Novel methods for fall prediction in older people
Technological advances have enabled less expensive ways to quantify physical fall risk in the homes of older people.
We are exploring whether unobtrusive monitoring of activities of daily living or regular unsupervised directed routine assessments using new sensor-based technologies can predict falls in older adults more accurately.
We are developing and validating a range of mobile apps to assess fall risk factors in research settings and clinical practice; i.e. questionnaires (fear of falling, physical activity, etc), sensorimotor assessments (balance, vision, etc) and cognitive assessments (executive functioning, processing speed, etc.).
We are also working on Smart home IT support for frail elderly people who live alone.