Daniele Bonacina

I am physical therapists and a PhD student in Clinical Neuroscience at the University of Milano Bicocca.

I graduated in Physical Therapy at the University of Milano-Bicocca (Italy) in 2015 discussing a thesis on “Continuing the treatment: the therapeutic value of the sitting posture – Assessment of positioning throughout proprioceptive and neuromuscular facilitations”. Since 2016, I have been working with subacute stroke patients and people with movement disorders – in particular, Parkinson’s disease (PD) – in a Rehabilitation Hospital in Milano area (GDS – Istituti Clinici Zucchi Hospital, Carate Brianza).

This clinical work pushed me to gain a better understanding of the fundamental mechanisms behind neurological diseases. Therefore, I pursued a MSc in Rehabilitation Sciences at the University of Genoa (Italy) diving deeper into scientific literature and research methodology. Now I am a PhD student in Clinical Neuroscience at the University of Milano Bicocca, which will last until 2025.

My PhD project aims to investigate kinetic and kinematic variables that could be reliable predictors of fall risk in individuals with Parkinson’s disease. Using 3D motion capture and force plates, I will collect data on single and dual-task walking that will be compared with that of healthy subjects. My goal is to evaluate all the data to better understand which variables could affect parkinsonian gait and implement this knowledge into daily clinical practice.

PhD research project

Gait parameters (kinetic and kinematic) as potential predictor of fall risk in patients with Parkinson’s disease

BACKGROUND: Parkinson’s disease (PD) is a progressive neurodegenerative disease that includes several motor symptoms. Rigidity, tremor, bradykinesia, and postural instability are the most common, and abnormal walking patterns were frequently observed in people suffering from PD. Gait in PD is no longer automatic and these dysfunctions lead to an increased risk of falling. The occurrence of falls is directly related to decreased quality of life and also to increased health costs and the possibility of death (9). Given the complexity of the problem, identifying measurements to predict fall risk is necessary, even before the first fall occurs

AIM: This research aim to examine the three-dimensional gait characteristics of PD patients who prospectively report at least one fall over a twelve month period, with the intent of identifying kinematic and kinematic variables that might characterize fallers and be a target for modification through tailored interventions.

METHODS: Inclusion criteria: 30-75 years old, ability to walk with no aids, absence of other pathologies or post-surgical condition that could affect walking, and no cognitive impairment (Mini-Mental State Examination – MMSE <24) Only idiopathic PD will be enrolled. A 3D Motion Capture system with ten cameras (47 retroreflective markers and 5 clusters) and 2 force plates recorded kinetic and kinematic data. Subjects will be instructed to walk on a 10-meter linear path at a comfortable speed under two conditions: spontaneous walking (single task – 1) and counting backward (dual task – 2) randomly.

EXPECTED RESULTS: We hypothesize that in fallers the pathological rigidity produces an higher reduction in ROM (especially in the knee) and a variation of muscle torque through all joints. In particular, during the heel contact phase of gait cycle, a diminished knee extension combined with insufficient ankle dorsiflexion could be a discriminating factor between fallers and non fallers.