Abstract
BackgroundWalking patterns can provide important indications of a person’s health status and be beneficial in the early diagnosis of individuals with a potential walking disorder. For appropriate gait analysis, it is critical that natural functional walking characteristics are captured, rather than those experienced in artificial or observed settings. To better understand the extent to which setting influences gait patterns, and particularly whether observation plays a varying role on subjects of different ages, the current study investigates to what extent people walk differently in lab versus real-world environments and whether age dependencies exist.MethodsThe walking patterns of 20 young and 20 elderly healthy subjects were recorded with five wearable inertial measurement units (ZurichMOVE sensors) attached to both ankles, both wrists and the chest. An automated detection process based on dynamic time warping was developed to efficiently identify the relevant sequences. From the ZurichMOVE recordings, 15 spatio-temporal gait parameters were extracted, analyzed and compared between motion patterns captured in a controlled lab environment (10 m walking test) and the non-controlled ecologically valid real-world environment (72 h recording) in both groups.ResultsSeveral parameters (Cluster A) showed significant differences between the two environments for both groups, including an increased outward foot rotation, step width, number of steps per 180° turn, stance to swing ratio, and cycle time deviation in the real-world. A number of parameters (Cluster B) showed only significant differences between the two environments for elderly subjects, including a decreased gait velocity (p = 0.0072), decreased cadence (p = 0.0051) and increased cycle time (p = 0.0051) in real-world settings. Importantly, the real-world environment increased the differences in several parameters between the young and elderly groups.ConclusionElderly test subjects walked differently in controlled lab settings compared to their real-world environments, which indicates the need to better understand natural walking patterns under ecologically valid conditions before clinically relevant conclusions can be drawn on a subject’s functional status. Moreover, the greater inter-group differences in real-world environments seem promising regarding the sensitive identification of subjects with indications of a walking disorder.
Highlights
Important indications of a person’s health status can be obtained through analysis of walking patterns (König et al, 2014; Ravi et al, 2019)
normal pressure hydrocephalus (NPH) exhibits specific gait characteristics such as increased foot outward rotation, increased number of steps needed for a 180◦ turnaround, increased cycle time deviation, and impaired arm swing compared to asymptomatic controls (Stolze et al, 2000, 2001; Relkin et al, 2005; Gallia et al, 2006; Shrinivasan et al, 2011)
For NPH patients, the following observations have been previously reported: increased foot outward rotation, increased number of steps needed for a 180◦ turnaround, increased cycle time deviation, and impaired arm swing compared to asymptomatic controls (Stolze et al, 2000, 2001; Relkin et al, 2005; Gallia et al, 2006; Shrinivasan et al, 2011)
Summary
Important indications of a person’s health status can be obtained through analysis of walking patterns (König et al, 2014; Ravi et al, 2019). A variety of neurological disorders show specific gait impairments such as dementia (Allan et al, 2005; McArdle et al, 2019), normal pressure hydrocephalus (NPH) (Stolze et al, 2000, 2001) or Parkinson’s disease (Stolze et al, 2001; Del Din et al, 2016) The diagnosis of these diseases is difficult, and misinterpretation is possible, especially in NPH. Indications suggest that subtle characteristics contained within a subject’s gait patterns are sufficient to differentiate neurological pathologies at an early time point, and could form a fundamental basis for aiding clinical decision making (König et al, 2016a,b) With sufficient objectivity, such information could support the clinical diagnosis of e.g., NPH, where it is estimated that only one in ten cases is correctly diagnosed and correctly treated (Jaraj et al, 2014). To better understand the extent to which setting influences gait patterns, and whether observation plays a varying role on subjects of different ages, the current study investigates to what extent people walk differently in lab versus real-world environments and whether age dependencies exist
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