Study of the Mechanism of Perceived Rotational Acceleration of a Bionic Semicircular Canal on the Basis of the "Circular Geometry Hypothesis".

Academia often uses the "circular geometry hypothesis" to explain the sensing principle of the human semicircular canal (SCC) system for angular acceleration, which is widely accepted as an important angular acceleration sensor in the human balance system. On the basis of this hypothesis and the anatomical structure of human SCCs, a series of physical SCC models with different geometries at 4× magnification were prepared via three-dimensional printing and modification of hydrogels. Theoretical models of the SCC perception mechanism were established. Then, impulse angular acceleration, sinusoidal rotation, and sinusoidal linear stimulation were applied to the models, and their responses were visually observed and analyzed in detail. As a result, the circular SCC model had a larger system gain and a smaller phase difference for angular acceleration stimulation but a smaller system gain and a larger phase difference for linear acceleration stimulation. These results verified that the circular semicircular canal was more sensitive to angular acceleration. Our bionic model is hoped to be used for demonstrating the human SCC working process, facilitating researchers in better understanding of the working mechanism of the human SCC, or as a manual model for medical staff to simulate the diagnosis and treatment of human SCC.

Agreement and Sensitivity of the Acceleration-Velocity Profile Derived via Local Positioning System.

Sprint performance is commonly assessed via discrete sprint tests and analyzed through kinematic estimates modeled using a mono-exponential equation, including estimated maximal sprinting speed (MSS), relative acceleration (TAU), maximum acceleration (MAC), and relative propulsive maximal power (PMAX). The acceleration-velocity profile (AVP) provides a simple summary of short sprint performance using two parameters: MSS and MAC, which are useful for simplifying descriptions of sprint performance, comparison between athletes and groups of athletes, and estimating changes in performance over time or due to training intervention. However, discrete testing poses logistical challenges and defines an athlete's AVP exclusively from the performance achieved in an isolated testing environment. Recently, an in situ AVP (velocity-acceleration method) was proposed to estimate kinematic parameters from velocity and acceleration data obtained via global or local positioning systems (GPS/LPS) over multiple training sessions, plausibly improving the time efficiency of sprint monitoring and increasing the sample size that defines the athlete's AVP. However, the validity and sensitivity of estimates derived from the velocity-acceleration method in relation to changes in criterion scores remain elusive. To assess the concurrent validity and sensitivity of kinematic measures from the velocity-acceleration method, 31 elite youth basketball athletes (23 males and 8 females) completed two maximal effort 30 m sprint trials. Performance was simultaneously measured by a laser gun and an LPS (Kinexon), with kinematic parameters estimated using the time-velocity and velocity-acceleration methods. Agreement (%Bias) between laser gun and LPS-derived estimates was within the practically significant magnitude (±5%), while confidence intervals for the percentage mean absolute difference (%MAD) overlapped practical significance for TAU, MAC, and PMAX using the velocity-acceleration method. Only the MSS parameter showed a sensitivity (%MDC95) within practical significance (<5%), with all other parameters showing unsatisfactory sensitivity (>10%) for both the time-velocity and velocity-acceleration methods. Thus, sports practitioners may be confident in the concurrent validity and sensitivity of MSS estimates derived in situ using the velocity-acceleration method, while caution should be applied when using this method to infer an athlete's maximal acceleration capabilities.

Gear Classification in Skating Cross-Country Skiing Using Inertial Sensors and Deep Learning.

The aim of this current work is to identify three different gears of cross-country skiing utilizing embedded inertial measurement units and a suitable deep learning model. The cross-country style studied was the skating style during the uphill, which involved three different gears: symmetric gear pushing with poles on both sides (G3) and two asymmetric gears pushing with poles on the right side (G2R) or to the left side (G2L). To monitor the technique, inertial measurement units (IMUs) were affixed to the skis, recording acceleration and Euler angle data during the uphill tests performed by two experienced skiers using the gears under study. The initiation and termination points of the tests were controlled via Bluetooth by a smartphone using a custom application developed with Android Studio. Data were collected on the smartphone and stored on the SD memory cards included in each IMU. Convolutional neural networks combined with long short-term memory were utilized to classify and extract spatio-temporal features. The performance of the model in cross-user evaluations demonstrated an overall accuracy of 90%, and it achieved an accuracy of 98% in the cross-scene evaluations for individual users. These results indicate a promising performance of the developed system in distinguishing between different ski gears within skating styles, providing a valuable tool to enhance ski training and analysis.

Training and Match-Related Head Acceleration Events in Top Level Domestic Senior Women's and Men's Rugby Union: A Multi-League Instrumented Mouthguard Study.

The aim of this study was to investigate the difference in head acceleration event (HAE) incidence between training and match-play in women's and men's players competing at the highest level of domestic rugby union globally. Players from Women's (Premiership Women's Rugby, Farah Palmer Cup) and Men's (Premiership Rugby, Currie Cup) rugby union competitions wore instrumented mouthguards during matches and training sessions during the 2022/2023 seasons. Peak linear (PLA) and angular (PAA) acceleration were calculated from each HAE and included within generalized linear mixed-effects models. The incidence of HAEs was significantly greater in match-play compared to training for all magnitude thresholds in both forwards and backs, despite players spending approximately 1.75-2.5 times more time in training. For all HAEs (PLA > 5 g and PAA > 400 rad/s2), incidence rate ratios (IRRs) for match versus training ranged from 2.80 (95% CI: 2.38-3.30; men's forwards) to 4.00 (3.31-4.84; women's forwards). At higher magnitude thresholds (PLA > 25 g; PAA > 2000 rad/s2), IRRs ranged from 3.64 (2.02-6.55; PAA > 2000 rad/s2 in men's backs) to 11.70 (6.50-21.08; PAA > 2000 rad/s2 in women's forwards). Similar trends were observed in each competition. Players experienced significantly more HAEs during match-play than training, particularly at higher magnitude thresholds. Where feasible, HAE mitigation strategies may have more scope for HAE reduction if targeted at match-play, particularly where higher magnitude HAEs are the primary concern. However, the number of HAEs associated with different training drills requires exploration to understand if HAEs can be reduced in training, alongside optimizing match performance (e.g., enhancing contact technique).

High-sensitivity acceleration sensor detecting micro-mechanomyogram and deep learning approach for parkinson's disease classification.

High-sensitivity acceleration sensors have been independently developed by our research group to detect vibrations that are > 10 dB smaller than those detected by conventional commercial sensors. This study is the first to measure high-frequency micro-vibrations in muscle fibers, termed micro-mechanomyogram (MMG) in patients with Parkinson's disease (PwPD) using a high-sensitivity acceleration sensor. We specifically measured the extensor pollicis brevis muscle at the base of the thumb in PwPD and healthy controls (HC) and detected not only low-frequency MMG (< 15 Hz) but also micro-MMG (≥ 15 Hz), which was preciously undetectable using commercial acceleration sensors. Analysis revealed remarkable differences in the frequency characteristics of micro-MMG between PwPD and HC. Specifically, during muscle power output, the low-frequency MMG energy was greater in PwPD than in HC, while the micro-MMG energy was smaller in PwPD compared to HC. These results suggest that micro-MMG detected by the high-sensitivity acceleration sensor provides crucial information for distinguishing between PwPD and HC. Moreover, a deep learning model trained on both low-frequency MMG and micro-MMG achieved a high accuracy (92.19%) in classifying PwPD and HC, demonstrating the potential for a diagnostic system for PwPD using micro-MMG.

Methods for Evaluating Tibial Accelerations and Spatiotemporal Gait Parameters during Unsupervised Outdoor Movement.

The purpose of this paper is to introduce a method of measuring spatiotemporal gait patterns, tibial accelerations, and heart rate that are matched with high resolution geographical terrain features using publicly available data. These methods were demonstrated using data from 218 Marines, who completed loaded outdoor ruck hikes between 5-20 km over varying terrain. Each participant was instrumented with two inertial measurement units (IMUs) and a GPS watch. Custom code synchronized accelerometer and positional data without a priori sensor synchronization, calibrated orientation of the IMUs in the tibial reference frame, detected and separated only periods of walking or running, and computed acceleration and spatiotemporal outcomes. GPS positional data were georeferenced with geographic information system (GIS) maps to extract terrain features such as slope, altitude, and surface conditions. This paper reveals the ease at which similar data can be gathered among relatively large groups of people with minimal setup and automated data processing. The methods described here can be adapted to other populations and similar ground-based activities such as skiing or trail running.

Predicting Athlete Workload in Women's Rugby Sevens Using GNSS Sensor Data, Contact Count and Mass.

The use of session rating of perceived exertion (sRPE) as a measure of workload is a popular athlete load monitoring tool. However, the nature of sRPE means the contribution of salient, sport-specific factors to athlete load in field sports is challenging to isolate and quantify. In rugby sevens, drivers of load include high-speed running and physical contact. In soccer and men's rugby, union acceleration/deceleration also influences load. These metrics are evaluated using data from global navigation satellite system (GNSS) sensors worn by athletes. Research suggests that sensor data methods for identifying load in men's rugby do not accurately quantify female athlete loads. This investigation examined how mass, contact, and accelerations and decelerations at different speeds contribute to load in women's rugby sevens. The study evaluated 99 international matches, using data from 19 full-time athletes. GNSS measures, RPE, athlete mass, and contact count were evaluated using a linear mixed-model regression. The model demonstrated significant effects for low decelerations at low and high speeds, mass, distance, and contact count explaining 48.7% of the global variance of sRPE. The use of acceleration/deceleration and speed from GNSS sensors alongside mass, as well as contact count, presents a novel approach to quantifying load.

Quantifying Hand Motion Complexity in Simulated Sailing Using Inertial Sensors.

The control of hand movement during sailing is important for performance. To quantify the amount of regularity and the unpredictability of hand fluctuations during the task, the mathematical algorithm Approximate Entropy (ApEn) of the hand acceleration can be used. Approximate Entropy is a mathematical algorithm that depends on the combination of two input parameters including (1) the length of the sequences to be compared (m), and (2) the tolerance threshold for accepting similar patterns between two segments (r). The aim of this study is to identify the proper combinations of 'm' and 'r' parameter values for ApEn measurement in the hand movement acceleration data during sailing. Inertial Measurement Units (IMUs) recorded acceleration data for both the mainsail (non-dominant) and tiller (dominant) hands across the X-, Y-, and Z-axes, as well as vector magnitude. ApEn values were computed for 24 parameter combinations, with 'm' ranging from 2 to 5 and 'r' from 0.10 to 0.50. The analysis revealed significant differences in acceleration ApEn regularity between the two hands, particularly along the Z-axis, where the mainsail hand exhibited higher entropy values (p = 0.000673), indicating greater acceleration complexity and unpredictability. In contrast, the tiller hand displayed more stable and predictable acceleration patterns, with lower ApEn values. ANOVA results confirmed that parameter 'm' had a significant effect on acceleration complexity for both hands, highlighting differing motor control demands between the mainsail and tiller hands. These findings demonstrate the utility of IMU sensors and ApEn in detecting nuanced variations in acceleration dynamics during sailing tasks. This research contributes to the understanding of hand-specific acceleration patterns in sailing and provides a foundation for further studies on adaptive sailing techniques and motor control strategies for both novice and expert sailors.

How Shell Add-On Products Influence Varsity Football Helmet Performance?

PURPOSE: The study purpose was to investigate the laboratory-based performance of three commercially available shell add-on products under varsity-level impact conditions. METHODS: Pendulum impact tests were conducted at multiple locations (front, front boss, rear, side) and speeds (3.1, 4.9, 6.4 m/s) using two helmet models. Tests were performed with a single add-on configuration for baseline comparisons and a double add-on configuration to simulate collisions with both players wearing shell add-ons. A linear mixed-effect model was used to evaluate peak linear acceleration (PLA), peak rotational acceleration (PRA), and concussion risk, which was calculated from a bivariate injury risk function, based on shell add-on and test configuration. RESULTS: All shell add-ons decreased peak head kinematics and injury risk compared to controls, with the Guardian NXT producing the largest reductions (PLA: 7.9%, PRA: 14.1%, Risk: 34.1%) compared to the SAFR Helmet Cover (PLA: 4.5%, PRA: 9.3%, Risk: 24.7%) and Guardian XT (PLA: 3.2%, PRA: 5.0%, Risk: 15.5%). The same trend was observed in the double add-on test configuration. However, the Guardian NXT (PLA: 17.1%; PRA: 11.5%; Risk: 62.8%) and SAFR Helmet Cover (PLA: 12.2%; PRA: 9.1%; Risk: 52.2%) produced larger reductions in peak head kinematics and injury risk than the Guardian XT (PLA: 5.7%, PRA: 2.2%, Risk: 21.8%). CONCLUSION: In laboratory-based assessments that simulated varsity-level impact conditions, the Guardian NXT was associated with larger reductions in PLA, PRA, and injury risk compared to the SAFR Helmet Cover and Guardian XT. Although shell add-ons can enhance head protection, helmet model selection should be prioritized.

How Do Technical and Tactical Demands of Football Matches Affect the Physical Performance of Elite Football Referees? Exploring the Role of Experience.

ABSTRACT: Martinez-Torremocha, G, Alonso-Callejo, A, Garcia-Unanue, J, Gallardo, L, Sanchez-Sanchez, J, and Felipe, JL. How do technical and tactical demands of football matches impact the physical performance of elite football referees? Exploring the role of experience. J Strength Cond Res 38(11): e664-e669, 2024-This study aimed to analyze whether the physical demands on elite football referees during matches are influenced by both the physical intensity of the game and the technical-tactical context, to assess the impact of elite experience on the physical demands of referees, and to compare the physical performance of the referees with the performance of the players divided by positions in each match analyzed. Physical demands were recorded on 20 Spanish male football referees during the 2020/21, 2021/22, and 2022/23 seasons over a total of 73 official matches, using Global Positioning Systems for physical demands (total distance [TD], high-speed running [HSR], sprint, and high-intensity acceleration [HI ACC] and deceleration) and WyScout for technical-tactical actions (ball circulation, possession, shot, passes, total turnovers, quick turnovers, and long passes). Referees showed lower values for all variables except in TD (p < 0.05). No significant differences (p > 0.05) were found in referees' physical demands based on experience. Low-experience referees correlated HSR and sprint distances with high-intensity decelerations distances in matches. Medium-experience referees linked HSR, sprinting, and HI ACC distances with greater sprint distances in matches. High-experience referees correlated HSR distance with HSR, sprint, and HI ACC distances match demands. Low-experience referees positively correlated HSR and sprint distances with ball circulation, passes, quick turnovers, and forward passes. In conclusion, referees' experience influenced the adaptation of their physical demands to the technical-tactical and physical factors of competitive matches. This information will help professionals working with referees to develop training programs that better prepare referees for specific challenges.

Identifying Gravity-Related Artifacts on Ballistocardiography Signals by Comparing Weightlessness and Normal Gravity Recordings (ARTIFACTS): Protocol for an Observational Study.

BACKGROUND: Modern ballistocardiography (BCG) and seismocardiography (SCG) use acceleration sensors to measure oscillating recoil movements of the body caused by the heartbeat and blood flow, which are transmitted to the body surface. Acceleration artifacts occur through intrinsic sensor roll, pitch, and yaw movements, assessed by the angular velocities of the respective sensor, during measurements that bias the signal interpretation. OBJECTIVE: This observational study aims to generate hypotheses on the detection and elimination of acceleration artifacts due to the intrinsic rotation of accelerometers and their differentiation from heart-induced sensor accelerations. METHODS: Multimodal data from 4 healthy participants (3 male and 1 female) using BCG-SCG and an electrocardiogram will be collected and serve as a basis for signal characterization, model modulation, and location vector derivation under parabolic flight conditions from µg to 1.8g. The data will be obtained during a parabolic flight campaign (3 times 30 parabolas) between September 24 and July 25 (depending on the flight schedule). To detect the described acceleration artifacts, accelerometers and gyroscopes (6-degree-of-freedom sensors) will be used for measuring acceleration and angular velocities attributed to intrinsic sensor rotation. Changes in acceleration and angular velocities will be explored by conducting descriptive data analysis of resting participants sitting upright in varying gravitational states. RESULTS: A multimodal data set will serve as a basis for research into a noninvasive and gentle method of BCG-SCG with the aid of low-noise and synchronous 3D gyroscopes and 3D acceleration sensors. Hypotheses will be generated related to detecting and eliminating acceleration artifacts due to the intrinsic rotation of accelerometers and gyroscopes (6-degree-of-freedom sensors) and their differentiation from heart-induced sensor accelerations. Data will be collected entirely and exclusively during the parabolic flights, taking place between September 2024 and July 2025. Thus, as of June 2024, no data have been collected yet. The data will be analyzed until December 2025. The results are expected to be published by June 2026. CONCLUSIONS: The study will contribute to understanding artificial acceleration bias to signal readings. It will be a first approach for a detection and elimination method. TRIAL REGISTRATION: Deutsches Register Klinische Studien DRKS00034402; https://drks.de/search/en/trial/DRKS00034402. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/63306.

Correlation between Muscular Activity and Vehicle Motion during Double Lane Change Driving.

The aim of this study was to compare the correlation between electromyography (EMG) activity and vehicle motion during double lane change driving. This study measured five vehicle motions: the steering wheel angle, steering wheel torque, lateral acceleration, roll angle, and yaw velocity. The EMG activity for 19 muscles and vehicle motions was applied for envelope detection. There was a significantly high positive correlation between muscles (mean correlation coefficient) for sternocleidomastoid (0.62) and biceps brachii (0.71) and vehicle motions for steering wheel angle, steering wheel torque, lateral acceleration, and yaw velocity, but a negative correlation between the muscles for middle deltoid (-0.75) and triceps brachii long head (-0.78) and these vehicle motions. The ANOVA test was used to analyze statistically significant differences in the main and interaction effects of muscle and vehicle speed. The mean absolute correlation coefficient exhibited an increasing trend with the increasing vehicle speed for the muscles (increasing rate%): upper trapezius (30.5%), pectoralis major sternal (38.7%), serratus anterior (13.3%), and biceps brachii (11.0%). The mean absolute correlation coefficient showed a decreasing trend with increasing vehicle speed for the masseter (-9.6%), sternocleidomastoid (-12.9%), middle deltoid (-5.5%), posterior deltoid (-20.0%), pectoralis major clavicular (-13.4%), and triceps brachii long head (-6.3%). The sternocleidomastoid muscle may decrease with increasing vehicle speed as the neck rotation decreases. As shoulder stabilizers, the upper trapezius, pectoralis major sternal, and serratus anterior muscles are considered to play a primary role in maintaining body balance. This study suggests that the primary muscles reflecting vehicle motions include the sternocleidomastoid, deltoid, upper trapezius, pectoralis major sternal, serratus anterior, biceps, and triceps muscles under real driving conditions.

Differences in Trunk Acceleration-Derived Gait Indexes in Stroke Subjects with and without Stroke-Induced Immunosuppression.

Background: Stroke-induced immunosuppression (SII) represents a negative rehabilitative prognostic factor associated with poor motor performance at discharge from a neurorehabilitation unit (NRB). This study aims to evaluate the association between SII and gait impairment at NRB admission. Methods: Forty-six stroke patients (65.4 ± 15.8 years, 28 males) and 42 healthy subjects (HS), matched for age, sex, and gait speed, underwent gait analysis using an inertial measurement unit at the lumbar level. Stroke patients were divided into two groups: (i) the SII group was defined using a neutrophil-to-lymphocyte ratio ≥ 5, and (ii) the immunocompetent (IC) group. Harmonic ratio (HR) and short-term largest Lyapunov's exponent (sLLE) were calculated as measures of gait symmetry and stability, respectively. Results: Out of 46 patients, 14 (30.4%) had SII. HR was higher in HS when compared to SII and IC groups (p < 0.01). HR values were lower in SII when compared to IC subjects (p < 0.01). sLLE was lower in HS when compared to SII and IC groups in the vertical and medio-lateral planes (p ≤ 0.01 for all comparisons). sLLE in the medio-lateral plane was higher in SII when compared to IC subjects (p = 0.04). Conclusions: SII individuals are characterized by a pronounced asymmetric gait and a more impaired dynamic gait stability. Our findings underline the importance of devising tailored rehabilitation programs in patients with SII. Further studies are needed to assess the long-term outcomes and the role of other clinical features on gait pattern.

The Determination of On-Water Rowing Stroke Kinematics Using an Undecimated Wavelet Transform of a Rowing Hull-Mounted Accelerometer Signal.

Boat acceleration profiles can provide valuable information for coaches and practitioners to make meaningful technical interventions and monitor the determinants of success in rowing. Previous studies have used simple feature detection methods to identify key phases within individual strokes, such as drive onset, drive time, drive offset and stroke time. However, based on skill level, technique or boat class, the hull acceleration profile can differ, making robust feature detection more challenging. The current study's purpose is to employ the undecimated wavelet transform (UWT) technique to detect individual features in the stroke acceleration profile from a single rowing hull-mounted accelerometer. In this investigation, the temporal and kinematic values obtained using the AdMosTM sensor in conjunction with the UWT processing approach were strongly correlated with the comparative measures of the Peach™ instrumented oarlock system. The measures for stroke time displayed very strong agreeability between the systems for all boat classes, with ICC values of 0.993, 0.963 and 0.954 for the W8+, W4- and W1x boats, respectively. Similarly, the drive time was also very consistent, with strong to very strong agreeability, producing ICC values of 0.937, 0.901 and 0.881 for the W8+, W4- and W1x boat classes. Further, a Bland-Altman analysis displayed little to no bias between the AdMosTM-derived and Peach™ measures, indicating that there were no systematic discrepancies between signals. This single-sensor solution could form the basis for a simple, cost-effective and accessible alternative to multi-sensor instrumented systems for the determination of sub-stroke kinematic phases.

Head Impacts in Collegiate Rodeo Athletes: An Observational Study.

INTRODUCTION: Brain health has been a growing concern across a wide range of contact sports in the last three decades. While most of the early brain health research was focused on identifying and preventing concussions, newer research has found that an accumulation of repetitive head impacts (RHI) are more predictive of long-term brain health than the number of concussions sustained. Consequently, being able to assess RHI in sports despite the lack of outward symptoms has become paramount in promoting the long-term health of athletes. The sport of rodeo has long been regarded as one of the most dangerous contact sports. While some epidemiological research has been done on injury rates in rodeo that has largely backed up its dangerous reputation, no research has been done into RHI in rodeo athletes. METHODS: Head acceleration events (HAE) were measured in collegiate athletes competing in the "Roughstock" events of Bareback Riding, Saddle Bronc Riding and Bull Riding. HAE were recorded using impact monitoring mouthgaurds (iMG) and subsequently confirmed using video verification and submitted to statistical analysis. RESULTS: Rodeo has a high rate of HAE across all the Roughstock events. The Bull Riding experiences the highest magnitude HAE based on both linear and rotational acceleration. These events are primarily the result of the head impacting either the ground or the animal during the dismount phase of the ride. Bareback riding experiences the highest quantity of lower magnitude HAE which mainly result from whiplash-like movement of the head during the ride. CONCLUSIONS: Rodeo athletes experience a high volume of HAE that often reach concerning magnitude. A surprising amount of the HAE are the result not of impacts, but of the whiplash-like movement that is experienced during the rides.

Classification of sex-dependent specific behaviours by tri-axial acceleration in the tegu lizard Salvator merianae.

Validated patterns of behaviour detected by tri-axial acceleration in the laboratory can be used for remote measurements of free-living animals. The tegu lizard naturally occupies diverse biomes in South America and presents ecological threats in regions where it was artificially introduced. We aimed to validate the use of tri-axial acceleration to distinguish among behaviours of male and female tegus in captivity by comparing observed behaviours to recorded acceleration data. Adult animals were externally fitted with an accelerometer fixed between their scapulae to quantify anteroposterior, lateral, and dorsoventral acceleration. Video recordings of cameras positioned on the walls of the animal-holding arena documented behaviours. Behaviour patterns, such as resting, walking, and eating, were identified for both sexes, and nest building in females and courtship and copulation in males. Random Forest algorithm was used to validate the behaviour patterns from accelerometry data based on two models, random split (70 % training-30 % validation; RS) and leave-one-out (divided by individual; LOO). Although LOO showed lower accuracies than RS for all the acceleration data, nest building in females and copulation in males had high accuracies in both models. In contrast, the lowest accuracies for walking and eating indicates they may involve more inconsistent movement patterns. Comparing the results from RS and LOO, female behaviours may be more identifiable in the field using triaxial accelerometry than males. The identification of behaviours by accelerometry, especially related to reproduction, without the necessity for direct observation of the tegus would be helpful for conservation purposes, for both natural and invasive populations.

The Effect of a Newly Developed Hand Rim on Mobility Performance and Propulsion Technique in Wheelchair Tennis Players.

PURPOSE: To investigate the effect of a newly developed hand rim in wheelchair tennis players from a lab and field perspective. METHODS: Nine wheelchair tennis players performed a set of field and lab tests with the new rim (NR) and regular rim on the racket side. Each player had a 60- to 120-minute regular training session with the NR. Three wheelchair tennis field tests (20-m sprint, Illinois, spider) were completed on a hard court using inertial measurement units. The inertial measurement units enabled analysis of linear/rotational velocity and acceleration. In the lab, two 4-minute submaximal tests (at 1.5 and 2 m/s, 0.2 W/kg), followed directly by a 5-second sprint, on a wheelchair ergometer were completed. Force and velocity were measured continuously throughout all tests. Mixed linear models investigated the effect between the 2 hand rims. RESULTS: During the spider test, mean rotational velocity to the racket side (-2%, P = .005) was lower in the NR, and end times were similar between hand-rim conditions. No differences were observed in the 20-m sprint and Illinois field tests. In the lab, contact angle (+6%, P = .04), cycle time (+12%, P = .007), and work per push (+13%, P = .005) were higher in the NR during submaximal propulsion. Work per push (+13%, P = .007), peak velocity (+3%, P < .001), and distance covered (+4%, P = .02) were higher with the NR during the 5-second sprint test. CONCLUSIONS: The NR seems slightly favorable compared with the regular rim during performance testing on a wheelchair ergometer in wheelchair tennis players. A longer practice time might show more insights between the hand-rim types.

Small energy benefits of in-wake flying in long-duration migratory flights.

During long-distance migrations, some bird species make use of in-wake flying, which should allow them to profit from the upwash produced by another bird. While indirect evidence supports energy saving as the primary benefit of in-wake flying, measurements are still missing. We equipped migrating northern bald ibises (Geronticus eremita) with high-precision global navigation satellite system data loggers to track their position in the flock. We estimated birds' energy expenditure through different proxies, namely dynamic body acceleration (DBA), heart rate and effective wingbeat frequency. During active flapping flight, DBA estimates dropped off when in-wake compared with when not-in-wake. In addition, effective wingbeat frequency decreased, suggesting an increased use of intermittent gliding flight during in-wake periods. Heart rate varied greatly among individuals, with a clear decrease during gliding-corroborating its energy-saving function. Furthermore, we found consistent proof for decreased heart rate during in-wake flying, by up to 4.2%. Hence, we have shown that flying in the wake of another individual reduces birds' DBA, heart rate and effective wingbeat frequency, which could reflect reduced energy requirement.

Pelvis and thoracolumbar spine response in simulated under-body blast impacts and protective seat cushion design.

Purpose: The aim of this study is to investigate the dynamic and biomechanical response of the pelvis and thoracolumbar spine in simulated under-body blast (UBB) impacts and design of protective seat cushion for thoracolumbar spine injuries. Methods: A whole-body FE (finite element) human body model in the anthropometry of Chinese 50th% adult male (named as C-HBM) was validated against existing PHMS (Postmortem Human Subjects) test data and employed to understand the dynamic and biomechanical response of the pelvis and thoracolumbar spine from FE simulations of UBB impacts. Then, the protective capability of different seat cushion designs for UBB pelvis and thoracolumbar injury risk was compared based on the predictions of the C-HBM. Results: The predicted spinal accelerations from the C-HUM are almost within the PHMS corridors. UBB impact combined with the effects from physiological curve of the human thoracolumbar spine and torso inertia leads to thoracolumbar spine anterior bending and axial compression, which results in stress concentration in the segments of T4-T8, T12-L1 and L4-L5. Foam seat cushion can effectively reduce the risk of thoracolumbar spine injury of armored vehicle occupants in UBB impacts, and the DO3 foam has better protective performance than ordinary foam, the 60 mm thick DO3 foam could reduce pelvic acceleration peak and DRIz value by 52.8% and 17.2%, respectively. Conclusions: UBB spinal injury risk is sensitive to the input load level, but reducing the pelvic acceleration peak only is not enough for protection of spinal UBB injury risk, control of torso inertia effect would be much helpful.

Enhancing Sports Injury Risk Assessment in Soccer Through Machine Learning and Training Load Analysis.

Sports injuries pose significant challenges in athlete welfare and team dynamics, particularly in high-intensity sports like soccer. This study used machine learning algorithms to assess non-contact injury risk in professional male soccer players from physiological and mechanical load variables. Twenty-five professional male soccer players with a first-time, non-contact muscle injury were included in this study. Recordings of external load (speed, distance, and acceleration/deceleration data) and internal load (heart rate) were obtained during all training sessions and official matches over a 4-year period. Machine learning model training and evaluation features were calculated for each of nine different metrics for a 28-day period prior to the injury and an equal-length baseline epoch. The acute surge in the values of each workload metric was quantified by the deviation of maximum values from the average, while the variations of cumulative workload over the last four weeks preceding injury were also calculated. Seven features were selected by the model as prominent estimators of injury incidence. Three of the features concerned acute load deviations (number of sprints, training load score-incorporating heart rate and muscle load- and time of heart rate at the 90-100% of maximum). The four cumulative load features were (total distance, high speed and sprint running distance and training load score). The accuracy of the muscle injury risk assessment model was 0.78, with a sensitivity of 0.73 and specificity of 0.85. Our model achieved high performance in injury risk detection using a limited number of training load variables. The inclusion, for the first time, of heart rate related variables in an injury risk assessment model highlights the importance of physiological overload as a contributor to muscle injuries in soccer. By identifying the important parameters, coaches may prevent muscle injuries by controlling surges of training load during training and competition.