Clinical trial NCT06649500: 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
Official title: Comparison Between Treatment with Sensorized Treadmill and Conventional Therapy in Balance Disorders and Use of Artificial Intelligence in Identifying Predictive and Prognostic Indices of the Risk of Falling in Balance Disorders in Adult-elderly Subjects
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Balance Disorders
Rehabilitation
Falls
Falls Prevention
Artificial Intelligence (AI)
Elderly (people Aged 65 or More)
Lead sponsor: Fondazione Policlinico Universitario Campus Bio-Medico
Sponsor class: OTHER
First posted: 2024-10-18
Enrollment: 108
Sex: ALL
Minimum age (years): 65
Standard ages: OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: TREATMENT

Brief summary: 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 criteria: Inclusion Criteria:

* Age ≥ 65 years
* Consent to participate in the study
* Positive history of balance disorders
* Absence of cognitive deficits (MMSE ≥ 24)
* Tinetti \&lt; 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.

Primary outcomes:
measure: Change in Step Length of Gait Analysis
timeFrame: Baseline, 6 weeks, 10 weeks
Secondary outcomes:
measure: Balance
timeFrame: Baseline, 6 weeks, 10 weeks
measure: Mobility
timeFrame: Baseline, 6 weeks, 10 weeks
measure: Risk of falling
timeFrame: Baseline, 6 weeks, 10 weeks
measure: Daily Living
timeFrame: Baseline, 6 weeks, 10 weeks
measure: Instrumental Activites of Daily Living
timeFrame: Baseline, 6 weeks, 10 weeks
measure: Muscle strength
timeFrame: Baseline, 6 weeks, 10 weeks
measure: Patient reported Quality of Life
timeFrame: Baseline, 6 weeks, 10 weeks
measure: Stability
timeFrame: Baseline, 6 weeks, 10 weeks
Other outcomes:
Locations:
city: Rome
country: Italy
facility: Policlinico Universitario Campus Bio Medico di Roma
Study officials:
References: