Detection and localisation of hesitant steps in people with Alzheimer's disease navigating routes of varying complexity

Abstract

People with Alzheimer's disease (AD) have characteristic problems navigating everyday environments. While patients may exhibit abnormal gait parameters, adaptive gait irregularities when navigating environments are little explored or understood. The aim of this study was to assess adaptive locomotor responses of AD subjects in a complex environment requiring spatial navigation. A controlled environment of three corridors was set up: straight (I), U-shaped (U) and dog-leg (S). Participants were asked to walk along corridors as part of a counterbalanced repeated-measures design. Three groups were studied: 11 people with posterior cortical atrophy (PCA), 10 with typical Alzheimer's disease (tAD) and 13 controls. Spatio-temporal gait parameters and position within the corridors were monitored with shoe-mounted inertial measurement units (IMUs). Hesitant steps were identified from statistical analysis of the distribution of step time data. Walking paths were generated from position data calculated by double integration of IMU acceleration. People with PCA and tAD had similar gait characteristics, having shorter steps and longer step times than controls. Hesitant steps tended to be clustered within certain regions of the walking paths. IMUs enabled identification of key gait characteristics in this clinical population (step time, length and step hesitancy) and environmental conditions (route complexity) modifying their expression.

Effects of lighting variability on locomotion in posterior cortical atrophy

“…Disproportionately long step times were considered to represent hesitations, consistent with previous observational 1,4 and gait investigations 35 . Individual step times were calculated using threshold resultant acceleration values detecting when the foot was in contact with the floor.…”

“…Medians of observed person‐specific median step times were calculated for each group, combining data from all trials irrespective of shadow condition. Outlying long step times were iteratively identified as follows 35 . For each of the three groups, a three‐level linear mixed model was fitted including random effects for participant, “room condition within participant,” and “trial within participant and room condition.” Outliers with long step times were defined as observations with a standardized residual >3; these were removed, the model refitted, and outlier removal repeated until no further outliers were identified.…”

“…IMU accelerations were converted to standard coordinates and integrated to calculate velocity. Velocity drift was corrected based on periods when feet were in contact with the ground, and corrected velocity integrated to estimate foot position 35 . Walking path straightness index (SI) was calculated as a ratio of the shortest possible path compared to the length of the path actually taken by a participant, with a range (0–1) for which 1 indicated maximum straightness 36 .…”

STEP-UP: Enabling Low-Cost IMU Sensors to Predict the Type of Dementia During Everyday Stair Climbing

“…Previous lab-based research has demonstrated differences in gait parameters such as step-time and walking speed between people with dementia and age-matched controls (Marquis et al, 2002;Waite et al, 2005;Wang et al, 2006;Verghese et al, 2007;Cedervall et al, 2014;Rosso et al, 2017). These studies indicate that the decline is linked to both phenotype and stage of the disease (Allali et al, 2016;Castrillo et al, 2016;Del Campo et al, 2016;McCarthy et al, 2019;Yong et al, 2020). Furthermore, a noticeable decline in gait is thought to predate other cognitive decline (Hall et al, 2000).…”

“…People with typical Alzheimer's Disease (tAD) have characteristic issues when navigating their everyday environments (McCarthy et al, 2019) with a noticeable general decline in gait patterns (Valkanova and Ebmeier, 2017). Previous lab-based research has demonstrated differences in gait parameters such as step-time and walking speed between people with dementia and age-matched controls (Marquis et al, 2002;Waite et al, 2005;Wang et al, 2006;Verghese et al, 2007;Cedervall et al, 2014;Rosso et al, 2017).…”