What can everyday walking tell us about dementia and its subtypes? Ríona Mc Ardle, Brook Galna, Alan Thomas and Lynn Rochester Institute of Neuroscience | Newcastle University Institute of Neuroscience, Newcastle University https://research.ncl.ac.uk/bam/ |
@BAM_Research | @RionaMcArdle |
[email protected]
Results
Introduction Lab-based gait assessment suggests different dementia subtypes have unique gait patterns that
Table 1: Descriptive information of study participants
may aid differential diagnosis [1]. However, this method is expensive and not indicative of everyday behaviour. Body-worn sensors allow us to quantify habitual walking patterns (micro gait) and activity (macro gait) over prolonged periods in a person’s everyday environment [2].
Aims:
Controls
AD
DLB
PDD
N
26
34
29
18
Age
74 ± 9
77 ±7
76 ±6
79 ± 6
Sex (F/M)
15/11
22/12
5/24
3/15
Faller (Y/N)
5/21
15/19
12/17
12/6
MMSE
29 ± 1
23 ± 4
24 ± 4
24 ± 4
Walking patterns in dementia subtypes
Investigate differences in habitual walking patterns and activity between dementia subtypes and older adult controls
People with dementia are slower and take shorter, more variable steps compared to controls (Figure 2). AD and PDD are also more asymmetric in their gait. People with PDD are more variable and take quicker, shorter steps compared to AD and DLB. They are also more asymmetric in their gait compared to DLB.
Methods Body-worn sensors collected gait data over 7 days in groups of older adults and people with very mild to moderate Alzheimer’s disease (AD), dementia with Lewy bodies (DLB) and
People with DLB are more variable and less asymmetric in their step length compared to AD.
Parkinson’s disease with dementia (PDD; see figure 1).
Figure 2: Walking patterns across dementia subtypes. Dementia subtypes are represented by z scores showing how they differ from controls. One-way ANOVA and Kruskal Wallis tests showed significant group differences for all gait variables.
Walking activity in dementia subtypes People with dementia walk less and take shorter, less variable walking bouts compared to controls (Figure 3). Walking activity is especially reduced in PDD than other dementia subtypes.
Mean Step Velocity Mean Step Length Swing Time Variability Stance Time Variability Step Time Variability
Pace
Volume Rhythm
Micro Gait
Variability
Asymmetry
Postural Control
Mean Step Time Mean Swing Time Mean Stance Time
Step Velocity Variability Step Length Variability
Swing Time Asymmetry Step Time Asymmetry Stance Time Asymmetry
Macro Gait
Total walking time Total steps Total bouts Mean bout length
Pattern
Variability
Alpha
Variability of bout length
Step Length Asymmetry
Figure 1: Example of methodology, data processing and gait outcomes collected
Conclusions People with different dementia subtypes have unique gait impairments compared to controls and each other. This may aid differential diagnosis for dementia. People with dementia are less active and variable in their habitual walking activity. This is more pronounced in DLB and PDD who also tend to take shorter walking bouts. Body-worn monitors can provide a comprehensive picture of habitual walking behaviours, which may improve detection, diagnosis and management of dementia.
Figure 3: Walking activity across dementia subtypes. Dementia subtypes are represented by z scores showing how they differ from controls. One-way ANOVA and Kruskal Wallis tests showed significant group differences for all walking measures.
Acknowledgements
References
This research was supported by the Alzheimer’s Society and the National Institute for Health Research (NIHR) Newcastle Biomedical Research Unit and Newcastle Biomedical Research Centre based at Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.
1. Mc Ardle et al., 2017. What Can Quantitative Gait Analysis Tell Us about Dementia and Its Subtypes? A Structured Review. Jrnl Alz Dis 2. Mc Ardle et al.,2018. Gait in Mild Alzheimer’s Disease: Feasibility of Multi-Center Measurement in the Clinic and Home with Body-Worn Sensors - A Pilot Study. Jrnl Alz Dis
