Diego Tosatto

I have been working as a physical therapist since 2010, when I got my Bachelor’s degree at the University of Milan – Bicocca with a project on “Assessing lumbar and hip movements in subjects with lumbar pain by means of 3D Motion Capture System”.
This interest led me to first pursue a Master of Science, completed in 2020. My project, “Spin of information and inconsistency between abstract and full text in RCTs investigating upper limb rehabilitation after stroke: An overview study” allowed me to combine my passions by exploring the literature on stroke rehabilitation and critically assessing the methodological quality of the papers reviewed. My first attempt to actively conducting research informed me of the concepts in motor control, and their potential to improve my work as a clinician.
In hopes of gaining a better understanding of how motor control could influence the rehabilitation of neurological patients, I applied for a PhD in Neuroscience in 2022. My PhD studies focus on assessing muscle activity during gait (single and dual task) in patients with Parkinson’s Disease (PD), with the aim to identify variables related to falling.

PhD research project

Muscle functions during gait as potential predictors of fall risk in people with Parkinson’s disease

Background: Gait disorders are frequently reported in individuals with Parkinson’s disease (PD). Despite extensive research, the specific gait features affected by PD are still not clearly defined.

Aim: To investigate muscle activation patterns during single and dual task gait in individuals with PD that prospectively report at least one fall in a 12 months follow-up period.

Materials and methods: Participants with idiopathic PD will be analyzed in two conditions: simple and dual task walking. Subjects will be instructed to walk along a 10m straight path at comfortable speed, with the addition of a cognitive task (counting backwards) during the dual task condition. Data will be collected by means of 3D Motion capture and surface electromyography to record muscle activity of both lower limbs of gluteus maximus, biceps femoris, rectus femoris, vastus medialis, gastrocnemius medialis, soleus and tibialis anterior. Patients will be contacted telephonically on a monthly basis and asked to report any falls in the previous month. Each patient will be followed for 12 months and then included into the faller or non-faller group. Muscles activations will be compared between groups taking into consideration the contraction of couples of agonist/antagonist at each joint, by computing the Co-Activation Index (CI). Qualisys Track Manager (QTM), Visual3D and Matlab, will be used to analyze data. Comparisons will be performed to study the effect of task (simple vs dual) and the effect of group (PD faller vs PD non faller). After normalization of the EMG signals and the gait cycle, Statistical Parametric Mapping (SPM) will be used to perform statistical analysis.

Expected Results: We hypothesize a higher Co-Activation Index (Cl) between lower limb agonist/antagonist muscles among PD fallers compared to PD non-fallers. Worse scores as assessed by the clinical outcome measures are expected to occur in PD fallers compared to PD non-fallers.