Electronic Thesis and Dissertation Repository

Degree

Doctor of Philosophy

Program

Health and Rehabilitation Sciences

Supervisor

Holmes, Jeffrey D.

2nd Supervisor

Grahn, Jessica, A.

Co-Supervisor

Abstract

The purpose of this study was to identify the ability of individuals with Parkinson’s disease (PD) to acquire different rhythmic complexity levels through individual home-based Improvised Active Music Therapy (IAMT) sessions. The study aimed to identify whether higher acquisition of rhythmic complexity levels improved gait performance, as well as beat perception and production abilities. In this single subject multiple baseline design, the study measured the ability of four right-handed participants with PD to acquire greater density of syncopation, as a measure of rhythmic complexity levels, while playing uninterrupted improvised music on a simplified electronic drum-set. An accredited music therapist led each session with an acoustic guitar. The study described how higher density of syncopation levels presented in participants’ playing related to not only gait performance, and beat perception and production abilities, but also to other music measurements. The participants’ music content was transformed into digital music data in real time using Musical Instrument Digital Interface (MIDI). MIDI data was analyzed to determine density of syncopation, note count, velocity, and asynchrony during baseline and treatment IAMT intervention. Results from visual analyses and Pearson correlations indicated partial evidence for the ability of individuals with PD to acquire different rhythmic complexity levels through IAMT. Partial evidence was also found to support the overall effectiveness of IAMT sessions in increasing participant’s mean gait velocity and stride length, and reducing step time and stride length variability. The findings of the current study indicate that IAMT sessions could be an effective strategy to increase physical mobility among individuals with PD. Using MIDI in the IAMT approach can yield data to evaluate treatment effectiveness and assess patient progress, providing daily measures and analysis of data using statistical analyses alongside visual analysis. This method has the potential to lead to new evidence-based interventions modeled in music therapy.

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