Biology subjects

Martini, D. N.

Publications and source records attributed to Martini, D. N..

4 recordsLinked to original sources

bioRxiv2025

Posterior parietal cortex activity during visually cued gait: a preliminary study

Safe gait requires visually cued (VC) step adjustments for negotiating targets and obstacles. Effective step adjustments rely on good visuospatial processing. The posterior parietal cortex (PPC) is implicated in visuospatial processing, yet empirical evidence is limited for the PPCs role during gait in humans. Increased cortical control of gait is associated with higher gait variability, a marker of gait performance and fall risk among older adults. However, the cortical underpinnings of gait variability in visually complex environments are not well established. The primary aim of this preliminary study was to assess PPC activity during VC gait and VC gait with perturbations (VCP). A secondary aim was to determine how PPC activity relates to gait variability during VC and VCP gait. Twenty-one healthy young adults completed three treadmill gait conditions at preferred speed: non-cued (NC) gait, VC gait, where stepping targets were presented in a regular pattern, and VCP gait, where stepping target positions were pseudorandomly shifted. Functional near-infrared spectroscopy quantified relative changes in deoxygenated and oxygenated hemoglobin ({Delta}HbO2) concentrations in the PPC. Inertial measurement units quantified gait variability. Moderate effects were observed for more positive {Delta}HbO2 from NC to both VC and VCP gait, likely reflecting the increased visuospatial processing demands. Stride time variability was positively correlated with PPC {Delta}HbO2 during VC gait, suggesting a potential role for the PPC in modulating temporal components of VC gait. Extending these findings to older adults will help to elucidate the PPCs role in gait adaptability and fall risk with aging.

neuroscience↗

bioRxiv2024

Walking with increased step length variability increases the metabolic cost of walking

Older adults and neurological populations tend to walk with slower speeds, more gait variability, and a higher metabolic cost. This higher metabolic cost could be related to their increased gait variability, but this relationship is still unclear. The purpose of this study was to determine how increased step length variability affects the metabolic cost of waking. Eighteen healthy young adults completed a set of 5-minute trials of treadmill walking at 1.20 m/s while we manipulated their step length variability. Illuminated rectangles were projected onto the surface of a treadmill to cue step length variabilities of 0, 5 and 10% (coefficient of variation). Actual step lengths and their variability were tracked with reflective markers on the feet, while metabolic cost was measured using indirect calorimetry. Changes in metabolic cost across habitual walking (no projections) and the three variability conditions were analyzed using a linear mixed effects model. Metabolic power was largest in the 10% condition (4.30 {+/-} 0.23 W/kg) compared to 0% (4.16 {+/-} 0.18 W/kg) and habitual (3.98 {+/-} 0.25 W/kg). The participants actual step length variability did not match projected conditions for 0% (3.10%) and 10% (7.03%). For every 1% increase in step length variability, there is an 0.7% increase in metabolic cost. Our results demonstrate an association between the metabolic cost of walking and gait step length variability. This suggests that increased gait variability contributes to a portion of the increased cost of walking seen in older adults and neurological populations. Summary StatementFor every 1% increase in step length variability, there is an 0.7% increase in the metabolic cost of walking.

physiology↗

bioRxiv2024

Assessing sprint technique with shoe-mounted inertial sensors

Negative foot speed (i.e., the speed of the backward and downward motion of the foot relative to the body at ground contact) is a strong predictor of sprinting performance. Inertial measurement units (IMUs) are becoming a popular approach for assessing sports performance. The primary aim of this study was to use IMUs to investigate the relationship between negative foot speed and top running speed attained during a sprint on an outdoor track. Seventeen participants performed 80-meter track sprints while wearing a shoe-mounted IMU. Anteroposterior and vertical components of negative foot speed were extracted from the IMU. For the mean peak stride speed of 7.98{+/-}0.78m/s, the adjusted R2 values were 0.27 and 0.42 versus the anteroposterior and vertical components of negative foot speed, respectively. In conclusion, our findings support the common coaching tip of increasing negative foot speed to improve sprint speed. In addition, the results of this study support the use of IMUs for quantifying sprinting technique with actionable metrics.

bioengineering↗

bioRxiv2023

Assessing the validity of the zero-velocity update method for sprinting speeds

The zero-velocity update (ZUPT) method has become a popular approach to estimate foot kinematics from foot worn inertial measurement units (IMUs) during walking and running. However, the accuracy of the ZUPT method for stride parameters at sprinting speeds remains unknown, specifically when using sensors with characteristics well suited for sprinting (i.e., high accelerometer and gyroscope ranges and sampling rates). Seventeen participants performed 70-meter track sprints while wearing a Blue Trident IMeasureU IMU. Two cameras, at 20 and 70 meters from the start, were used to validate the ZUPT method on a stride-by-stride and on a cumulative distance basis. In particular, the validity of the ZUPT method was assessed for: (1) estimating a single stride length attained at the end of a 70m sprint (i.e., stride at 70m); (2) estimating cumulative distance from [~]20 to [~]70 m; and (3) estimating total distance traveled for a 70-meter track sprint. Individual stride length errors at the 70-meter mark were within - 6% to 3%, with a bias of -0.27%. Cumulative distance errors were within -4 to 2%, with biases ranging from -0.85 to -1.22%. The results of this study demonstrate the ZUPT method provides accurate estimates of stride length and cumulative distance traveled for sprinting speeds.

bioengineering↗