MIE Department: University of Massachusetts Amherst/Unobtrusive Continuous Chronic Pain Monitoring and Assessment for LTC Residents with ADRD Using Multimode Sensing and Deep Learning

The team integrates vision, biosignals, and wearable data with interpretable deep learning to monitor and assess chronic pain in LTC settings.

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Led by Xian Du at UMass Amherst, the project builds an intelligent model that combines computer vision, body movement, facial expression, and wearable biosignals to assess chronic pain in long-term care residents with Alzheimer’s disease and related dementias. Using an interpretable Vision Transformer approach and sensor fusion, the system aims for objective, automatic, and real-time monitoring that can inform earlier care and improved treatment. The work also considers expansion to community-dwelling older adults receiving home care.

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