➣ Music has a powerful effect on our emotions, and this effect can be harnessed for therapeutic purposes.
Music therapy can even surpass cultural boundaries and work for people of all backgrounds.
Such personalized music therapy has the potential to improve mental health, manage pain, aid in substance abuse recovery, etc.
➣ Technological advancements like Affective Algorithmic Composition (AAC) and facial recognition offer new possibilities for personalized music therapy.
Facial recognition technology provides a cost-effective and versatile way to measure emotions in real-time for music therapy applications.
AAC algorithms can feasibly generate music tailored to an individual.
There is potential in the marriage of music and technology through Affective Algorithmic Composition (AAC) and facial recognition. By harnessing the science of musical impact and the efficiency of algorithms, such a system has certain purpose beyond sole entertainment in crucial sectors like mental health therapy, pain management, and substance abuse recovery.
This personalized approach holds significant advantages over generic interventions and transcends cultural boundaries, as the literature suggests, and while challenges remain in refining AI-based emotion recognition and tailoring music in real-time with the most efficient/high-yield algorithms, the potential to create a strong "biofeedback symphony" is immense.
There is a need...
to improve the accuracy and efficiency of facial recognition algorithms, which will be particularly helpful for real-time emotion detection in music therapy applications.
to improve AAC algorithms for efficient processing and seamless music generation, especially within a music therapy setting. Generating high-quality music in real-time based on emotional input is a complex task.
for additional research with a more diverse age group and broader demographic representation to strengthen the generalizability of the findings, as the dominant teenage demographic of this study has potentially skewed some results.
Conducting clinical trials to evaluate the effectiveness of personalized music therapy using AAC and facial recognition compared to traditional methods may prove to be a fruit-bearing venture.
There is the possibility of incorporating additional data sources beyond facial expressions, such as physiological responses, for a more complete understanding of emotional state. "The face is certainly a great indicator, but body language is something to look out for." --Mr. Richard McCready, March 2024
More research in the future will be focused on the potential of music technology for intervention, including therapeutic music for enhanced medical care and quality of life. There is immense potential in musical interventions for patients suffering from Alzheimer’s, dementia, neuro-cognitive disorders, and chronic/terminal illnesses.