Step to the music: an App to Improve Gait In Parkinson’s Disease.

Parkinson’s disease (PD) is a neurodegenerative condition marked by motor symptoms such as bradykinesia, tremor, and debilitating gait disturbances like shuffling, reduced stride length, and impaired rhythmicity. These gait deficits are tied to dysfunction in the basal ganglia and impaired auditory-motor coupling. Rhythmic Auditory Stimulation (RAS), has shown promise by exploiting the brain’s ability to synchronize movement to external rhythmic cues. However, traditional RAS tools—like metronomes or fixed-tempo tracks—often lack adaptability and user engagement. This thesis presents a mobile-based approach for delivering personalized rhythmic stimulation through a custom Android app that integrates rhythmic cues with music. The project aimed to: (1) design a robust music-cue synchronization algorithm, (2) develop a patient- and clinician-friendly app for rhythmic feedback, and (3) test the usability and cadence-matching capacity in individuals with PD. Developed in Android Studio, the app enables users to choose music and rhythmic sounds, while clinicians can define target cadence values. Rhythmic cues are delivered in stereo, alternating between channels to potentially stimulate lateralized entrainment. Cadence is adjusted based on prior walking tests or clinician input. Preliminary tests were conducted at the Institute of Neurological Sciences (Bologna) with supervised single-session trials. Though the sample size was small, early results demonstrated ease of use, and positive user feedback. Participants reported greater rhythmic awareness and preferred the music-integrated cues over isolated tones. Overall, this system demonstrates the feasibility of mobile RAS tools as low-cost, accessible solutions for gait rehabilitation in PD. Future development could explore adaptive cueing, integration with wearable sensors, and phased training protocols to better accommodate the dynamic needs of users.