scholarly journals A Preliminary Investigation of the Effects of Obstacle Negotiation and Turning on Gait Variability in Adults with Multiple Sclerosis

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5806
Author(s):  
Lara Weed ◽  
Casey Little ◽  
Susan L. Kasser ◽  
Ryan S. McGinnis
Keyword(s):  
Multiple Sclerosis ◽  
Fall Risk ◽  
Preliminary Investigation ◽  
Gait Variability ◽  
Daily Activities ◽  
Healthy Controls ◽  
Trunk Rotation ◽  
Inertial Measurement ◽  
Gait Parameters ◽  
Measurement Units

Many falls in persons with multiple sclerosis (PwMS) occur during daily activities such as negotiating obstacles or changing direction. While increased gait variability is a robust biomarker of fall risk in PwMS, gait variability in more ecologically related tasks is unclear. Here, the effects of turning and negotiating an obstacle on gait variability in PwMS were investigated. PwMS and matched healthy controls were instrumented with inertial measurement units on the feet, lumbar, and torso. Subjects completed a walk and turn (WT) with and without an obstacle crossing (OW). Each task was partitioned into pre-turn, post-turn, pre-obstacle, and post-obstacle phases for analysis. Spatial and temporal gait measures and measures of trunk rotation were captured for each phase of each task. In the WT condition, PwMS demonstrated significantly more variability in lumbar and trunk yaw range of motion and rate, lateral foot deviation, cadence, and step time after turning than before. In the OW condition, PwMS demonstrated significantly more variability in both spatial and temporal gait parameters in obstacle approach after turning compared to before turning. No significant differences in gait variability were observed after negotiating an obstacle, regardless of turning or not. Results suggest that the context of gait variability measurement is important. The increased number of variables impacted from turning and the influence of turning on obstacle negotiation suggest that varying tasks must be considered together rather than in isolation to obtain an informed understanding of gait variability that more closely resembles everyday walking.

scholarly journals Accuracy and Repeatability of Spatiotemporal Gait Parameters Measured with an Inertial Measurement Unit

2021 ◽  
Vol 10 (9) ◽  
pp. 1804
Author(s):  
Jorge Posada-Ordax ◽  
Julia Cosin-Matamoros ◽  
Marta Elena Losa-Iglesias ◽  
Ricardo Becerro-de-Bengoa-Vallejo ◽  
Laura Esteban-Gonzalo ◽  
...  
Keyword(s):  
Healthy Subjects ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
High Speeds ◽  
Controlled Conditions ◽  
Gait Parameters ◽  
Measurement Units ◽  
Accuracy And Repeatability

In recent years, interest in finding alternatives for the evaluation of mobility has increased. Inertial measurement units (IMUs) stand out for their portability, size, and low price. The objective of this study was to examine the accuracy and repeatability of a commercially available IMU under controlled conditions in healthy subjects. A total of 36 subjects, including 17 males and 19 females were analyzed with a Wiva Science IMU in a corridor test while walking for 10 m and in a threadmill at 1.6 km/h, 2.4 km/h, 3.2 km/h, 4 km/h, and 4.8 km/h for one minute. We found no difference when we compared the variables at 4 km/h and 4.8 km/h. However, we found greater differences and errors at 1.6 km/h, 2.4 km/h and 3.2 km/h, and the latter one (1.6 km/h) generated more error. The main conclusion is that the Wiva Science IMU is reliable at high speeds but loses reliability at low speeds.

scholarly journals Validity and repeatability of inertial measurement units for measuring gait parameters

2017 ◽  
Vol 55 ◽  
pp. 87-93 ◽  
Author(s):  
Edward P. Washabaugh ◽  
Tarun Kalyanaraman ◽  
Peter G. Adamczyk ◽  
Edward S. Claflin ◽  
Chandramouli Krishnan
Keyword(s):  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Gait Parameters ◽  
Measurement Units

Gait Variability Measures Reveal Differences between Multiple Sclerosis Patients and Healthy Controls

Motor Control ◽  
2012 ◽  
Vol 16 (2) ◽  
pp. 229-244 ◽  
Author(s):  
Jeffrey P. Kaipust ◽  
Jessie M. Huisinga ◽  
Mary Filipi ◽  
Nicholas Stergiou
Keyword(s):  
Multiple Sclerosis ◽  
Gait Variability ◽  
Healthy Controls ◽  
Multiple Sclerosis Patients

scholarly journals Personalized Template-Based Step Detection From Inertial Measurement Units Signals in Multiple Sclerosis

2020 ◽  
Vol 11 ◽  
Author(s):  
Aliénor Vienne-Jumeau ◽  
Laurent Oudre ◽  
Albane Moreau ◽  
Flavien Quijoux ◽  
Sébastien Edmond ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Step Detection ◽  
Measurement Units

Gait Mechanics Are Different Between Healthy Controls and Patients With Multiple Sclerosis

2013 ◽  
Vol 29 (3) ◽  
pp. 303-311 ◽  
Author(s):  
Jessie M. Huisinga ◽  
Kendra K. Schmid ◽  
Mary L. Filipi ◽  
Nicholas Stergiou
Keyword(s):  
Multiple Sclerosis ◽  
Joint Torque ◽  
Group Differences ◽  
Healthy Controls ◽  
Joint Power ◽  
Joint Torques ◽  
Gait Parameters ◽  
Healthy Control ◽  
Gait Mechanics ◽  
Walking Velocity

Multiple sclerosis (MS) causes severe gait problems in relatively young individuals, yet there have been limited studies to quantitatively identify the specific gait parameters that are affected. The purpose of this study was to define any differences in biomechanical gait parameters between patients with MS and healthy controls. A total of 31 MS patients and 31 healthy controls were evaluated: joint torques and joint powers were calculated at the ankle, knee, and hip during the stance phase of gait. The self-selected walking velocity was used as a covariate in the analysis to ensure that group differences were not due to differences in walking velocity between the MS and healthy control groups. Reduced angular range, less joint torque, and reduced joint power were seen in patients with MS. We also found significant correlations between biomechanical gait parameters and EDSS score, which provides a clinical rating of disease severity. Our findings provide a quantitative assessment of the gait mechanics employed in patients with MS. The altered lower extremity mechanics observed in patients with MS reflect both a neurological and strength deficit compared with healthy controls during walking.

scholarly journals Accelerometry Reveals Differences in Gait Variability Between Patients with Multiple Sclerosis and Healthy Controls

2012 ◽  
Vol 41 (8) ◽  
pp. 1670-1679 ◽  
Author(s):  
Jessie M. Huisinga ◽  
Martina Mancini ◽  
Rebecca J. St. George ◽  
Fay B. Horak
Keyword(s):  
Multiple Sclerosis ◽  
Gait Variability ◽  
Healthy Controls

scholarly journals Stride-Time Variability and Fall Risk in Persons with Multiple Sclerosis

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Yaejin Moon ◽  
Douglas A. Wajda ◽  
Robert W. Motl ◽  
Jacob J. Sosnoff
Keyword(s):  
Multiple Sclerosis ◽  
Fall Risk ◽  
Postural Sway ◽  
Short Form ◽  
Gait Variability ◽  
Time Variability ◽  
Control Group ◽  
Stride Time ◽  
Fall Risk Factors ◽  
The Relationship

Gait variability is associated with falls in clinical populations. However, gait variability’s link to falls in persons with Multiple Sclerosis (PwMS) is not well established. This investigation examined the relationship between stride-time variability, fall risk, and physiological fall risk factors in PwMS. 17 PwMS (62.8±7.4years) and 17 age-matched controls (62.8±5.9years) performed the 6-minute walk test. Stride-time was assessed with accelerometers attached to the participants’ shanks. Stride-time variability was measured by interstride coefficient of variation (CV) of stride-time. The participant’s fall risk was measured by the short form physiological profile assessment (PPA). A Spearman correlation analysis was used to determine the relationship between variables. Increased fall risk was strongly associated with increased stride-time CV in both PwMS (ρ=0.71,p<0.01) and the controls (ρ=0.67,p<0.01). Fall risk was not correlated with average stride-time (p>0.05). In PwMS, stride-time CV was related to postural sway (ρ=0.74,p<0.01) while in the control group, it was related to proprioception (ρ=0.61,p<0.01) and postural sway (ρ=0.78,p<0.01). Current observations suggest that gait variability is maybe more sensitive marker of fall risk than average gait parameters in PwMS. It was also noted that postural sway may be potentially targeted to modify gait variability in PwMS.

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