Passive, in-home gait measurement using an inexpensive depth camera: Initial results

In-home gait measurement results from the apartments of seven older adults obtained using an environmentally mounted depth camera, the Microsoft Kinect, are presented. Previous work evaluating the use of the Kinect for in-home gait assessment in a lab setting has shown the potential of this approach. In this work, a single Kinect sensor and computer have been deployed in five apartments, two of which contain multiple residents, in an independent living facility for older adults. Data collected in the five apartments, along with techniques for generating automated gait measurements from the data, are presented.

[1]  B. E. Maki,et al.  Gait Changes in Older Adults: Predictors of Falls or Indicators of Fear? , 1997, Journal of the American Geriatrics Society.

[2]  J. Kaye,et al.  Motor slowing precedes cognitive impairment in the oldest old , 1998, Neurology.

[3]  Jeffrey M. Hausdorff,et al.  Gait variability and fall risk in community-living older adults: a 1-year prospective study. , 2001, Archives of physical medicine and rehabilitation.

[4]  M. Skubic,et al.  Older adults' attitudes towards and perceptions of ‘smart home’ technologies: a pilot study , 2004, Medical informatics and the Internet in medicine.

[5]  M. Montero‐Odasso,et al.  Gait velocity as a single predictor of adverse events in healthy seniors aged 75 years and older. , 2005, The journals of gerontology. Series A, Biological sciences and medical sciences.

[6]  K. Holt,et al.  Gait Characteristics of Elderly People With a History of Falls: A Dynamic Approach , 2006, Physical Therapy.

[7]  M. Runge,et al.  Determinants of musculoskeletal frailty and the risk of falls in old age. , 2006, Journal of musculoskeletal & neuronal interactions.

[8]  Diana Hodgins.  The importance of measuring human gait. , 2008, Medical device technology.

[9]  Marjorie Skubic,et al.  Older adults' privacy considerations for vision based recognition methods of eldercare applications. , 2009, Technology and health care : official journal of the European Society for Engineering and Medicine.

[10]  James M. Keller,et al.  Extracting footfalls from voxel data , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[11]  Misha Pavel,et al.  Unobtrusive and Ubiquitous In-Home Monitoring: A Methodology for Continuous Assessment of Gait Velocity in Elders , 2010, IEEE Transactions on Biomedical Engineering.

[12]  Barry R. Greene,et al.  Quantitative Falls Risk Assessment Using the Timed Up and Go Test , 2010, IEEE Transactions on Biomedical Engineering.

[13]  Marjorie Skubic,et al.  Evaluation of an inexpensive depth camera for in-home gait assessment , 2011, J. Ambient Intell. Smart Environ..

[14]  T. Hayes,et al.  One walk a year to 1000 within a year: continuous in-home unobtrusive gait assessment of older adults. , 2012, Gait & posture.