Detection and localisation of hesitant steps in people with Alzheimer's disease navigating routes of varying complexity. Issue 2 (24th April 2019)

• Record Type: Journal Article
• Authors: McCarthy, Ian; Suzuki, Tatsuto; Holloway, Catherine; Poole, Teresa; Frost, Chris; Carton, Amelia; Tyler, Nick; Crutch, Sebastian; Yong, Keir
• Is Part Of: Healthcare technology letters. Volume 6:Issue 2(2019)
• Page Start: 42
• Page End: 47
• Publication Date: 2019-04-24
• Subjects: statistical analysis -- diseases -- gait analysis -- biomedical measurement -- patient monitoring; walking paths -- step hesitancy -- route complexity -- Alzheimer's disease navigating routes -- abnormal gait parameters -- gait irregularities -- adaptive locomotor responses -- spatial navigation -- corridors -- dog‐leg -- counterbalanced repeated‐measures design -- posterior cortical atrophy -- shoe‐mounted inertial measurement units -- step time data -- position data -- Alzheimer's disease -- gait characteristics -- IMU acceleration -- statistical analysi; Biomedical engineering -- Periodicals; Medical technology -- Periodicals; 610.28
• DOI: 10.1049/htl.2018.5034
• Languages: English
• ISSNs: 2053-3713

Abstract

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.