resource-constrained embedded systems
- Data science and big data engineering for high-frequency biomedical signals
- Maternal and newborns health monitoring solutions
- Assessing the impact of signal quality on heart rate detection from long-term clinical wrist PPG under varying cardiac rhythms (2026)
- Biomedical Signal Processing and Control
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Low-complexity fetal heart rate monitoring from carbon-based single-channel dry electrodes maternal electrocardiogram (2026)
- Physiological Measurement
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Randomized trial of smartphone application and bed sensor for atrial fibrillation detection in high-risk patients (2026)
- Scientific Reports
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - A Novel Wearable-Based Fetal Movement Localization System Using Machine Learning (2025)
- Proceedings of IEEE Sensors
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Bed sensor ballistocardiogram for non-invasive detection of atrial fibrillation: a comprehensive clinical study (2025)
- Physiological Measurement
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Continuous Radar-based Heart Rate Monitoring using Autocorrelation-based Algorithm in Intensive Care Unit (2025)
- IEEE Journal of Biomedical and Health Informatics
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Dynamic Resource Management in IoT-Enabled Health Monitoring Systems (2025) Anzanpour, Arman
(G5 Artikkeliväitöskirja) - Lightweight ResNet-Based Deep Learning for Photoplethysmography Signal Quality Assessment (2025)
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Evaluating Piezoelectric Ballistocardiography for Post-Surgical Heart Rate Monitoring (2024)
- Computing in Cardiology
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - An energy-efficient semi-supervised approach for on-device photoplethysmogram signal quality assessment (2023)
- Smart Health
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Confidence-Enhanced Early Warning Score Based on Fuzzy Logic (2022)
- Mobile Networks and Applications
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Detecting Atrial Fibrillation With a Wearable Device (2022)
- Computing in Cardiology
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Exploring computation offloading in IoT systems (2022)
- Information Systems
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Identification of Myocardial Infarction by High Frequency Serial ECG Measurement (2022)
- Computing in Cardiology
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Personal mental health navigator: Harnessing the power of data, personal models, and health cybernetics to promote psychological well-being (2022)
- Frontiers in Digital Health
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Context-Aware Sensing via Dynamic Programming for Edge-Assisted Wearable Systems (2020)
- ACM Transactions on Computing for Healthcare
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - 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
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - 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
(A3 Vertaisarvioitu kirjan tai muun kokoomateoksen osa) - Acute pain intensity monitoring with the classification of multiple physiological parameters (2019)
- Journal of Clinical Monitoring and Computing
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - 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.
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)



