Phone Based Fall Risk Prediction


Falls in older people can represent serious individual and socioeconomic problems. With the increasing number of older people in the population, management of falls is becoming a challenge.

It is now recognized that several risk factors for falling can be identified, and specific interventions can be designed in order to reduce those risks. Several tools were then developed and are now available to screen for fall risk. However, these tools are applied with low frequency, usually requiring the use of expensive equipments that can only be manipulated by experts. This poses some constraints on the prevention of falls, since when these techniques are applied, it can be too late.

In order to improve the earlier detection of risks and the application of fall prevention strategies, new community based solutions must be developed. In this project, the mobile phone was purposed as a potential instrument to perform fall risk screening. Several strategies were then evaluated to be adapted to the phone for fall risk screening purposes.

Phone’s inertial sensors were used to extract some parameters of gait that were related with an increased risk of falling. Foot contacts, gait phases, step length, step duration, walking velocity and variability parameters could then be determined from sensors data. Acceptable measures of step length and walking velocity could be obtained. Additionally, other risk factors were selected to be assessed by self-report, using some clinical scales/questionnaires.

Results suggest that phone can be used as a major strategy to improve fall prevention, being a great value for older persons and society.


Author: Vânia Guimarães

Type: MSc thesis

Partner: Faculdade de Engenharia da Universidade do Porto

Year: 2011