Design and development of an automated fall risk assessment system for older adults

Ruopeng Sun, Vignesh R. Paramathayalan, Rama Ratnam, Sanjiv Jain, Daniel G. Morrow, Jacob J. Sosnoff

Research output: Chapter in Book/Report/Conference proceedingChapter


Falls are the leading cause of accidental injury and death in older adults and exceedingly common with one-third of adults over the age of 65 years experiencing a fall. Falls can be prevented with targeted interventions. However current fall risk screening is inadequate. This chapter outlines the need for technological advancements in fall risk screening. It also discusses the design and development of an automated fall risk screening system. The system consists of a Microsoft Kinect V2 camera, a PC-based computer, and a display screen. A Fall Risk Assessment Avatar leads users through a series of balance tasks while their movement is recorded and a cloud-based algorithm determines the individual’s fall risk. Preliminary data on its validity and usability reveal that the movement analysis is sensitive to balance impairment and that older adults find the system easy to use. Future design iterations and next steps are discussed to conclude this chapter.

Original languageEnglish (US)
Title of host publicationAging, Technology and Health
Number of pages12
ISBN (Electronic)9780128112724
ISBN (Print)9780128112731
StatePublished - Jan 1 2018


  • Falls
  • balance
  • clinical outcomes
  • human-computer interaction
  • imaging
  • mobility
  • motor control
  • postural control

ASJC Scopus subject areas

  • Psychology(all)


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