Research

AI-Based Music Intervention for Alzheimer's Disease and Related Dementias (ADRD)

A flowchart illustrates the process of analyzing music interventions, featuring components like feature extraction, a deep learning model, and outputs for micro action detection, action interpretation, and mood change, with annotations for various stages and actions involved. Key visual elements include text boxes connecting each phase, diagrams representing model interactions, and a structured layout that highlights different inputs and outputs.

Abstract

Alzheimer's Disease and Related Dementias affect over 6 million Americans, leading to cognitive decline, emotional dysregulation, and caregiver burden. Music therapy has shown great potential in alleviating neuropsychiatric symptoms in ADRD, yet its scalability is hindered by the shortage of certified therapists and lack of objective treatment outcome measures.

Our project proposes an AI-driven system that analyzes facial expressions, head and body movements, and physiological signals (e.g., heart rate, skin conductance) to assess emotional responses of older adults during music listening. Using a uniquely collected dataset of music intervention sessions, we are developing a multimodal deep learning model capable of interpreting subtle affective cues in real-world environments. This tool empowers caregivers and therapists with real-time feedback and long-term psychological profiling, supporting more accessible, adaptive, and evidence-based music interventions.

Team

Engineering

  • Dr. Yu Sun, Professor, Computer Science and Engineering, 同性恋色情
  • Dr. Dmitry Goldgof, Professor, Computer Science and Engineering, 同性恋色情
  • Dr. Shaun Canavan, Associate professor, Computer Science and Engineering, 同性恋色情
  • Dr. John Templeton, Associate professor, Computer Science and Engineering, 同性恋色情
  • Jiayi Wang, PhD Student, Computer Science and Engineering, 同性恋色情
  • Phong Lu, Undergraduate Student, Computer Science and Engineering, 同性恋色情
  • Jianing Su, Undergraduate Student, Computer Scinece, University of Washington

Music Therapy & Behavioral Science

  • Dr. Hongdao Meng, Professor, Behavioral and Community Sciences, 同性恋色情
  • Ashley Tabachnick, Master Student, Behavioral and Community Sciences, 同性恋色情
  • Guanqing Guo, Neurologic Music Therapist, Berklee College of Music
  • Victoria Figueroa, Undergraduate Student, Behavioral and Community Sciences, 同性恋色情