What we do
About our project
Understanding Cancer Pain
Pain is one of the most common and distressing symptoms for people with cancer. It negatively affects physical and emotional well-being, daily functioning, and quality of life. Despite medical progress, pain often remains undertreated because assessing it accurately is still difficult. Current methods rely on short conversations or numerical scores that depend on how well patients can express their pain at that moment. Especially in the outpatient setting, where contact with care teams is less frequent, important pain experiences are often missed.
Our vision
The SENSAI project aims to improve how pain is recognised and managed in oncology. We are developing a mobile application that uses artificial intelligence (AI) to interpret a patient’s facial expressions and voice when they describe their pain. Together with self-reported pain scores and mood questions, these signals help provide a completer and more standardised picture of the pain experience and make it possible to monitor pain more continuously between hospital visits.
A collaborative and ethical approach
SENSAI is built through close collaboration between researchers, healthcare specialists, engineers, and patients. We follow a human-centred design process in which feedback from end-users guides every step of development. This ensures the tool fits naturally into daily care, respects privacy, and remains understandable and trustworthy for both patients and clinicians.
Expected impact
By combining state-of-the-art technology with clinical expertise, SENSAI aims to empower patients to reflect on their pain, give doctors clearer insight into its severity and pattern, and support more personalised and timely pain management. Ultimately, the project strives to improve comfort and communication throughout the cancer journey.Our research focus
Start of the project
Unlike many technical projects, SENSAI begins with people rather than algorithms. Early interviews with oncologists have shown how complex it can be to interpret pain from patients’ descriptions and how easily important cues are missed. These insights guide the design of the tool, ensuring that technology supports – rather than replaces – the personal interaction between patients and clinicians. Interviews with patients are currently underway to explore their experiences with cancer pain and their needs for communication and self-management support.The SENSAI application
The SENSAI app enables patients to record short, guided sessions in which they describe their pain and answer a few brief questions about pain intensity and mood. The app captures both facial expressions and voice characteristics while the patient speaks. These recordings are processed by the AI model to identify patterns associated with different pain levels. Over time, the app will offer patients a simple visual overview of their pain experiences, helping them recognise changes and communicate more effectively with their healthcare team.The SENSAI cancer pain database
To train and validate the AI model, SENSAI is establishing a secure multimodal cancer pain database at Erasmus MC. This data collection study is registered at ClinicalTrials.gov. This database contains synchronised recordings of facial video, voice audio, and self-reported pain and mood data collected in a controlled clinical environment. All data are handled according to strict ethical and privacy standards. In the future, anonymised data will be made available to collaborating researchers, supporting transparency and further innovation in automatic pain assessment.The SENSAI AI model
The SENSAI AI model integrates information from facial and vocal features with patients’ self-reported pain scores to estimate pain intensity levels. Its design focuses on transparency and explainability, ensuring that clinicians can understand and trust how the model reaches its conclusions. Future developments will include analysis of spoken content and emotional tone to better capture the complex and multidimensional nature of cancer pain. Eventually we will also make our code publicly available to collaborating researchers.Funds & Grants
Collaborations
Internal collaborations
The SENSAI project is carried out in the Department of Medical Oncology at Erasmus MC.
External collaborations
The project is carried out in collaboration with the Multi-Actor Systems group at Delft University of Technology (TU Delft), where several members of the research team are affiliated. This partnership contributes expertise in human-centred design and state-of-the-art artificial intelligence.
Furthermore, the mobile application is developed together with Innovattic, a software company based in Delft, the Netherlands. See Innovattic.com for more information.
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Publications
Kamsteeg M. J. (2025, October 9). Perspectieven van oncologen op pijnbeoordeling en AI-ondersteunde automatische pijnbeoordeling bij kanker: een explorerende interviewstudie [Conference presentation] Nederlands Vlaamse Wetenschapsdagen Palliatieve Zorg
Kamsteeg M.J. (2025, November 12-14). Towards an Artificial Intelligence Based Multimodal Pain Assessment Tool for Cancer-Related Pain: Foundations from the SENSAI Project [Conference poster] ESMO Artificial Intelligence & Digital Oncology
Our team
Coordinating researcher
m.kamsteeg@erasmusmc.nl
Prof. Karin van der Rijt – Medical Oncologist & Professor Palliative Care – Erasmus MC
Dr. Wendy Oldenmenger – Assistant Professor Palliative Care – Erasmus MC
Dr. ir. Helma Torkamaan – Assistant Professor AI for Health Systems – TU Delft
Dr. ir. Mark Mulder – Medical Oncologist – Erasmus MC
