EmoPain(at)Home: Dataset and Automatic Assessment within Functional Activity for Chronic Pain Rehabilitation

While there is growing interest in developing tech-nology to support pain assessment, pain-related self-management, and healthcare personalisation, there are currently no datasets on nonverbal pain behaviour in the context of functional activities. To address this gap, we introduce the EmoPain(at)Home dataset which consists of motion capture data and self-reported pain, worry, and confidence intensities captured from people with chronic pain. The data were recorded during self-selected functional activities in the home, e.g. vacuuming. We include analysis of the dataset as well as baseline classification of pain levels with average F1 score of 0.61 for two classes. We additionally discuss inclusivity considerations for capture of datasets in naturalistic settings, based on lessons learnt within our study.