title: Kinect-Based Five-Times-Sit-to-Stand Test for Clinical and In-Home Assessment of Fall Risk in Older People.
abstract: BACKGROUND
  Accidental falls remain an important problem in older people. The five-times-sit-to-stand (5STS) test is commonly used as a functional test to assess fall risk. Recent advances in sensor technologies hold great promise for more objective and accurate assessments.
  
  
  OBJECTIVE
  The aims of this study were: (1) to examine the feasibility of a low-cost and portable Kinect-based 5STS test to discriminate between fallers and nonfallers and (2) to investigate whether this test can be used for supervised clinical, supervised and unsupervised in-home fall risk assessments.
  
  
  METHODS
  A total of 94 community-dwelling older adults were assessed by the Kinect-based 5STS test in the laboratory and 20 participants were tested in their own homes. An algorithm was developed to automatically calculate timing- and speed-related measurements from the Kinect-based sensor data to discriminate between fallers and nonfallers. The associations of these measurements with standard clinical fall risk tests and the results of supervised and unsupervised in-home assessments were examined.
  
  
  RESULTS
  Fallers were significantly slower than nonfallers on Kinect-based measures. The mean velocity of the sit-to-stand transitions discriminated well between the fallers and nonfallers based on 12-month retrospective fall data. The Kinect-based measures collected in the laboratory correlated strongly with those collected in the supervised (r = 0.704-0.832) and unsupervised (r = 0.775-0.931) in-home assessments.
  
  
  CONCLUSIONS
  In summary, we found that the Kinect-based 5STS test discriminated well between the fallers and nonfallers and was feasible to administer in clinical and supervised in-home settings. This test may be useful in clinical settings for identifying high-risk fallers for further intervention or for regular in-home assessments in the future.
authors.affiliation: Austrian Institute of Technology, Assistive Healthcare Information Technology Group, Vienna, Austria.
authors.forename: Andreas
authors.initials: A
authors.lastname: Ejupi
authors.forename: Matthew
authors.initials: M
authors.lastname: Brodie
authors.forename: Yves J
authors.initials: YJ
authors.lastname: Gschwind
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Lord
authors.forename: Wolfgang L
authors.initials: WL
authors.lastname: Zagler
authors.forename: Kim
authors.initials: K
authors.lastname: Delbaere
mesh_terms: D000058:Accidental Falls; D000368:Aged; D000369:Aged, 80 and over; D001696:Biomechanical Phenomena; D005260:Female; D006801:Humans; D057187:Independent Living; D008297:Male; D004856:Postural Balance; D011187:Posture; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods*