Assessment of a New System to Detect, Quantify and Treat Near Falls in Older Adults

Assessment of a New System to Detect, Quantify and Treat Near Falls in Older Adults

The study is aimed to assess a new system for the automatic detection, quantification and treatment of Near Fall (NF) episodes in healthy older adults with a history of falls. The system is comprized of a treadmill and a virtual reality simulation which provides a motor-cognitive challenge to provoke NF. The challenges provided by the system are individualized and using machine learning algorithms will enable the identification and detection of NF under different conditions and allow for the most suitable treatment.

Inclusion Criteria:

1. Healthy older adults with a history of falls or complaints of gait instability
2. Able to walk independently for at least 10 minutes

Exclusion Criteria:

1. Systemic chronic or acute pathologies:

   1. Ischemic heart disease
   2. Orthopedic or Rheumatic diseases
   3. Severe vision problems
   4. Neurological disease: PD, AD, CVA

2. Patients who underwent brain surgery in the last 6 months prior to the study