U.S., July 11 -- ClinicalTrials.gov registry received information related to the study (NCT07058714) titled 'Multimodal Artificial Intelligence Based Fall Risk Prediction in Parkinson's Disease' on July 01.
Brief Summary: Parkinson's disease (PD) is characterized by motor symptoms such as bradykinesia, tremor, rigidity, and postural instability, often leading to gait disturbances and a high risk of falls. Dual-task walking assessments-requiring simultaneous motor and cognitive engagement-have gained importance in evaluating real-life mobility impairments in PD, as they more accurately reflect challenges faced during daily activities. While clinical tools such as the Timed Up and Go (TUG), Four Square Step Test (FSST), and Mini-BESTest are ...