Falls are the most common cause of injury and hospitalization and one of the principal causes of death and disability in older adults worldwide. It is estimated that 30% of elderly adults over 65 years of age fall each year. In the community, the proportion of people who sustain at least one fall over a 1-year period varies from 28 to 35% in the 1 65-year age group to 32–42% in the 75+ age group, with 15% of older people falling at least twice each year . Incidence rates in hospitals are higher, and in long-term care settings approximately 30–50% of people fall each year, with 40% falling recurrently. The direct and indirect societal costs of falls are enormous; among older people in the USA alone, the cost of falls has been estimated to be in the region of US $20Bn per year.
The combination of high frequency and high risk to injury in older people make falls one of the major geriatric issues. Falls are strongly associated with impairments in gait and balance; furthermore, gait and balance are considered to be easily modifiable falls risk factors. Falls risk is generally assessed in clinical environment physiotherapists, geriatricians, clinical nurse specialists or occupational therapists using a variety of clinical scales such as the Berg balance scale (BBS) or Performance Orientated Mobility Assessment (POMA). Such scales can be subjection and variable in administration. Multifactorial intervention, based on modifiable risk factors has been shown to be effective in reducing the incidence of falls in community-dwelling older adults although, despite detailed targeted multifactorial interventions, the best reported reduction in the incidence of falls is in the region of 30%. Accurate identification of those participants at high risk of falls would facilitate appropriate and timely intervention, and could lead to improved quality of care and reduced associated hospital costs due to reduced admissions and reduced severity of falls.
The TRIL centre aims to develop novel, objective technologies for assessment of gait, mobility and balance in order to provide intelligent indicators for falls risk and facilitate timely intervention.
Current research is investigating the application of inertial and pressure sensor technologies, combined with advanced algorithms to aid in falls prevention, falls and frailty risk assessment as well as clinical gait, mobility and balance analysis and assessment of cognitive decline.