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Exploring Therapeutic Effects in Music and Video Playlist in Active and Passive Music Therapy Approaches
The Hong Kong University of Science and Technology
Department of Computer Science and Engineering
PhD Thesis Defence
Title: "Exploring Therapeutic Effects in Music and Video Playlist in Active
and Passive Music Therapy Approaches"
By
Miss Man Hei LAW
Abstract:
The prevalence of individuals suffering from mental health issues is on the
rise, now as common as catching the flu. Human resources in mental health
care remain limited across mental health care units. How can we provide 24/7
services and a non-invasive approach in such situations? This thesis
investigates the therapeutic benefits of algorithmic music and music video
selection applied to multisensory and single-sensory passive music therapy
approaches. This thesis also covers with highlights on walking, music video,
and music listening approaches.
The algorithmic selection methods are based on the energy and mood of music,
considering music in four general categories: Happy, Angry, Sad, and
Relaxed. The study of active music therapy approach integrates single
category music selection into daily walking routines through our research
app, "Emotion Equalization App". It reveals how categorized music impacts
participants' emotions, even manipulating the use of negative mood music.
Additionally, it explores the influence of music videos on emotional
well-being, emphasizing the strategies to enhance emotional impact including
limiting music video consumption and using dynamic sequencing methods for
distraction and relaxation. Moreover, the passive listening approaches also
promote mental health and mood improvements across severity of depression
and anxiety. By investigating the impact of these approaches on mental
health balance, particularly in depression and anxiety conditions, this
thesis aims to provide the directions of how digital music therapy
interventions can be implemented for supporting mental health care agencies
in 24/7 mode and staying connected and being responsive to our users'
emotions, daily routines, and current trends.
Date: Monday, 12 May 2025
Time: 4:00pm - 6:00pm
Venue: Room 3494
Lifts 25/26
Chairman: Prof. Janet Hui-wen HSIAO (SOSC)
Committee Members: Prof. Andrew HORNER (Supervisor)
Prof. Gary CHAN
Dr. Arpit NARECHANIA
Prof. Keith LAU (LIFS)
Dr. Dan LIN (EdUHK)