The effect of biomechanical features on classification of dual-task gait.

Early detection of Alzheimer's Disease and Related Disorders (ADRD) has been a focus of research with the hope that early intervention may improve clinical outcomes. The manifestation of motor impairment in early stages of ADRD has led to the inclusion of gait assessments including spatiotemporal parameters in clinical evaluations. This study aims to determine the effect of adding kinetic and kinematic gait features to classification of different levels of cognitive load in healthy individuals. A dual-task paradigm was used to simulate cognitive impairment in 40 healthy adults, with single-task walking trials representing normal, healthy gait. The Paced Auditory Serial Addition Task was administered at two different inter-stimulus intervals representing two levels of cognitive load in dual-task gait. We predicted that a richer dataset would improve classification accuracy relative to spatiotemporal parameters. Repeated Measures ANOVA showed significant changes in 15 different gait features across all three levels of cognitive load. We used three supervised machine learning algorithms to classify data points using a series of different gait feature sets with performance based on the area under the curve (AUC). Classification yielded 0.778 AUC across all three conditions (0.889 AUC Single vs. Dual) using kinematic and spatiotemporal features compared to 0.724 AUC using spatiotemporal features only (0.792 AUC Single vs. Dual). These data suggest that additional kinematic parameters improve classification performance. However, the benefit of measuring a wider set of parameters compared to their cost needs consideration. Further work will lead to a clinically viable ADRD detection classifier.

How humans use visual optic flow to regulate stepping during walking.

Humans use visual optic flow to regulate average walking speed. Among many possible strategies available, healthy humans walking on motorized treadmills allow fluctuations in stride length (Ln) and stride time (Tn) to persist across multiple consecutive strides, but rapidly correct deviations in stride speed (Sn=Ln/Tn) at each successive stride, n. Several experiments verified this stepping strategy when participants walked with no optic flow. This study determined how removing or systematically altering optic flow influenced peoples' stride-to-stride stepping control strategies. Participants walked on a treadmill with a virtual reality (VR) scene projected onto a 3m tall, 180° semi-cylindrical screen in front of the treadmill. Five conditions were tested: blank screen ("BLANK"), static scene ("STATIC"), or moving scene with optic flow speed slower than ("SLOW"), matched to ("MATCH"), or faster than ("FAST") walking speed. Participants took shorter and faster strides and demonstrated increased stepping variability during the BLANK condition compared to the other conditions. Thus, when visual information was removed, individuals appeared to walk more cautiously. Optic flow influenced both how quickly humans corrected stride speed deviations and how successful they were at enacting this strategy to try to maintain approximately constant speed at each stride. These results were consistent with Weber's law: healthy adults more-rapidly corrected stride speed deviations in a no optic flow condition (the lower intensity stimuli) compared to contexts with non-zero optic flow. These results demonstrate how the temporal characteristics of optic flow influence ability to correct speed fluctuations during walking.

Increased gait variability may not imply impaired stride-to-stride control of walking in healthy older adults: Winner: 2013 Gait and Clinical Movement Analysis Society Best Paper Award.

Older adults exhibit increased gait variability that is associated with fall history and predicts future falls. It is not known to what extent this increased variability results from increased physiological noise versus a decreased ability to regulate walking movements. To "walk", a person must move a finite distance in finite time, making stride length (Ln) and time (Tn) the fundamental stride variables to define forward walking. Multiple age-related physiological changes increase neuromotor noise, increasing gait variability. If older adults also alter how they regulate their stride variables, this could further exacerbate that variability. We previously developed a Goal Equivalent Manifold (GEM) computational framework specifically to separate these causes of variability. Here, we apply this framework to identify how both young and high-functioning healthy older adults regulate stepping from each stride to the next. Healthy older adults exhibited increased gait variability, independent of walking speed. However, despite this, these healthy older adults also concurrently exhibited no differences (all p>0.50) from young adults either in how their stride variability was distributed relative to the GEM or in how they regulated, from stride to stride, either their basic stepping variables or deviations relative to the GEM. Using a validated computational model, we found these experimental findings were consistent with increased gait variability arising solely from increased neuromotor noise, and not from changes in stride-to-stride control. Thus, age-related increased gait variability likely precedes impaired stepping control. This suggests these changes may in turn precede increased fall risk.

Acute high-intensity exercise-induced cognitive enhancement and brain-derived neurotrophic factor in young, healthy adults.

Acute exercise can positively impact cognition. The present study examined the effect of acute high-intensity aerobic exercise on prefrontal-dependent cognitive performance and brain-derived neurotrophic factor (BDNF). Fifty-eight young adults were randomly assigned to one of two experimental groups: (a) an acute bout of high-intensity exercise (n=29) or (b) a non-exercise control (n=29). Participants in the exercise group improved performance on inhibitory control in Stroop interference and on cognitive flexibility in Trail Making Test (TMT) Part-B compared with participants in the control group and increased BDNF immediately after exercise. There was a significant relationship between BDNF and TMT Part-B on the pre-post change following exercise. These findings provide support for the association between improved prefrontal-dependent cognitive performance and increased BDNF in response to acute exercise. We conclude that the changes in BDNF concentration may be partially responsible for prefrontal-dependent cognitive functioning following an acute bout of exercise.