↓ Skip to main content

Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, August 2017
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 X users
facebook
1 Facebook page

Citations

dimensions_citation
26 Dimensions

Readers on

mendeley
101 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment
Published in
Journal of NeuroEngineering and Rehabilitation, August 2017
DOI 10.1186/s12984-017-0297-z
Pubmed ID
Authors

Lisette H. J. Kikkert, Nicolas Vuillerme, Jos P. van Campen, Bregje A. Appels, Tibor Hortobágyi, Claudine J. C. Lamoth

Abstract

A detailed gait analysis (e.g., measures related to speed, self-affinity, stability, and variability) can help to unravel the underlying causes of gait dysfunction, and identify cognitive impairment. However, because geriatric patients present with multiple conditions that also affect gait, results from healthy old adults cannot easily be extrapolated to geriatric patients. Hence, we (1) quantified gait outcomes based on dynamical systems theory, and (2) determined their discriminative power in three groups: healthy old adults, geriatric patients with- and geriatric patients without cognitive impairment. For the present cross-sectional study, 25 healthy old adults recruited from community (65 ± 5.5 years), and 70 geriatric patients with (n = 39) and without (n = 31) cognitive impairment from the geriatric dayclinic of the MC Slotervaart hospital in Amsterdam (80 ± 6.6 years) were included. Participants walked for 3 min during single- and dual-tasking at self-selected speed while 3D trunk accelerations were registered with an IPod touch G4. We quantified 23 gait outcomes that reflect multiple gait aspects. A multivariate model was built using Partial Least Square- Discriminant Analysis (PLS-DA) that best modelled participant group from gait outcomes. For single-task walking, the PLS-DA model consisted of 4 Latent Variables that explained 63 and 41% of the variance in gait outcomes and group, respectively. Outcomes related to speed, regularity, predictability, and stability of trunk accelerations revealed with the highest discriminative power (VIP > 1). A high proportion of healthy old adults (96 and 93% for single- and dual-task, respectively) was correctly classified based on the gait outcomes. The discrimination of geriatric patients with and without cognitive impairment was poor, with 57% (single-task) and 64% (dual-task) of the patients misclassified. While geriatric patients vs. healthy old adults walked slower, and less regular, predictable, and stable, we found no differences in gait between geriatric patients with and without cognitive impairment. The effects of multiple comorbidities on geriatric patients' gait possibly causes a 'floor-effect', with no room for further deterioration when patients develop cognitive impairment. An accurate identification of cognitive status thus necessitates a multifactorial approach.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 101 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 101 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 19%
Student > Bachelor 14 14%
Researcher 11 11%
Student > Ph. D. Student 11 11%
Student > Doctoral Student 6 6%
Other 6 6%
Unknown 34 34%
Readers by discipline Count As %
Nursing and Health Professions 14 14%
Engineering 12 12%
Medicine and Dentistry 8 8%
Sports and Recreations 7 7%
Psychology 6 6%
Other 12 12%
Unknown 42 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 January 2018.
All research outputs
#14,079,280
of 22,999,744 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#699
of 1,290 outputs
Outputs of similar age
#169,350
of 316,577 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#15
of 24 outputs
Altmetric has tracked 22,999,744 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,290 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 316,577 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.