Paper Info
Title
Passive In-Home Measurement Of Stride-To-Stride Gait Variability Comparing Vision And Kinect Sensing
Abstract
We present an analysis of measuring stride-to-stride gait variability passively, in a home setting using two vision based monitoring techniques: anonymized video data from a system of two web-cameras, and depth imagery from a single Microsoft Kinect. Millions of older adults fall every year. The ability to assess the fall risk of elderly individuals is essential to allowing them to continue living safely in independent settings as they age. Studies have shown that measures of stride-to-stride gait variability are predictive of falls in older adults. For this analysis, a set of participants were asked to perform a number of short walks while being monitored by the two vision based systems, along with a marker based Vicon motion capture system for ground truth. Measures of stride-to-stride gait variability were computed using each of the systems and compared against those obtained from the Vicon.
Year
DOI
Venue
2011
10.1109/IEMBS.2011.6091602
2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Keywords
Field
DocType
length measurement,independent set,geriatrics,accuracy,three dimensional,ground truth,gait analysis,patient monitoring,motion capture
Computer vision,Motion capture,Activities of daily living,Gait,STRIDE,Remote patient monitoring,Computer science,Gait analysis,Ground truth,Artificial intelligence,Falls in older adults
Conference
Volume
ISSN
Citations 
2011
1557-170X
49
PageRank 
References 
Authors
3.33
3
2
Name
Order
Citations
PageRank
Erik E. Stone138131.42
M. Skubic222718.61