The ability of gait kinematic parameters to predict falls in older adults with cognitive impairments living in long term institutions

Marques, Nise Ribeiro; Camilo, Giovanna Ferreira; Santos, Ana Paula de Martini Lopes dos; Cardoso, Bruna Carvalho; Navega, Marcelo Tavella; Abreu, Daniela Cristina Carvalho de

doi:10.1016/j.clinbiomech.2019.04.011

Cited by 6 publications

(6 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This gait disturbance also can be re ected under dual task condition when performing naming animals test. The greater variability of stride length in MCI were also reported in other studies [20,21]. Moreover, our study identi ed that in dual task mode, swing time, in paralleled with the percent of terminal swing phase in a gait cycle greatly reduced in cognitively impaired individuals compared to normal aging people.…”

Section: Discussionsupporting

confidence: 86%

Spatiotemporal gait parameter fluctuations in older adults affected by mild cognitive impairment: comparisons among three cognitive dual-task tests

Ma²,

Wang

et al. 2023

Preprint

View full text Add to dashboard Cite

Backgrounds: Gait disorder is associated with cognitive functional impairment, and this disturbance is more pronouncedly when performing additional cognitive tasks. Our study aimed to characterize gait disorders in mild cognitive impairment (MCI) under three dual tasks and determine the association between gait performance and cognitive function. Methods: A total of 260 participants were enrolled in this cross-sectional study and divided into MCI and cognitively normal control. Spatiotemporal and kinematic gait parameters (31 items) in single task and three dual tasks (serial 100-7, naming animals and words recall) were measured using a wearable sensor. Baseline characteristics of the two groups were balanced using propensity score matching. Important gait features were filtered using random forest method and LASSO regression and further described using logistic analysis. Results: After matching, 106 participants with MCI and 106 normal controls were recruited. Top 5 gait features in random forest and 4~6 important features in LASSO regression were selected. Robust variables associating with cognitive function were temporal gait parameters. Participants with MCI exhibited decreased swing time and terminal swing, increased mid stance and variability of stride length compared with normal control. Subjects walked slower when performing an extra dual cognitive task. In the three dual tasks, words recall test exhibited more pronounced impact on gait regularity, velocity and dual task cost than the other two cognitive tests. Conclusion:Gait assessment under dual task conditions, particularly in words recall test, using wearable sensors could be useful as a complementary strategy for early detection of MCI.

show abstract

Section: Discussionsupporting

confidence: 86%

Spatiotemporal gait parameter fluctuations in older adults affected by mild cognitive impairment: comparisons among three cognitive dual-task tests

Ma²,

Wang

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…This gait disturbance also can be reflected under dual task condition when performing naming animals test. The greater variability of stride length in MCI were also reported in other studies [ 42 , 43 ]. Moreover, our study identified that in dual task mode, temporal gait parameters swing time, in paralleled with the percent of terminal swing phase in a gait cycle greatly reduced in cognitively impaired individuals compared to normal aging people.…”

Section: Discussionsupporting

confidence: 85%

Spatiotemporal gait parameter fluctuations in older adults affected by mild cognitive impairment: comparisons among three cognitive dual-task tests

Du,

Ma,

Wang

et al. 2023

BMC Geriatr

View full text Add to dashboard Cite

Backgrounds Gait disorder is associated with cognitive functional impairment, and this disturbance is more pronouncedly when performing additional cognitive tasks. Our study aimed to characterize gait disorders in mild cognitive impairment (MCI) under three dual tasks and determine the association between gait performance and cognitive function. Methods A total of 260 participants were enrolled in this cross-sectional study and divided into MCI and cognitively normal control. Spatiotemporal and kinematic gait parameters (31 items) in single task and three dual tasks (serial 100-7, naming animals and words recall) were measured using a wearable sensor. Baseline characteristics of the two groups were balanced using propensity score matching. Important gait features were filtered using random forest method and LASSO regression and further described using logistic analysis. Results After matching, 106 participants with MCI and 106 normal controls were recruited. Top 5 gait features in random forest and 4 ~ 6 important features in LASSO regression were selected. Robust variables associating with cognitive function were temporal gait parameters. Participants with MCI exhibited decreased swing time and terminal swing, increased mid stance and variability of stride length compared with normal control. Subjects walked slower when performing an extra dual cognitive task. In the three dual tasks, words recall test exhibited more pronounced impact on gait regularity, velocity, and dual task cost than the other two cognitive tests. Conclusion Gait assessment under dual task conditions, particularly in words recall test, using portable sensors could be useful as a complementary strategy for early detection of MCI.

show abstract

“…The mean speed, step length, and step duration matched the expected values for all cases (compare Tables 1 and 2 for an example). The step duration standard deviations were mostly on the order of 0.001 to 0.01 s. This is somewhat lower than is typically reported for human subjects (order 0.01 to 0.1 s) [25,[40][41][42] but somewhat higher than in another simulation study (order 0.001 s) [24]. This study's step length standard deviation (order 10 −10 m) was much lower than in human experiments (order 10 −2 m) [40,42].…”

Section: Comparison To Human Gait Parameter Valuesmentioning

confidence: 61%

Predicting fall risk using multiple mechanics-based metrics for a planar biped model

Williams

Martin

2023

PLoS ONE

View full text Add to dashboard Cite

For both humans and robots, falls are undesirable, motivating the development of fall prediction models. Many mechanics-based fall risk metrics have been proposed and validated to varying degrees, including the extrapolated center of mass, the foot rotation index, Lyapunov exponents, joint and spatiotemporal variability, and mean spatiotemporal parameters. To obtain a best-case estimate of how well these metrics can predict fall risk both individually and in combination, this work used a planar six-link hip-knee-ankle biped model with curved feet walking at speeds ranging from 0.8 m/s to 1.2 m/s. The true number of steps to fall was determined using the mean first passage times from a Markov chain describing the gaits. In addition, each metric was estimated using the Markov chain of the gait. Because calculating the fall risk metrics from the Markov chain had not been done before, the results were validated using brute force simulations. Except for the short-term Lyapunov exponents, the Markov chains could accurately calculate the metrics. Using the Markov chain data, quadratic fall prediction models were created and evaluated. The models were further evaluated using differing length brute force simulations. None of the 49 tested fall risk metrics could accurately predict the number of steps to fall by themselves. However, when all the fall risk metrics except the Lyapunov exponents were combined into a single model, the accuracy increased substantially. These results suggest that multiple fall risk metrics must be combined to obtain a useful measure of stability. As expected, as the number of steps used to calculate the fall risk metrics increased, the accuracy and precision increased. This led to a corresponding increase in the accuracy and precision of the combined fall risk model. 300 step simulations seemed to provide the best tradeoff between accuracy and using as few steps as possible.

show abstract

The ability of gait kinematic parameters to predict falls in older adults with cognitive impairments living in long term institutions

Cited by 6 publications

References 14 publications

Spatiotemporal gait parameter fluctuations in older adults affected by mild cognitive impairment: comparisons among three cognitive dual-task tests

Spatiotemporal gait parameter fluctuations in older adults affected by mild cognitive impairment: comparisons among three cognitive dual-task tests

Spatiotemporal gait parameter fluctuations in older adults affected by mild cognitive impairment: comparisons among three cognitive dual-task tests

Predicting fall risk using multiple mechanics-based metrics for a planar biped model

Contact Info

Product

Resources

About