Aging and partial body weight support affects gait variability

Can't be applied to stroke survivors since none seemed to be in the test subjects. I despised BWSTT because it did nothing to control my spasticity. Fix my spasticity and I would walk normally in no time. 

Aging and partial body weight support affects gait variability

2008, Journal of NeuroEngineering and Rehabilitation

Anastasia Kyvelidou†1, Max J Kurz†1,2, Julie L Ehlers†1 and Nicholas Stergiou*1,3
Address: 1HPER Biomechanics Lab, University of Nebraska at Omaha, 6001 Dodge Street Omaha, NE 68182-0216, USA, 2Laboratory of Integrated Physiology, University of Houston, 3855 Holman Street Houston, TX 77204-6015, USA and 3Environmental, Agricultural and Occupational Health Sciences, College of Public Health, University of Nebraska Medical Center, 985450 Nebraska Medical Center, Omaha, NE 68198-5450, USA Email: Anastasia Kyvelidou - akyvelidou@mail.unomaha.edu; Max J Kurz - mkurz@mail.coe.uh.edu; Julie L Ehlers - jlehlers@unmc.edu; Nicholas Stergiou* - nstergiou@mail.unomaha.edu * Corresponding author    †Equal contributors

Abstract 

Background: 

Aging leads to increases in gait variability which may explain the large incidence of falls in the elderly. Body weight support training may be utilized to improve gait in the elderly and minimize falls. However, before initiating rehabilitation protocols, baseline studies are needed to identify the effect of body weight support on elderly gait variability. Our purpose was to determine the kinematic variability of the lower extremities in young and elderly healthy females at changing levels of body weight support during walking. 

Methods: 

Ten young and ten elderly females walked on a treadmill for two minutes with a body weight support (BWS) system under four different conditions: 1 g, 0.9 g, 0.8 g, and 0.7 g. Three dimensional kinematics was captured at 60 Hz with a Peak Performance high speed video system. Magnitude and structure of variability of the sagittal plane angular kinematics of the right lower extremity was analyzed using both linear (magnitude; standard deviations and coefficient of variations) and nonlinear (structure; Lyapunov exponents) measures. A two way mixed ANOVA was used to evaluate the effect of age and BWS on variability. Results: Linear analysis showed that the elderly presented significantly more variability at the hip and knee joint than the young females. Moreover, higher levels of BWS presented increased variability at all joints as found in both the linear and nonlinear measures utilized. 

Conclusion: 

Increased levels of BWS increased lower extremity kinematic variability. If the intent of BWS training is to decrease variability in gait patterns, this did not occur based on our results. However, we did not perform a training study. Thus, it is possible that after several weeks of training and increased habituation, these initial increased variability values will decrease. This assumption needs to be addressed in future investigation with both "healthy" elderly and elderly fallers. In addition, it is possible that BWS training can have a positive transfer effect by bringing overground kinematic variability to healthy normative levels, which also needs to be explored in future studies.

Dynamic balance and instrumented gait variables are independent predictors of falls following stroke

Fuck, fuck, fuck. More useless predictions rather than coming up with recovery solutions that would prevent such falls. Does no one understand that survivors don't give a shit about fall prediction? They want 100% recovery. GET THERE!

Dynamic balance and instrumented gait variables are independent predictors of falls following stroke 

• Kelly BowerEmail authorView ORCID ID profile,
• Shamala Thilarajah,
• Yong-Hao Pua,
• Gavin Williams,
• Dawn Tan,
• Benjamin Mentiplay,
• Linda Denehy and
• Ross Clark

Journal of NeuroEngineering and Rehabilitation201916:3

https://doi.org/10.1186/s12984-018-0478-4

©  The Author(s). 2019

• Received: 3 September 2018
• Accepted: 19 December 2018
• Published: 7 January 2019

Abstract

Background

Falls are common following stroke and are frequently related to deficits in balance and mobility. This study aimed to investigate the predictive strength of gait and balance variables for evaluating post-stroke falls risk over 12 months following rehabilitation discharge.

Methods

A prospective cohort study was undertaken in inpatient rehabilitation centres based in Australia and Singapore. A consecutive sample of 81 individuals (mean age 63 years; median 24 days post stroke) were assessed within one week prior to discharge. In addition to comfortable gait speed over six metres (6mWT), a depth-sensing camera (Kinect) was used to obtain fast-paced gait speed, stride length, cadence, step width, step length asymmetry, gait speed variability, and mediolateral and vertical pelvic displacement. Balance variables were the step test, timed up and go (TUG), dual-task TUG, and Wii Balance Board-derived centre of pressure velocity during static standing. Falls data were collected using monthly calendars.

Results

Over 12 months, 28% of individuals fell at least once. The faller group had increased TUG time and reduced stride length, gait speed variability, mediolateral and vertical pelvic displacement, and step test scores (P < 0.001–0.048). Significant predictors, when adjusted for country, prior falls and assistance (i.e., physical assistance and/or gait aid use) were stride length, step length asymmetry, mediolateral pelvic displacement, step test and TUG scores (P < 0.040; IQR-odds ratio(OR) = 1.37–7.85). With comfortable gait speed as an additional covariate, to determine the additive benefit over standard clinical assessment, only mediolateral pelvic displacement, TUG and step test scores remained significant (P = 0.001–0.018; IQR-OR = 5.28–10.29).

Conclusions

Reduced displacement of the pelvis in the mediolateral direction during walking was the strongest predictor of post-stroke falls compared with other gait variables.(Well, then create a protocol that has correct pelvis placement. ) Dynamic balance measures, such as the TUG and step test, may better predict falls than gait speed or static balance measures.

Gait Speed and Gait Variability are Associated with Different Functional Brain Networks

Are your therapists determining objectively which of these networks is damaged ? So they have the right protocols to use to correct those problems? I had one PT whose knowledge was essentially that my walking wasn't correct and the instruction was to show himself walking and say' Walk this way'. What a fucking useless piece of information. I expect objective diagnosis of walking irregularities probably with motion sensors and accelerometers, then use that objective diagnosis to select stroke protocols that recover every piece. That is my 'pie in the sky' goal. I expect all stroke medical professionals to be working toward that same goal.

Gait Speed and Gait Variability are Associated with Different Functional Brain Networks

On-Yee Lo^{1, 2*}, Mark A. Halko³, Junhong Zhou^{1, 2}, Rachel Harrison¹, Lewis A. Lipsitz^{1, 2} and Brad Manor^{1, 2}

• ¹Institute for Aging Research, Hebrew SeniorLife, United States
• ²Division of Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, United States
• ³Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, United States

Gait speed and gait variability are clinically-meaningful markers of locomotor control that are suspected to be regulated by multiple supraspinal control mechanisms. The purpose of this study was to evaluate the relationships between these gait parameters and the functional connectivity of brain networks in functionally-limited older adults. Twelve older adults with mild-to-moderate cognition “executive” dysfunction and relatively slow gait, yet free from neurological diseases, completed a gait assessment and a resting state fMRI. Gait speed and variability were associated with the strength of functional connectivity of different brain networks. Those with faster gait speed had stronger functional connectivity within the frontoparietal control network (R=0.61, p=0.04). Those with less gait variability (i.e., steadier walking patterns) exhibited stronger negative functional connectivity between the dorsal attention network and the default network (R=0.78, p<0.01). No other significant relationships between gait metrics and the strength of within- or between- network functional connectivity was observed. Results of this pilot study warrant further investigation to confirm that gait speed and variability are linked to different brain networks in vulnerable older adults.

Keywords: Gait, gait speed, Gait Variability, resting state fMRI, functional connectivity, functional brain networks

Received: 10 Jul 2017; Accepted: 13 Nov 2017.

Edited by:

Philip P. Foster, University of Texas Health Science Center at Houston, United States

Reviewed by:

Graham J. Galloway, Translational Research Institute, Australia
Richard B. Reilly, Trinity College, Dublin, Ireland  

Copyright: © 2017 Lo, Halko, Zhou, Harrison, Lipsitz and Manor. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. On-Yee Lo, Hebrew SeniorLife, Institute for Aging Research, Boston, 02131, MA, United States, AmyLo@hsl.harvard.edu