11th Clinical Trials on Alzheimer's Disease (CTAD) 2018 Barcelona

Can digital footprints capture clinically relevant gait endpoints in non-clinically setting? A Proof of Concept

M. Mc Carthy, C. Gon



gait analysis, plantar pressure


This proof of concept has two components; mining the literature to identify the gait parameters that correlate with cognitive decline and determining if those endpoints could be captured using smart-insoles. There is growing interest in gait change as a marker for cognitive decline, with reports of gait disturbances found to precede dementia by more than 5 years. The use of wrist worn physical activity monitors (PAM) to collect steps and gait cadence is well established. While gait speed has been identified as signal, other spatiotemporal characteristics also appear have potential as key indicators of cognitive decline. Assessing spatiotemporal gait is not a simple process with the use of electronic walkways and specialist clinics common. This can impact the number of locations available for gait assessments particularly in clinical trials. New technology such as smart-insoles is emerging. This has the potential to capture more nuanced assessment of gait change including balance, inter-gait variability even stance. If alternative viable technologies were available gait could be assessed outside of specialist clinics, including residential care setting or the patient’s own home.

Moticon's Summary

This proof-of-concept study explores the use of Moticon sensor insoles to identify gait parameters correlated with cognitive decline. Gait changes, such as disturbances preceding dementia, are gaining attention as markers for cognitive impairment. Traditionally, gait speed, stride time variability (STV), and balance are assessed in specialist clinics, limiting accessibility. Sensor insoles could enable broader, more nuanced gait assessments outside these settings. Methods involved a literature review to identify key gait parameters and practical testing with two healthy volunteers using Moticon sensor insoles. Gait was assessed at various speeds set by a metronome, STV was measured through swing duration variability, and balance was evaluated using Berg Balance assessment tasks. Results showed that sensor insoles successfully quantified gait speed and STV, highlighting their potential for use in non-clinical settings.

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