Dynamic Postural Stability Assessment in Neurorehabilitation

Postural and balance disorders are common in neurological disorders. They are often associated with reduced mobility and fear of falling, which strongly limit independent activities of daily living (ADL), compromise the quality of life and reduce social participation. Here the investigators apply an existing software solution to: 1) obtain biomarkers of gait deficits in 5 neurological conditions, 2) develop an automatic procedure supporting clinicians in the early identification of patients at high risk of falling as to tailor rehabilitation treatment; 3) longitudinally assess these patients to test the efficacy of rehabilitation. High-density electroencephalography (EEG), and inertial sensors located at lower limbs and at upper body levels will be used to extract the most appropriate indexes during motor tasks. The ultimate goal is to develop cost-effective treatment procedures to prevent recurrent falls and fall-related injuries and favour the reintegration of the patient into everyday activities. The first hypothesis of this study is that clinical professionals (e.g., medical doctors and rehabilitative staff) would strongly benefit from the possibility to rely on quantitative, reliable and reproducible information about patients motor deficits. This piece of information can be nowadays readily available through miniaturized wearable technology and its information content can be effectively conveyed thanks to ad hoc software solution, like the A.r.i.s.e. software. The second hypothesis of the present study is that early identification of patients at high risk of dependence and the subsequent application of personalized treatment would allow for cost-effective treatment procedures to favor the autonomy into everyday activities. The results of this project could represent a valuable support in the clinical reasoning and decision-making process.