Optimizing Gait Outcomes in Parkinson\u27s Disease with Auditory Cues: The Effects of Synchronization, Groove, and Beat Perception Ability

This dissertation explores a common, rehabilitative strategy for mitigating gait impairments in Parkinson’s disease (PD) called Rhythmic Auditory Stimulation (RAS). The effects of this intervention on gait in PD are well documented but highly variable, which poses difficulty for appropriate therapeutic application. Part of this variability may be related to individual musical abilities, such as beat perception accuracy, as most RAS interventions involve synchronizing with a beat. However, music is complex and variable. Therefore, factors inherent in the music itself may play a role in these differences, such as how much the music makes you want to move (groove), or how familiar it is. The studies in this thesis address these questions by examining the effects of different musical features (e.g., groove, familiarity) in auditory stimuli on the gait of different populations (younger adults, older adults, people with PD). The immediate effects of instructions to synchronize or to walk freely to the auditory stimuli on spatiotemporal gait parameters were compared between those with good beat perception and with poor beat perception in each of the populations. This research supports overall that high groove music and metronome cues have markedly different effects on spatiotemporal gait parameters than low groove cues, and that low groove cues have the potential to hinder spatial and temporal gait parameters. This indicates that music in RAS should be carefully assessed before use. This thesis also supports that synchronizing to RAS may be helpful to maximize the effects of cueing on temporal gait parameters across healthy adults and the PD group. However, these studies also highlight the various ways in which synchronizing can potentially compromise gait (e.g., shortening strides, increasing variability) and that this is not necessarily dependent on how well one can find a musical beat. Further research is required to understand what additional factors can be manipulated to best individualize music-based RAS for optimal gait management in clinical populations