Testing treadmill training for walking difficulties

Parkinson's disease (PD) affects over 10 million worldwide, causing unstable gait and falls in 70% of patients despite medication. This leads to confidence loss, isolation, fractures, and hospitalizations. Treadmill training, augmented by mechanical/virtual-reality triggers, has proven effective in enhancing gait and reducing falls. However, underlying treadmill training mechanisms are unclear. To personalize training, we'll explore how PD patients benefit and transfer effects to daily life. This trial is part of three parallel randomized controlled trials within the Steps Against the Burden of Parkinson's Disease (CT-IDs: 6ef2e427b002, 6ef2e427b003, 6ef2e427b004) project, which will perform a pooled analysis across all sites in addition to individual RCT analyses. Each trial adheres to a shared core protocol while allowing for adaptations in the perturbation protocol, ensuring that data can be combined. Importantly, mechanistic findings and outcomes from this specific RCT will be reported independently, but also as part of a pooled analysis. In this trials, PD patients will undergo treadmill training with and without adaptaions (perturbations). 12 sessions of treadmill training will be provided, with pre/post assessments and a follow-up with pre/post assessments and a follow-up at 8 to 12 weeks after the post assessment. For post treadmill training a phone app will be offered as a home-based speed dependent walk training intervention. This intervention is an App based training for gait adaptability and allows users to set their own training time and pace. It delivers a rhythmic metronomic beat for three different walking speeds, designed to trigger movement and encourage better walking patterns.. Gait improvements are expected, driven by sensorimotor integration improving balance control. Biomechanical data analysis will reveal enhanced foot placement control. Neurophysiological changes will be studied through EEG and EMG, aiming to find improved gait stability with reduced EEG beta power and increased EEG-EMG coherence. Gait improvement in the lab might not correlate with daily-life results. Gait self-efficacy could influence transfer, prompting investigation into mechanistic associations with mobility outcomes. Remote digital tools will assess week-long mobility outcomes, employing machine learning to comprehend why some improve both in lab and life, while others don't. This will uncover mechanisms translating treatment effects into real-world outcomes, aiding personalized intervention development.

i. Rationale The rationale of this trial is that speed dependent treadmill training (SDTT) improves gait through improved sensorimotor integration, with changes in cortical activity as neural correlates. Additional benefits of treadmill training can be seen if perturbation or adaptations are added. This is based on the idea, that in addition to the sensorimotor integration the reactive balance in trained as well18. Furthermore, it hypothesizes that treadmill training and its effects on gait quality will improve gait self-efficacy, which mediates and/or modifies transfer of training effects to improved daily-life gait. ii. Objectives Thus, the objectives of our StepuP project are: 1. To understand the kinematic and neural mechanisms that underlie improvements in gait due to treadmill training with and without mechanically and VR-triggered gait adaptations in people with PD; 2. To assess to what extent improvements in gait due to treadmill training, as measured in the lab, transfer to improvements in daily life mobility; 3. To understand the mechanisms that underpin transfer from improvements in gait to improvements of mobility in daily life in people with PD; 4. To understand for whom treadmill training improves lab-based gait characteristics and for whom it does not, and understand for whom treadmill training improves mobility in daily life and for whom it does not. Attaining these objectives will provide a better understanding of the successes and failures of treadmill training to improve gait stability and prevent falls in people with PD at an individual level, which in the medium term will allow targeted delivery of such interventions and in the long term will allow personalization of such interventions to improve outcomes for all. iii. Endpoints Concerning the endpoints, this trial examines the effect of treadmill training with and without perturbations on gait performance, and neural correlates in people with PD. The primary endpoint is (change in) gait speed, secondary endpoints are divided into three groups (clinical, kinematic and neurophysiological). Clinical measures are used to assess the effect of training on disease symptoms. Kinematic measures are changes from baseline to follow-up, all under controlled conditions (treadmill), and provide insight into gait performance and quality. Neurophysiological measures aim to understand the neural control mechanisms underlying the training effects. On an exploratory level, the study aims to assess the training effects on daily-life gait by using wearable devices and assess gait self-efficacy using previously validated questionnaires.