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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

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

Recruiting
65 years and older
All
Phase N/A

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Overview

Falls in the elderly are one of the main sources of disability and hospitalization, with a significant impact on quality of life and social and healthcare costs. Falls represent a significant health concern for people over 60 years old. Numerous studies have shown that falls cause serious health consequences. Around 30% of people over the age of 60 experience a fall during the year.

According to the impact falls have, the investigators decided to analyze the effectiveness of training on a Walker View sensorized treadmill, with the possibility of exercises for coordination and balance, compared to training with a conventional group therapy, in order to understand the best training to reduce the risk of falling and observe the possible improvements in daily life activities.

So the study aims to identify the most effective rehabilitation method between a treatment with a sensorized treadmill (Walker View) and a conventional group therapy in balance disorders.

The study also aims to identify predictive indices, with the use of Artificial Intelligence, that can contribute to the prevention and diagnosis of balance disorders in a short time and prevent falls in the elderly.

Eligibility

Inclusion Criteria:

  • Age ≥ 65 years
  • Consent to participate in the study
  • Positive history of balance disorders
  • Absence of cognitive deficits (MMSE ≥ 24)
  • Tinetti < 25

Exclusion Criteria:

  • Clinical pictures associated with musculoskeletal, cardiovascular, cerebrovascular, neuro-psychic problems and post-surgical outcomes that make the planned evaluation tests unfeasible.
  • Inability to carry out a walking test.
  • History of more than one fall in the last six months.
  • Subjects who have not expressed informed consent to participate in the study.

Study details
    Balance Disorders
    Rehabilitation
    Falls
    Falls Prevention
    Artificial Intelligence (AI)
    Elderly (people Aged 65 or More)

NCT06649500

Fondazione Policlinico Universitario Campus Bio-Medico

15 October 2025

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