Gait variability: methods, modeling and meaning

The study of gait variability, the stride-to-stride fluctuations in walking, offers a complementary way of quantifying locomotion and its changes with aging and disease as well as a means of monitoring the effects of therapeutic interventions and rehabilitation. Previous work has suggested that measures of gait variability may be more closely related to falls, a serious consequence of many gait disorders, than are measures based on the mean values of other walking parameters. The Current JNER series presents nine reports on the results of recent investigations into gait variability. One novel method for collecting unconstrained, ambulatory data is reviewed, and a primer on analysis methods is presented along with a heuristic approach to summarizing variability measures. In addition, the first studies of gait variability in animal models of neurodegenerative disease are described, as is a mathematical model of human walking that characterizes certain complex (multifractal) features of the motor control's pattern generator. Another investigation demonstrates that, whereas both healthy older controls and patients with a higher-level gait disorder walk more slowly in reduced lighting, only the latter's stride variability increases. Studies of the effects of dual tasks suggest that the regulation of the stride-to-stride fluctuations in stride width and stride time may be influenced by attention loading and may require cognitive input. Finally, a report of gait variability in over 500 subjects, probably the largest study of this kind, suggests how step width variability may relate to fall risk. Together, these studies provide new insights into the factors that regulate the stride-to-stride fluctuations in walking and pave the way for expanded research into the control of gait and the practical application of measures of gait variability in the clinical setting

Is Freezing of Gait in Parkinson's Disease a Result of Multiple Gait Impairments? Implications for Treatment

Several gait impairments have been associated with freezing of gait (FOG) in patients with Parkinson's disease (PD). These include deteriorations in rhythm control, gait symmetry, bilateral coordination of gait, dynamic postural control and step scaling. We suggest that these seemingly independent gait features may have mutual interactions which, during certain circumstances, jointly drive the predisposed locomotion system into a FOG episode. This new theoretical framework is illustrated by the evaluation of the potential relationships between the so-called “sequence effect”, that is, impairments in step scaling, and gait asymmetry just prior to FOG. We further discuss what factors influence gait control to maintain functional gait. “Triggers”, for example, such as attention shifts or trajectory transitions, may precede FOG. We propose distinct categories of interventions and describe examples of existing work that support this idea: (a) interventions which aim to maintain a good level of locomotion control especially with respect to aspects related to FOG; (b) those that aim at avoiding FOG “triggers”; and (c) those that merely aim to escape from FOG once it occurs. The proposed theoretical framework sets the stage for testable hypotheses regarding the mechanisms that lead to FOG and may also lead to new treatment ideas

Shedding light on walking in the dark: the effects of reduced lighting on the gait of older adults with a higher-level gait disorder and controls

OBJECTIVE: To study the effects of reduced lighting on the gait of older adults with a high level gait disorder (HLGD) and to compare their response to that of healthy elderly controls. METHODS: 22 patients with a HLGD and 20 age-matched healthy controls were studied under usual lighting conditions (1000 lumens) and in near darkness (5 lumens). Gait speed and gait dynamics were measured under both conditions. Cognitive function, co-morbidities, depressive symptoms, and vision were also evaluated. RESULTS: Under usual lighting conditions, patients walked more slowly, with reduced swing times, and increased stride-to-stride variability, compared to controls. When walking under near darkness conditions, both groups slowed their gait. All other measures of gait were not affected by lighting in the controls. In contrast, patients further reduced their swing times and increased their stride-to-stride variability, both stride time variability and swing time variability. The unique response of the patients was not explained by vision, mental status, co-morbidities, or the values of walking under usual lighting conditions. CONCLUSION: Walking with reduced lighting does not affect the gait of healthy elderly subjects, except for a reduction in speed. On the other hand, the gait of older adults with a HLGD becomes more variable and unsteady when they walk in near darkness, despite adapting a slow and cautious gait. Further work is needed to identify the causes of the maladaptive response among patients with a HLGD and the potential connection between this behavior and the increased fall risk observed in these patients

Objective Assessment of Fall Risk in Parkinson's Disease Using a Body-Fixed Sensor Worn for 3 Days

Background: Patients with Parkinson's disease (PD) suffer from a high fall risk. Previous approaches for evaluating fall risk are based on self-report or testing at a given time point and may, therefore, be insufficient to optimally capture fall risk. We tested, for the first time, whether metrics derived from 3 day continuous recordings are associated with fall risk in PD. Methods and Materials 107 patients (Hoehn & Yahr Stage: 2.6±0.7) wore a small, body-fixed sensor (3D accelerometer) on lower back for 3 days. Walking quantity (e.g., steps per 3-days) and quality (e.g., frequency-derived measures of gait variability) were determined. Subjects were classified as fallers or non-fallers based on fall history. Subjects were also followed for one year to evaluate predictors of the transition from non-faller to faller. Results: The 3 day acceleration derived measures were significantly different in fallers and non-fallers and were significantly correlated with previously validated measures of fall risk. Walking quantity was similar in the two groups. In contrast, the fallers walked with higher step-to-step variability, e.g., anterior-posterior width of the dominant frequency was larger (p = 0.012) in the fallers (0.78±0.17 Hz) compared to the non-fallers (0.71±0.07 Hz). Among subjects who reported no falls in the year prior to testing, sensor-derived measures predicted the time to first fall (p = 0.0034), whereas many traditional measures did not. Cox regression analysis showed that anterior-posterior width was significantly (p = 0.0039) associated with time to fall during the follow-up period, even after adjusting for traditional measures. Conclusions/Significance: These findings indicate that a body-fixed sensor worn continuously can evaluate fall risk in PD. This sensor-based approach was able to identify transition from non-faller to faller, whereas many traditional metrics were not successful. This approach may facilitate earlier detection of fall risk and may in the future, help reduce high costs associated with falls

Automated detection of near falls: algorithm development and preliminary results

<p>Abstract</p> <p>Background</p> <p>Falls are a major source of morbidity and mortality among older adults. Unfortunately, self-report is, to a large degree, the gold-standard method for characterizing and quantifying fall frequency. A number of studies have demonstrated that near falls predict falls and that near falls may occur more frequently than falls. These studies suggest that near falls might be an appropriate fall risk measure. However, to date, such investigations have also relied on self-report. The purpose of the present study was to develop a method for automatic detection of near falls, potentially a sensitive, objectivemarker of fall risk and to demonstrate the ability to detect near falls using this approach.</p> <p>Findings</p> <p>15 healthy subjects wore a tri-axial accelerometer on the pelvis as they walked on a treadmill under different conditions. Near falls were induced by placing obstacles on the treadmill and were defined using observational analysis. Acceleration-derived parameters were examined as potential indicators of near falls, alone and in various combinations. 21 near falls were observed and compared to 668 "non-near falls" segments, consisting of normal and abnormal (but not near falls) gait. The best single method was based on the maximum peak-to-peak vertical acceleration derivative, with detection rates better than 85% sensitivity and specificity.</p> <p>Conclusions</p> <p>These findings suggest that tri-axial accelerometers may be used to successfully distinguish near falls from other gait patterns observed in the gait laboratory and may have the potential for improving the objective evaluation of fall risk, perhaps both in the lab and in at home-settings.</p

Impact of sub-thalamic nucleus deep brain stimulation on dual tasking gait in Parkinson’s disease

Background: The beneficial effects of bilateral sub-thalamic nucleus deep brain stimulation on motor function and gait in advanced Parkinson’s disease are established. Less is known about the effect of stimulation on cognitive function and the capacity to walk while dual tasking, an ability that has been related to fall risk. Everyday walking takes place in complex environments that often require multi-tasking. Hence, dual tasking gait performance reflects everyday ambulation as well as gait automaticity. The purpose of this study was to examine the impact of sub-thalamic nucleus deep brain stimulation on dual task walking in patients with advanced Parkinson’s disease. Methods: Gait was assessed using a performance-based test and by quantifying single-task and dual task walking conditions in 28 patients with advanced Parkinson’s disease. These tests were conducted in 4 conditions: “OFF” medication, with the stimulator turned on and off, and “ON” medication, with the stimulator turned on and off. A previously validated, computerized neuro-psychological battery assessed executive function, attention and memory “OFF” and “ON” deep brain stimulation, after subjects took their anti-Parkinsonian medications. Results: Stimulation improved motor function and the spatiotemporal parameters of gait (e.g., gait speed) during both single-task and dual task walking conditions. Attention improved, but executive function did not. The dual task effect on gait did not change in response to stimulation. For example, during serial 3 subtractions, gait speed was reduced by -0.20 ± 0.14 m/sec while OFF DBS and OFF meds and by -0.22 ± 0.14 m/sec when the DBS was turned on (p = 0.648). Similarly, ON medication, serial 3 subtractions reduced gait speed by -0.20 ± 0.16 m/sec OFF DBS and by -0.22 ± 0.09 m/sec ON DBS (p = 0.543). Conclusions: Bilateral sub-thalamic nucleus deep brain stimulation improves motor symptoms, certain features of gait and even some aspects of cognitive function. However, stimulation apparently fails to reduce the negative impact of a dual task on walking abilities. These findings provide new insight into the effects of deep brain stimulation on gait during cognitively challenging conditions and everyday walking

Gait unsteadiness and fall risk in two affective disorders: a preliminary study

BACKGROUND: In older adults, depression has been associated with increased fall risk, but the reasons for this link are not fully clear. Given parallels between major depression and Parkinson's disease, we hypothesized that major depression and related affective disorders would be associated with impairment in the ability to regulate the stride-to-stride fluctuations in gait cycle timing. METHODS: We measured stride-to-stride fluctuations of patients with two forms of mood disorders, unipolar major depressive disorder (MDD) and bipolar disorder, and compared their gait to that of a healthy control group. The primary outcomes were two measures of gait unsteadiness that have been associated with fall risk: stride time variability and swing time variability. RESULTS: Compared to the control group, the two patient groups tended to walk more slowly and with decreased swing time and increased stride time. However, none of these differences was statistically significant. Compared to the control group, swing time variability was significantly larger in the subjects with bipolar disorder (p < 0.0001) and in the subjects with MDD (p < 0.0004). CONCLUSIONS: Patients with MDD and patients with bipolar disorder display gait unsteadiness. This perturbation in gait may provide a mechanistic link connecting depression and falls. The present findings also suggest the possibility that measurement of variability of gait may provide a readily quantifiable objective approach to monitoring depression and related affective disorders