The PhD position is part of the interdisciplinary research project CardiacCare@Home, funded by the Dutch Research Council (NWO, Perspectief programme). The project aims to improve care for heart failure patients by relocating monitoring and rehabilitation to their home environment. Through co-creation involving patients, healthcare professionals, and industry partners, CardiacCare@Home develops innovative solutions integrating wearable data, biomarkers, and tele-rehabilitation. This includes continuous monitoring of physical signals using multiple wearable devices from industrial patterns, combined with machine learning algorithms to predict deterioration. However, the resulting data streams overwhelm clinicians who struggle to extract meaningful insights. This is a key problem to address with concrete implications on how remote patient monitoring (RPM) will be accepted and adopted by patients and healthcare professionals alike.
Your research will focus on bridging the critical gap by designing and developing data sensemaking tools that transform complex physiological and behavioral data into actionable insights for diverse stakeholders. The main goal is to design data sensemaking tools and user-centered human-AI interfaces that facilitate informed healthcare decisions for all involved stakeholders. Thereby, we want to bridge technological innovations (WP1), tele-rehabilitation strategies (WP2), and data platform integration (WP3). The project offers an exciting opportunity to contribute to cutting-edge research at the intersection of Interaction Design (IxD), Human-Computer Interaction (HCI), and Artificial Intelligence (AI), with the potential to create transformative societal impact by revolutionizing remote patient monitoring and establishing new paradigms for home-based healthcare delivery.
InformationAs a PhD candidate, your tasks will include:
- Designing and developing a data sensemaking tool providing clear and actionable insights into patient behaviors and physiological signals.
- Creating human-AI collaborative interfaces and visualizations to effectively communicate insights from machine learning models based on wearable and biomarker data.
- Collaborating closely with consortium partners to identify stakeholder needs and align these across the different work packages.
- Developing and prototyping novel interaction techniques that translate AI capabilities into meaningful, accessible, and engaging collaborative experiences for healthcare stakeholders
- Integrating developed solutions into an eHealth platform, ensuring usability for clinicians, physiotherapists, and patients.
- Conducting user studies and iterative design processes to validate and refine Human-AI interaction concepts in real healthcare settings.
The PhD will be under the supervision by Prof. Dr. Hareld Kemps, Dr. Janet Huang, and Dr. Mathias Funk, collaborating closely with clinical and industrial partners across the Netherlands.
Prospective starting date: September 2025.