Developing a Multimodal Cancer Pain Database to Support AI-Based Automatic Pain Assessment

SENSAI: Seeing, hEaring, seNsing: Smart, Effortless and Objective Pain Assessment With Mobile AI Technology - DataBase Development

The goal of this observational study is to collect short video and sound recordings of people with cancer to create a secure database that can be used in future research to develop an artificial intelligence (AI) tool for pain assessment. The main aim is to build a large, high-quality collection of audiovisual data showing how people with cancer express themselves when they do and do not have pain.

Participants will include adults with cancer who are admitted to the oncology ward for pain treatment and a control group admitted for chemotherapy who have no pain. After giving consent, participants will:

• Be recorded on video (from the shoulders up) for up to 60 seconds while reading a short sentence and describing their pain or daily experience.
• Complete a short questionnaire about their mood and pain expression.
• Allow researchers to collect some information from their medical record, such as their pain score, medications, and cancer type.

These recordings will be securely stored and used to create a database for future AI research. No medical tests, new treatments, or extra hospital visits are involved. This study will provide the foundation for developing future AI-based tools that could support doctors and patients in monitoring and managing pain more accurately and easily.

This is a prospective, single-centre database development study conducted at the Erasmus MC Cancer Institute. The purpose of the study is to create a high-quality audiovisual database for future research on automated pain assessment in people with cancer. The database will include short (up to 60 seconds) video and sound recordings of participants' facial and vocal expressions, alongside relevant clinical and demographic information.

The study will include two groups: (1) adults admitted to the oncology ward for cancer-related pain (pain group) and (2) adults admitted for chemotherapy who report no pain (control group). Participants will provide written informed consent before any recording takes place.

Each participant will be recorded from the shoulders up while reading a neutral prompt and, if applicable, describing their pain experience. The recordings will be securely stored in compliance with the General Data Protection Regulation (GDPR). In addition, researchers will collect secondary parameters from the participants' electronic medical record, such as pain scores, analgesic use, tumour type, and clinical status. Participants in the pain group may be recorded on multiple days during admission, while controls will be recorded once.

The audiovisual recordings will be used to extract facial and vocal features (e.g., Facial Action Units, voice parameters) with open-source software such as OpenFace and OpenSmile. These features will form the foundation for future artificial intelligence (AI) model development aimed at automatic pain assessment.

No experimental interventions, additional clinical procedures, or diagnostic tests are part of this study. The study carries minimal risk to participants, primarily related to the handling of identifiable audiovisual data. All data will be stored on Erasmus MC's secure Research Storage & Compute infrastructure, accessible only to authorised researchers.

The resulting dataset will be used to develop and validate AI models that can objectively estimate pain intensity from audiovisual data, supporting more accurate and continuous pain monitoring in clinical care.

Inclusion Criteria:

• Adult patients (≥18 years)
• Diagnosed with cancer, active
• Able to communicate verbally in Dutch or English
• Able to provide written informed consent.
• Pain group specific:
• Experiencing pain related to cancer
• Admitted to the hospital due to pain
• Control group specific:
• Not experiencing pain (NRS = 0)
• Admitted to the hospital for chemotherapy

Exclusion Criteria:

• Cognitive, physical, or medical limitations that prevent participation in the audiovisual recording sessions or affect facial expressions or voice (e.g. facial paralysis, tracheostomy, severe speech impairment).
• Critical illness or end-of-life care where participation would impose an additional burden.
• Experiencing pain not associated with cancer
• Infectious isolation precautions that prevent safe data collection