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Actively Recruiting

Phase Not Applicable
Age: 65Years +
All Genders
ID06649500

Comparing Sensorized Treadmill Therapy and Conventional Group Therapy for Balance Disorders in Adults 65 and Older Using Artificial Intelligence to Identify Fall Risk and Predictive Indicators

Led by Fondazione Policlinico Universitario Campus Bio-Medico · Updated on 2025-03-19

108

Participants Needed

1

Research Sites

4 weeks

Total Duration

AI-Summary

What this Trial Is About

Falls are a major cause of disability and hospitalization in people over 60, significantly affecting quality of life and healthcare costs. This research aims to compare the effectiveness of rehabilitation using a sensorized treadmill called Walker View with conventional group therapy to reduce fall risk and improve daily activities in people with balance disorders. The study also explores using Artificial Intelligence to identify early signs that predict and help prevent falls in the elderly. Participants will be randomly assigned to one of three groups one group will use the Walker View treadmill, which provides 3D visual feedback to help improve balance through 18 sessions of 30 minutes each another group will receive conventional group therapy for balance rehabilitation with the same number of sessions the third group will have clinical monitoring and educational support without active treatment. Treatments focus on enhancing coordination and balance. During the study, participants will be evaluated at baseline, 6 weeks, and 10 weeks for changes in walking step length, balance, mobility, fall risk, daily living activities, muscle strength, quality of life, and stability. These assessments will include gait analysis and various physical and patient-reported measures. The study uses double-blind methods and will monitor progress to identify the best rehabilitation approach.

CONDITIONS

Brief Title

Identify the Most Effective Rehabilitation Method Between a Treatment with a Sensorized Treadmill (Walker View) and a Treatment with Conventional Group Therapy in Balance Disorders and the Use of Artificial Intelligence to Identify Predictive Indices to Prevent Falls and Diagnose Promptly the Risk

Research Team

F

Federica Bressi, MD

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