Dataset Information

Head and Tibial Acceleration as a Function of Stride Frequency and Visual Feedback during Running.

ABSTRACT: Individuals regulate the transmission of shock to the head during running at different stride frequencies although the consequences of this on head-gaze stability remain unclear. The purpose of this study was to examine if providing individuals with visual feedback of their head-gaze orientation impacts tibial and head accelerations, shock attenuation and head-gaze motion during preferred speed running at different stride frequencies. Fifteen strides from twelve recreational runners running on a treadmill at their preferred speed were collected during five stride frequencies (preferred, ±10% and ±20% of preferred) in two visual task conditions (with and without real-time visual feedback of head-gaze orientation). The main outcome measures were tibial and head peak accelerations assessed in the time and frequency domains, shock attenuation from tibia to head, and the magnitude and velocity of head-gaze motion. Decreasing stride frequency resulted in greater vertical accelerations of the tibia (p<0.01) during early stance and at the head (p<0.01) during early and late stance; however, for the impact portion the increase in head acceleration was only observed for the slowest stride frequency condition. Visual feedback resulted in reduced head acceleration magnitude (p<0.01) and integrated power spectral density in the frequency domain (p<0.01) in late stance, as well as overall of head-gaze motion (p<0.01). When running at preferred speed individuals were able to stabilize head acceleration within a wide range of stride frequencies; only at a stride frequency 20% below preferred did head acceleration increase. Furthermore, impact accelerations of the head and tibia appear to be solely a function of stride frequency as no differences were observed between feedback conditions. Increased visual task demands through head gaze feedback resulted in reductions in head accelerations in the active portion of stance and increased head-gaze stability.

SUBMITTER: Busa MA

PROVIDER: S-EPMC4896625 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Head and Tibial Acceleration as a Function of Stride Frequency and Visual Feedback during Running.

Busa Michael A MA Lim Jongil J van Emmerik Richard E A RE Hamill Joseph J

PloS one 20160607 6

Individuals regulate the transmission of shock to the head during running at different stride frequencies although the consequences of this on head-gaze stability remain unclear. The purpose of this study was to examine if providing individuals with visual feedback of their head-gaze orientation impacts tibial and head accelerations, shock attenuation and head-gaze motion during preferred speed running at different stride frequencies. Fifteen strides from twelve recreational runners running on a ...[more]

PMID: 27271850

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Project description:BackgroundStress fractures are injuries caused by repetitive loading during activities such as running. The application of advanced analytical methods such as machine learning to data from multiple wearable sensors has allowed for predictions of biomechanical variables associated with running-related injuries like stress fractures. However, it is unclear if data from a single wearable sensor can accurately estimate variables that characterize external loading during running such as peak vertical ground reaction force (vGRF), vertical impulse, and ground contact time. Predicting these biomechanical variables with a single wearable sensor could allow researchers, clinicians, and coaches to longitudinally monitor biomechanical running-related injury risk factors without expensive force-measuring equipment.PurposeWe quantified the accuracy of applying quantile regression forest (QRF) and linear regression (LR) models to sacral-mounted accelerometer data to predict peak vGRF, vertical impulse, and ground contact time across a range of running speeds.MethodsThirty-seven collegiate cross country runners (24 females, 13 males) ran on a force-measuring treadmill at 3.8-5.4 m/s while wearing an accelerometer clipped posteriorly to the waistband of their running shorts. We cross-validated QRF and LR models by training them on acceleration data, running speed, step frequency, and body mass as predictor variables. Trained models were then used to predict peak vGRF, vertical impulse, and contact time. We compared predicted values to those calculated from a force-measuring treadmill on a subset of data (n = 9) withheld during model training. We quantified prediction accuracy by calculating the root mean square error (RMSE) and mean absolute percentage error (MAPE).ResultsThe QRF model predicted peak vGRF with a RMSE of 0.150 body weights (BW) and MAPE of 4.27 ± 2.85%, predicted vertical impulse with a RMSE of 0.004 BW*s and MAPE of 0.80 ± 0.91%, and predicted contact time with a RMSE of 0.011 s and MAPE of 4.68 ± 3.00%. The LR model predicted peak vGRF with a RMSE of 0.139 BW and MAPE of 4.04 ± 2.57%, predicted vertical impulse with a RMSE of 0.002 BW*s and MAPE of 0.50 ± 0.42%, and predicted contact time with a RMSE of 0.008 s and MAPE of 3.50 ± 2.27%. There were no statistically significant differences between QRF and LR model prediction MAPE for peak vGRF (p = 0.549) or vertical impulse (p = 0.073), but the LR model's MAPE for contact time was significantly lower than the QRF model's MAPE (p = 0.0497).ConclusionsOur findings indicate that the QRF and LR models can accurately predict peak vGRF, vertical impulse, and contact time (MAPE < 5%) from a single sacral-mounted accelerometer across a range of running speeds. These findings may be beneficial for researchers, clinicians, or coaches seeking to monitor running-related injury risk factors without force-measuring equipment.

Project description:During flight maneuvers, insects exhibit compensatory head movements which are essential for stabilizing the visual field on their retina, reducing motion blur, and supporting visual self-motion estimation. In Diptera, such head movements are mediated via visual feedback from their compound eyes that detect retinal slip, as well as rapid mechanosensory feedback from their halteres - the modified hindwings that sense the angular rates of body rotations. Because non-Dipteran insects lack halteres, it is not known if mechanosensory feedback about body rotations plays any role in their head stabilization response. Diverse non-Dipteran insects are known to rely on visual and antennal mechanosensory feedback for flight control. In hawkmoths, for instance, reduction of antennal mechanosensory feedback severely compromises their ability to control flight. Similarly, when the head movements of freely flying moths are restricted, their flight ability is also severely impaired. The role of compensatory head movements as well as multimodal feedback in insect flight raises an interesting question: in insects that lack halteres, what sensory cues are required for head stabilization? Here, we show that in the nocturnal hawkmoth Daphnis nerii, compensatory head movements are mediated by combined visual and antennal mechanosensory feedback. We subjected tethered moths to open-loop body roll rotations under different lighting conditions, and measured their ability to maintain head angle in the presence or absence of antennal mechanosensory feedback. Our study suggests that head stabilization in moths is mediated primarily by visual feedback during roll movements at lower frequencies, whereas antennal mechanosensory feedback is required when roll occurs at higher frequency. These findings are consistent with the hypothesis that control of head angle results from a multimodal feedback loop that integrates both visual and antennal mechanosensory feedback, albeit at different latencies. At adequate light levels, visual feedback is sufficient for head stabilization primarily at low frequencies of body roll. However, under dark conditions, antennal mechanosensory feedback is essential for the control of head movements at high frequencies of body roll.

Dataset Information

Head and Tibial Acceleration as a Function of Stride Frequency and Visual Feedback during Running.

Publications

Head and Tibial Acceleration as a Function of Stride Frequency and Visual Feedback during Running.

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