Age related changes in gait variability, asymmetry, and bilateral coordination - When does deterioration starts?

BACKGROUND: Gait pattern coordination is affected by several factors (e.g., neurodegeneration), while aging is known to have a significant negative impact. Various gait parameters, such as gait asymmetry (GA) and stride time coefficient of variation (CV), are widely used in both research and clinical settings in order to evaluate human locomotion. Another parameter is the phase coordination index (PCI), which specifically assesses bilateral coordination of gait (BCG), by quantifying the consistency and accuracy of the anti-phased stepping pattern. OBJECTIVE: In this study we hypothesized that there is a steady deterioration in the bilateral coordination of walking through ageing, and in gait rhythmicity, which would be evident by an increase in the values of the coordination parameters which are examined. METHODS: We analyzed gait cycles of 66 healthy participants in ages between 40 and 85 years which were divided into five age groups (40-44; 45-54; 55-64; 75 +). The participants performed corridor walking (i.e., back and forth) wearing a computerized motion sensor-based gait analysis system. PCI, CV and GA parameters were calculated for the straight-line walking segments. RESULTS: PCI values remained relatively stable between the ages of 40-75 (3.16 ± 1.11%), while in the age group of 75 + years old we observed a significant increase (i.e., deterioration in BCG) in PCI values (5.68 ± 2.01%, p < 0.047). Same pattern was seen for the CV parameter. However, GA was not statistically significantly different between all age groups. CONCLUSION: It appears that PCI and CV are more sensitive measures to detect changes in gait through the aging process. The results suggest that potential screening to detect salient gait deterioration should start from the age of 70. On the other hand, GA may be used to identify neurological impairments if found increased at any age.

Gait Speed Modulations Are Proportional to Grades of Virtual Visual Slopes-A Virtual Reality Study.

Gait is a complex mechanism relying on integration of several sensory inputs such as vestibular, proprioceptive, and visual cues to maintain stability while walking. Often humans adapt their gait to changes in surface inclinations, and this is typically achieved by modulating walking speed according to the inclination in order to counteract the gravitational forces, either uphill (exertion effect) or downhill (braking effect). The contribution of vision to these speed modulations is not fully understood. Here we assessed gait speed effects by parametrically manipulating the discrepancy between virtual visual inclination and the actual surface inclination (aka visual incongruence). Fifteen healthy participants walked in a large-scale virtual reality (VR) system on a self-paced treadmill synchronized with projected visual scenes. During walking they were randomly exposed to varying degrees of physical-visual incongruence inclinations (e.g., treadmill leveled & visual scene uphill) in a wide range of inclinations (-15° to +15°). We observed an approximately linear relation between the relative change in gait speed and the anticipated gravitational forces associated with the virtual inclinations. Mean relative gait speed increase of ~7%, ~11%, and ~17% were measured for virtual inclinations of +5°, +10°, and +15°, respectively (anticipated decelerating forces were proportional to sin[5°], sin[10°], sin[15°]). The same pattern was seen for downhill virtual inclinations with relative gait speed modulations of ~-10%, ~-16%, and ~-24% for inclinations of -5°, -10°, and -15°, respectively (in anticipation of accelerating forces). Furthermore, we observed that the magnitude of speed modulation following virtual inclination at ±10° was associated with subjective visual verticality misperception. In conclusion, visual cues modulate gait speed when surface inclinations change proportional to the anticipated effect of the gravitational force associated the inclinations. Our results emphasize the contribution of vision to locomotion in a dynamic environment and may enhance personalized rehabilitation strategies for gait speed modulations in neurological patients with gait impairments.

Vision Affects Gait Speed but not Patterns of Muscle Activation During Inclined Walking-A Virtual Reality Study.

While walking, our locomotion is affected by and adapts to the environment based on vision- and body-based (vestibular and proprioception) cues. When transitioning to downhill walking, we modulate gait by braking to avoid uncontrolled acceleration, and when transitioning to uphill walking, we exert effort to avoid deceleration. In this study, we aimed to measure the influence of visual inputs on this behavior and on muscle activation. Specifically, we aimed to explore whether the gait speed modulations triggered by mere visual cues after transitioning to virtually inclined surface walking are accompanied by changes in muscle activation patterns typical to those triggered by veridical (gravitational) surface inclination transitions. We used an immersive virtual reality system equipped with a self-paced treadmill and projected visual scenes that allowed us to modulate physical-visual inclination congruence parametrically. Gait speed and leg muscle electromyography were measured in 12 healthy young adults. In addition, the magnitude of subjective visual verticality misperception (SVV) was measured by the rod and frame test. During virtual (non-veridical) inclination transitions, vision modulated gait speed by (i) slowing down to counteract the excepted gravitational "boost" in virtual downhill inclinations and (ii) speeding up to counteract the expected gravity resistance in virtual uphill inclinations. These gait speed modulations were reflected in muscle activation intensity changes and associated with SVV misperception. However, temporal patterns of muscle activation were not affected by virtual (visual) inclination transitions. Our results delineate the contribution of vision to locomotion and may lead to enhanced rehabilitation strategies for neurological disorders affecting movement.

Sedative drugs modulate the neuronal activity in the subthalamic nucleus of parkinsonian patients.

Microelectrode recording (MER) is often used to identify electrode location which is critical for the success of deep brain stimulation (DBS) treatment of Parkinson's disease. The usage of anesthesia and its' impact on MER quality and electrode placement is controversial. We recorded neuronal activity at a single depth inside the Subthalamic Nucleus (STN) before, during, and after remifentanil infusion. The root mean square (RMS) of the 250-6000 Hz band-passed signal was used to evaluate the regional spiking activity, the power spectrum to evaluate the oscillatory activity and the coherence to evaluate synchrony between two microelectrodes. We compare those to new frequency domain (spectral) analysis of previously obtained data during propofol sedation. Results showed Remifentanil decreased the normalized RMS by 9% (P < 0.001), a smaller decrease compared to propofol. Regarding the beta range oscillatory activity, remifentanil depressed oscillations (drop from 25 to 5% of oscillatory electrodes), while propofol did not (increase from 33.3 to 41.7% of oscillatory electrodes). In the cases of simultaneously recorded oscillatory electrodes, propofol did not change the synchronization while remifentanil depressed it. In conclusion, remifentanil interferes with the identification of the dorsolateral oscillatory region, whereas propofol interferes with RMS identification of the STN borders. Thus, both have undesired effect during the MER procedure.Trial registration: NCT00355927 and NCT00588926.

Using the loading response peak for defining gait cycle timing: A novel solution for the double-belt problem.

Split-belt treadmills (SBTM) contain force plates under each belt that measure ground reaction force (GRF). Initial contact (IC) detection for each gait cycle obtained from the GRF is used for calculating temporal gait parameters (e.g., gait variability, step time, stride time). Occasionally, the participant steps with one leg on the contralateral belt (i.e., crossing) making the IC undetectable and the calculation of temporal gait parameters are compromised. We term this the double-belt problem (DBP). OBJECTIVE: here we developed a complementary detection method using the loading response peak (LRP), anchor point for calculating gait parameters. METHODS: we used GRF gait data from twenty adults (age 56.45 ± 4.81 y; 6 males) who walked on an SBTM. First, we used no-crossing gait periods free of the DBP to calculate stride time, step time, and stride time to stride time coefficient of variation and evaluated the true error and the normalized true error of the LRP detection method. Then, we used multiple comparisons between no-crossing data and crossing data. RESULTS: we found that normalized errors (in comparison to the IC method) are ≤5.1%. Strong correlations were found between gait parameters computed based on the two detection methods (Intraclass correlation coefficient ≥0.97; p ≤ 0.001). CONCLUSION: detecting gait cycle timing based on the LRP detection method is reliable for estimating temporal gait parameters, demonstrating high correspondence with the gold standard IC detection method.