Aging is a condition characterized by a general decline in physical and cognitive performance, however its effects on various functions are still controversial. These changes lead to an increased risk of injuries, particularly due to falls. According to the World Health Organization (WHO) report, 28-35% of individuals aged over 65 experience a fall each year, and this percentage increases with age. For this reason, preventing falls among the elderly is undeniably one of the most critical public health issues in today's aging society. Nowadays, it is widely demonstrated that the loss of muscle strength and mass, along with decreased balance, significantly increases the risk of falls. However, with aging, numerous other changes occur that contribute to an increased risk of falls, such as a decline in cognitive function, including attention, reaction capabilities and memory, as well as other factors that worsen the quality of life, such as insufficient sleep or nutrition. According to WHO estimates, by 2030, the number of injuries due to falls will double. Therefore, it is of great importance to understand and analyze the factors contributing to falls among older adults in everyday life. For this reason, the principal aim of this study was to evaluate the correlation between the fall index and the Visual Attention, Reaction Time and visual field using the technologies of Virtual Reality (VR). Since aging brigs changes in different aspect, the secondary objectives aim to study the correlation also with i) sleep quantity and quality parameters, ii) risk of malnutrition, and iii) physical condition, muscle conditions and strength in order to have a comprehensive understanding of the factors that most contribute to the risk of falls. In addition to these objectives, the correlation between acute sleep deprivation and the risk of falls will also be analyzed, in order to understand how inadequate sleep quantity can impact injuries in the elderly.
Male or female, of any ethnicity;
Age ≥ 60 years;
Cognitively intact;
Autonomous ambulation;
Body Mass Index > 40.0;
History of epileptic episodes;
Bone fractures in the last 6 months;
Previous surgical treatments for orthopedic conditions performed in the six months prior to study inclusion;
A minimum of 100 subjects aged 60 years or older will be recruited, but recruitment will continue until enough subjects are identified to reach the predetermined number for the second study. The subjects are chosen on the basis of the following inclusion and exclusion criteria
Other
Cross-sectional
Not listed
30 - second chair stand test
to assess the leg strength and endurance in older adults. Being in a specific sitting position on a chair, the test consists of getting up and sitting down as many times as possible in 30 seconds
Virtual reality (VR-Brain Tracker)
Evaluation to assess visual attention through the Multiple Object Tracking paradigm.
Strength asessment
Handgrip Test (Kg) Flexors and Extensors of thigh muscles (Kg)
Balance test
balance assessment is conducted using Baiobit equipment from BTS Bioengineering. The maximal balance time in monopodalic will be considered (s)
Sleep assessment
Objective assessment of sleep quantity and quality using the MotionWatch 8® (CamTec, USA), and sleep diary.
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