Pasi Liljeberg
Professor, Head of Department
pasi.liljeberg@utu.fi +358 29 450 2469 +358 40 543 3722 Vesilinnantie 5 Turku Office: 1st floor ORCID identifier: https://orcid.org/0000-0002-9392-3589 |
Biomedical engineering, Internet of Things, edge computing, Wearable sensors, Digital health technology, Health data analytics, Approximate and adaptive computing,
Research interest fall to the areas of biomedical engineering, health technology and edge computing. Please see also: https://healthtech.utu.fi
Pasi Liljeberg received MSc and PhD degrees in information and communication technology from the University of Turku, Turku, Finland, in 1999 and 2005, respectively. He received Adjunct professorship in embedded computing architectures in 2010. Currently he is working as a full professor in University of Turku in the Digital Health Technology unit. At the same time he serves as head of the Department of Computing, Faculty of Technology, University of Turku. His research interests are biomedical engineering, Internet of Things, edge computing, approximate and adaptive computing, wearable sensors, digital health technology and health data analytics. Liljeberg is the (co-)author of around 300 peer-reviewed publications.
My research interest fall in the field of biomedical engineering, health technology and Internet-of-Things. This is in the context wearable biomedical, wearable technology, applied machine learning, bio-signal processing, health informatics and edge computing. Special attention is paid to novel biomedical sensing applications, wearable computing, analytics, informatics, communication, and networking paradigms, especial focus onhealthcare and wellbeing applications.
Teaching interest in the field of Health Technology in general.
- Approximate Feature Extraction for Low Power Epileptic Seizure Prediction in Wearable Devices (2021) 2021 IEEE Nordic Circuits and Systems Conference (NorCAS) Taufique Zain, Kanduri Anil, Bin Altaf Muhammad Awais, Liljeberg Pasi
(A4 Refereed article in a conference publication ) - Energy-Performance Co-Management of Mixed-Sensitivity Workloads on Heterogeneous Multi-core Systems (2021)
- Proceedings of the Asia and South Pacific Design Automation Conference
(A4 Refereed article in a conference publication ) - Lightweight Photoplethysmography Quality Assessment for Real-time IoT-based Health Monitoring using Unsupervised Anomaly Detection (2021)
- Procedia Computer Science
(A4 Refereed article in a conference publication ) - Long-Term IoT-Based Maternal Monitoring: System Design and Evaluation (2021)
- Sensors
(A1 Refereed original research article in a scientific journal) - Pain assessment tool with electrodermal activity for postoperative patients: Method validation study (2021)
- JMIR mHealth and uHealth
(A1 Refereed original research article in a scientific journal) - Pain Recognition With Electrocardiographic Features in Postoperative Patients: Method Validation Study (2021)
- Journal of Medical Internet Research
(A1 Refereed original research article in a scientific journal) - Pregnant women's daily patterns of well-being before and during the COVID-19 pandemic in Finland: Longitudinal monitoring through smartwatch technology (2021)
- PLoS ONE
(A1 Refereed original research article in a scientific journal) - UBAR: User- and Battery-aware Resource Management for Smartphones (2021)
- ACM Transactions in Embedded Computing Systems
(A1 Refereed original research article in a scientific journal) - Being ‘A Google Mom’ or Securely Monitored at Home - Perceptions of Remote Monitoring in Maternity Care (2020)
- Journal of Advanced Nursing
(A1 Refereed original research article in a scientific journal) - Context-Aware Sensing via Dynamic Programming for Edge-Assisted Wearable Systems (2020)
- ACM Transactions on Computing for Healthcare
(A1 Refereed original research article in a scientific journal) - Continuous 7-month Internet of Things -based monitoring of health parameters of pregnant and Postpartum Women: prospective observational feasibility study (2020)
- JMIR Formative Research
(A1 Refereed original research article in a scientific journal) - Developing a pain intensity prediction model using facial expression: A feasibility study with electromyography (2020)
- PLoS ONE
(A1 Refereed original research article in a scientific journal) - 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 Refereed original research article in a scientific journal) - 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 Refereed book chapter or chapter in a compilation book) - Prospective Study Evaluating a Pain Assessment Tool in a Postoperative Environment: Protocol for Algorithm Testing and Enhancement (2020)
- JMIR Research Protocols
(A2 Refereed review article in a scientific journal ) - Robust ECG R-peak detection using LSTM (2020) SAC '20: Proceedings of the 35th Annual ACM Symposium on Applied Computing Laitala J., Jiang M., Syrjälä E., Naeini E.K., Airola A., Rahmani A.M., Dutt N.D., Liljeberg P.
(A4 Refereed article in a conference publication ) - RoSA: A Framework for Modeling Self-Awareness in Cyber-Physical Systems (2020)
- IEEE Access
(A1 Refereed original research article in a scientific journal) - Sleep tracking of a commercially available smart ring and smartwatch against medical-grade actigraphy in everyday settings: instrument validation study (2020)
- JMIR mHealth and uHealth
(A1 Refereed original research article in a scientific journal) - User-centric Resource Management for Embedded Multi-core Processors (2020)
- VLSI Design
(A4 Refereed article in a conference publication ) - Acute pain intensity monitoring with the classification of multiple physiological parameters (2019)
- Journal of Clinical Monitoring and Computing
(A1 Refereed original research article in a scientific journal)