title: Single-Camera-Based Method for Step Length Symmetry Measurement in Unconstrained Elderly Home Monitoring.
abstract: single-camera-based gait monitoring is unobtrusive, inexpensive, and easy-to-use to monitor daily gait of seniors in their homes. However, most studies require subjects to walk perpendicularly to camera's optical axis or along some specified routes, which limits its application in elderly home monitoring. To build unconstrained monitoring environments, we propose a method to measure step length symmetry ratio (a useful gait parameter representing gait symmetry without significant relationship with age) from unconstrained straight walking using a single camera, without strict restrictions on walking directions or routes.
  
  
  
  according to projective geometry theory, we first develop a calculation formula of step length ratio for the case of unconstrained straight-line walking. Then, to adapt to general cases, we propose to modify noncollinear footprints, and accordingly provide general procedure for step length ratio extraction from unconstrained straight walking.
  
  
  
  Our method achieves a mean absolute percentage error (MAPE) of 1.9547% for 15 subjects' normal and abnormal side-view gaits, and also obtains satisfactory MAPEs for non-side-view gaits (2.4026% for 45°-view gaits and 3.9721% for 30°-view gaits). The performance is much better than a well-established monocular gait measurement system suitable only for side-view gaits with a MAPE of 3.5538%.
  
  
  
  Independently of walking directions, our method can accurately estimate step length ratios from unconstrained straight walking.
  
  
  
  This demonstrates our method is applicable for elders' daily gait monitoring to provide valuable information for elderly health care, such as abnormal gait recognition, fall risk assessment, etc.
  
  
  
  single-camera-based gait monitoring is unobtrusive, inexpensive, and easy-to-use to monitor daily gait of seniors in their homes. However, most studies require subjects to walk perpendicularly to camera's optical axis or along some specified routes, which limits its application in elderly home monitoring. To build unconstrained monitoring environments, we propose a method to measure step length symmetry ratio (a useful gait parameter representing gait symmetry without significant relationship with age) from unconstrained straight walking using a single camera, without strict restrictions on walking directions or routes.
  
  
  
  according to projective geometry theory, we first develop a calculation formula of step length ratio for the case of unconstrained straight-line walking. Then, to adapt to general cases, we propose to modify noncollinear footprints, and accordingly provide general procedure for step length ratio extraction from unconstrained straight walking.
  
  
  
  Our method achieves a mean absolute percentage error (MAPE) of 1.9547% for 15 subjects' normal and abnormal side-view gaits, and also obtains satisfactory MAPEs for non-side-view gaits (2.4026% for 45°-view gaits and 3.9721% for 30°-view gaits). The performance is much better than a well-established monocular gait measurement system suitable only for side-view gaits with a MAPE of 3.5538%.
  
  
  
  Independently of walking directions, our method can accurately estimate step length ratios from unconstrained straight walking.
  
  
  
  This demonstrates our method is applicable for elders' daily gait monitoring to provide valuable information for elderly health care, such as abnormal gait recognition, fall risk assessment, etc.
authors.affiliation: College of Information Science and EngineeringNortheastern University.
authors.forename: Xi
authors.initials: X
authors.lastname: Cai
authors.affiliation: College of Information Science and Engineering, Northeastern University, Shenyang, China.
authors.forename: Guang
authors.initials: G
authors.lastname: Han
authors.affiliation: College of Information Science and EngineeringNortheastern University.
authors.forename: Xin
authors.initials: X
authors.lastname: Song
authors.affiliation: College of Information Science and EngineeringNortheastern University.
authors.forename: Jinkuan
authors.initials: J
authors.lastname: Wang
mesh_terms: D000328:Adult; D005260:Female; D005684:Gait / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D018670:Monitoring, Ambulatory / Q000379:methods*; D015203:Reproducibility of Results; D014741:Video Recording / Q000379:methods; D016138:Walking / Q000502:physiology*; D055815:Young Adult
keywords: Biomedical monitoring; Cameras; Legged locomotion; Length measurement; Monitoring; Senior citizens