# A Gesture-Powered Software Platform of Neurologic Music Therapy Games and Puzzles: To Stimulate Neuroplasticity and Prolong Functional Independence in Individuals Diagnosed with Alzheimer's Disease

> **NIH NIH R43** · OUTLIER TECHNOLOGY, LLC · 2023 · $504,505

## Abstract

Abstract
 The inclusion of music therapy into a total treatment modality can be used to improve the cognitive, physical,
emotional, and social outcomes of patients diagnosed with neurological aging disorders, such as Alzheimer’s
Disease (AD). Moreover, the healing benefits of music therapy and music-based interventions may be optimized
when the patient is actively engaged in the process of creating music (composing, singing, moving), as opposed
to sole reliance on receptive or passive music listening. The process of creating music has been shown to
enhance neuroplasticity, reduce pain, and promote mental wellness. AD, in particular, as a neurodegenerative
disease characterized by adverse neuropathological changes that impair neural connectivity and the brain’s
natural ability to repair itself, is a prime candidate for the therapeutic neurological benefits that arise from creating
music. Unfortunately, however, those who stand to gain the most from creating music often find the challenging
process of relearning, learning, and/or manipulating a musical instrument to be impractical.
 Outlier Technology (Outlier) seeks to address this issue by developing a novel, Neurologic Music Therapy
(NMT)-based software platform to help modernize the rehabilitation and habilitation of function & well-being
among people suffering from AD. This next-generation approach to NMT will offer the medical community an
innovative new way to enhance neuroplasticity and mitigate cognitive decline. The hallmark of this platform is a
proprietary algorithm which utilizes computer vision as an input modality to translate body movements into an
interactive, aesthetically pleasing musical experience integrated with a data-driven curriculum of NMT-based
puzzles and games designed in collaboration with Board-Certified Music Therapists (MT-BCs) to target
therapeutic objectives. This platform can be utilized by therapists to augment their traditional treatment regimens
or by patients who do not have regular access to therapy resources but seek the potential benefits of such use.
 This proposal describes the development of a gesture-powered “smart instrument” that combines an
interactive, adaptive, and therapeutic music creation experience with structured data analytics. Musical data from
studio musicians will be sampled, analyzed, and mapped onto an aesthetically refined decision matrix that
produces pleasing, software-generated music that may be customized to the user’s personal tastes. Computer
vision will be used to map physical movements onto sensible musical outcomes to develop a “smart instrument”
with intuitive, motion-powered haptic feedback. A curriculum of NMT-based games and puzzles that utilize this
instrument will be developed with neuroscientists and MT-BCs to stimulate neuroplasticity and prolong functional
independence. We will also integrate a data portal which allows the practitioner to record real-time patient events
and notes about session progress, and access org...

## Key facts

- **NIH application ID:** 10611831
- **Project number:** 1R43AG081111-01
- **Recipient organization:** OUTLIER TECHNOLOGY, LLC
- **Principal Investigator:** Peter Gray
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $504,505
- **Award type:** 1
- **Project period:** 2023-02-01 → 2025-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10611831

## Citation

> US National Institutes of Health, RePORTER application 10611831, A Gesture-Powered Software Platform of Neurologic Music Therapy Games and Puzzles: To Stimulate Neuroplasticity and Prolong Functional Independence in Individuals Diagnosed with Alzheimer's Disease (1R43AG081111-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10611831. Licensed CC0.

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