Abstract
Various factors, such as fear of falling, postural instability, and altered executive function, contribute to the high risk of falling in Parkinson's disease (PD). Dual-task training is an established method to reduce this risk. Motor-perceptual task combinations typically require a patient to walk while simultaneously engaging in a perceptual task. Motor-executive dual-tasking (DT) combines locomotion with executive function tasks. One augmented reality treadmill training (AR-TT) study revealed promising results of a perceptual dual-task training with a markedly reduced frequency of falls especially in patients with PD. We here propose to compare the effects of two types of concurrent tasks, perceptual and executive, on high-intensity TT). Patients will be trained with TT alone, in combination with an augmented reality perceptual DT (AR-TT) or with an executive DT (Random Number Generation; RNG-TT). The results are expected to inform research on therapeutic strategies for the training of balance in PD.
Highlights
Falls occur with a high prevalence of about 60% in patients with Parkinson’s disease (PD) with 40% having recurrent falls with an average of 20 falls per year [1]
In a randomized-controlled study with a parallel-group design, one of the three interventions will be applied over 3 weeks during regular neurorehabilitation with a follow-up of three months (AR-TT vs. random number generation (RNG)-TT vs. TT)
We hope that Sensor-based gait (SBG) analyses will reveal which intervention has more impact on improving gait stability, on freezing of gait (FoG), and on gait performance in daily life
Summary
Falls occur with a high prevalence of about 60% in patients with Parkinson’s disease (PD) with 40% having recurrent falls with an average of 20 falls per year [1]. Already in an early stage of PD, diminished gait speed, pain, history of falls or near falls, balance disturbances during dual-tasking (DT), retropulsion, freezing of gait (FoG), and the need for stabilization assistance are associated with falls [3]. When controlled for age and sex, only fear of falling, history of near falls, and retropulsion predict prospective falls [3]. The akinetic-rigid motor type, motor fluctuations (off-phases and dyskinesia), high L-dopa dosage, FoG, and anxiety predict falls [4, 5]. At these stages, falls are further predicted by impaired postural stability and by impaired cognitive function. Attention, executive function, and the capability of DT predict future falls [6, 7]
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