Wearable technology for behavioral monitoring in pediatric cancer – A digital biopsychosocial approach to expand and personalize care for improved health and quality of life (WeCare)

Contenuto del lavoro

The project consortium brings together four interdisciplinary research groups from KU Leuven, integrating expertise in rehabilitation, oncology, health engineering, and human-computer interaction.

Prof. Dr. Sabine Verschueren heads the Research Group for Musculoskeletal Rehabilitation and is a prominent figure in exercise-based and digital rehabilitation, particularly in pediatric oncology. She has led several clinical trials and international collaborations, including the EU-funded MOVE-AGE and Horizon 2020 OACTIVE projects, and co-directs the KU Leuven Digital Society Institute (DigiSoc).

Prof. Dr. Anne Uyttebroeck is a leading pediatric hemato-oncologist at UZ Leuven and a key figure in survivorship care and clinical trials for childhood lymphoma and leukemia. Her work connects frontline oncology with long-term digital health innovations through projects like PanCareFollowUp and PanCareSurPass.

Prof. Dr. Jean-Marie Aerts, head of the M3-BIORES group in the Department of Biosystems, specializes in data-based mechanistic modeling and wearable technologies for health monitoring. He is co-director of DigiSoc and chair of the Department of Biosystems, with active roles in multiple spin-offs translating research into healthcare applications.

Finally, Prof. Dr. Bieke Zaman leads the Meaningful Interactions Lab (Mintlab) in the Faculty of Social Sciences and is Director of DigiSoc. Her research bridges communication sciences and human-computer interaction with a strong focus on ethical and participatory digital innovation, particularly with youth. Together, this consortium offers a robust foundation for translational research in digital health, rehabilitation, and patient-centered technologies.

Project

Children and adolescents and young adults (AYAs) diagnosed with cancer often face significant disruptions in physical activity (PA), sleep, and heightened stress levels, which can adversely impact their health and recovery during treatment and into survivorship. These behavioral aspects are frequently overlooked during routine medical visits, often due to time constraints faced by medical staff or the burden that lengthy questionnaires place on patients and their families. Consequently, discussions about these issues during follow-up consultations are minimal, and to date, no studies have comprehensively evaluated these factors, their interactions, or their overall impact on health of children or AYAs diagnosed with cancer. Wearable digital health technologies might offer a promising solution by continuously tracking behavior in real-world settings, providing data-driven insights that can be used to stimulate behavior change. However, implementing wearable technology to collect biometric data in this young and vulnerable population— both during hospital stays and in home settings—presents considerable technical, social, legal, and ethical challenges that must be carefully navigated and addressed.

Addressing these technical, social, legal, and ethical challenges is needed to facilitate widespread use of wearable healthcare technologies and requires transdisciplinary collaboration among engineers, healthcare providers, social scientists, ethicists, and patients and their parents to develop a framework to use wearables effectively and with reliable output but also in an ethical, user-friendly way, aligned with the unique needs of pediatric/AYA cancer patients. When the obstacles are overcome, wearable health devices and personalized mobile applications can facilitate a paradigm shift in pediatric oncology from a reactive, disease-centered approach to a proactive, patient-centered model.

WeCARE aims to advance the state of the art by developing and implementing an innovative, interdisciplinary framework for using medically approved wearable technology to assess the critical yet often overlooked factors PA, sleep and stress in young oncology patients. Our research is inherently pioneering, bridging rehabilitation and medical sciences, engineering, and communication/social sciences to create a biopsychosocial framework tackling the technical, social and ethical challenges to integrate digital technology for continuous, objective health behavior monitoring and to stimulate healthy lifestyle. Unlike existing studies that rely on self-reported measures or fragmented assessments, our approach leverages validated state-of-the-art wearable technology through a patient-centered lens, ensuring real-world applicability and clinical relevance. This involves refining and validating existing wearable devices through multi-disciplinary literature reviews, policy document analyses, stakeholder consultations, and experimental work to optimize feasibility, usability, and acceptability in young cancer patients. By integrating real-time health data into personalized oncology care, this study aims to transform patient management, shifting the paradigm from episodic clinical assessments to continuous, patient-centered behavior monitoring and healthy lifestyle stimulation.

The main focus of the technical PhD (this position) include validating wearable devices for monitoring sleep, stress, physical activity, and sedentary behavior; assessing the accuracy of EmbracePlus wearable in measuring physical activity and heart rate in young cancer patients; comparing sleep data from wearables to gold-standard polysomnography in a sleep lab; and validating stress measurements using controlled stress-induction paradigms and questionnaires. The role also involves further developing algorithms and writing an application to develop a wearable device functionality for monitoring patient behavior monitoring based on the gained insights.

Profile

We Value Candidates Who

• have a master degree in the field of data science, computer science, electronic engineering, biomedical engineering, bio-engineering, human health engineering or related field.
• have knowledge in the field of data analysis, time series analysis, machine learning and algorithm development.
• have knowledge on machine learning with Python or MATLAB.
• are very fluent in English, both spoken and written.
• possess strong analytical skills with the ability to collect, organize, analyse, and disseminate significant amounts of information with attention to detail and accuracy.
• are adept at report writing and presenting findings.
• are stress resistant and have passion for excellence.
• have genuine passion for developing technology solutions that contribute to improving human health and well-being
• are analytical, structured and result-oriented.
• are highly self-motivated, flexible, logical thinking, goal-oriented, team players.
• have the capability and interest to write scientific papers.
• can work collaboratively with the research team leader and team to produce excellent research results.
• can work with clinical partners and is willing to interact with patients.
• are willing to become an expert in data analysis and machine learning with state-of-the-art and novel methodologies, and to understand how to balance performance with complexity to achieve implementable technologies.
• are creative individuals and have a "persistent itch" to develop innovative solutions.
  
  

Offer

If you see yourself in the above description then we would really like to speak with you.

We recognize that this is challenging position and will pay accordingly. KU Leuven offers a young and dynamic working environment with access to state-of-the-art infrastructure, a competitive salary and outstanding health care benefits. The project offers a PhD position for 4 years which should be sufficient to complete a PhD on the topic. You start with a full-time position for 1 year, which can be extended to four years upon positive evaluation. Other working conditions can be found at https://www.kuleuven.be/personeel/jobsite/en/phd/phd-information.

Interested?

For more information please contact Prof. dr. ir. Jean-Marie Aerts, tel.: +32 16 32 14 34, mail: jean-marie.aerts@kuleuven.be.

Please Provide

• a motivation letter and CV with at least 2 contacts who can be contacted
• a PDF version of your Master thesis
• Full transcripts (overview of study results) of your Bachelor’s and Master’s studies. Please, provide preliminary results if the Master’s degree is not completed yet.
• if possible, a certificate of an English language test (IELTS or TOEFL)
  
  

You can apply for this job no later than August 31, 2025 via the online application tool

KU Leuven strives for an inclusive, respectful and socially safe environment. We embrace diversity among individuals and groups as an asset. Open dialogue and differences in perspective are essential for an ambitious research and educational environment. In our commitment to equal opportunity, we recognize the consequences of historical inequalities. We do not accept any form of discrimination based on, but not limited to, gender identity and expression, sexual orientation, age, ethnic or national background, skin colour, religious and philosophical diversity, neurodivergence, employment disability, health, or socioeconomic status. For questions about accessibility or support offered, we are happy to assist you at this email address.

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