A need for speed: Objectively identifying full-body kinematic and neuromuscular features associated with faster sprint velocities

Sprinting is multifactorial and dependent on a variety of kinematic, kinetic, and neuromuscular features. A key objective in sprinting is covering a set amount of distance in the shortest amount of time. To achieve this, sprinters are required to coordinate their entire body to achieve a fast sprint velocity. This suggests that a whole-body kinematic and neuromuscular coordinative strategy exists which is associated with improved sprint performance. The purpose of this study was to leverage inertial measurement units (IMUs) and wireless surface electromyography (sEMG) to find coordinative strategies associated with peak over-ground sprint velocity using machine learning. We recruited 40 healthy university age sprint-based athletes from a variety of athletic backgrounds. IMU and sEMG data were used as inputs into a principal components analysis (PCA) to observe major modes of variation (i.e., PC scores). PC scores were then used as inputs into a stepwise multivariate linear regression model to derive associations of each mode of variation with peak sprint velocity. Both the kinematic (R2 = 0.795) and sEMG data (R2 = 0.586) produced significant multivariate linear regression models. The PCs that were selected as inputs into the multivariate linear regression model were reconstructed using multi-component reconstruction to produce a representation of the whole-body movement pattern and changes in the sEMG waveform associated with faster sprint velocities. The findings of this work suggest that distinct features are associated with faster sprint velocity. These include the timing of the contralateral arm and leg swing, stance leg kinematics, dynamic trunk extension at toe-off, asymmetry between the right and left swing side leg and a phase shift feature of the posterior chain musculature. These results demonstrate the utility of data-driven frameworks in identifying different coordinative features that are associated with a movement outcome. Using our framework, coaches and biomechanists can make decisions based on objective movement information, which can ultimately improve an athlete’s performance.Natural Sciences and Engineering Research Council (NSERC) of Canada & Brock Library Open Access Publishing Fun

An exploratory study evaluating the effectiveness of a data driven approach to identifying coordinative features that are associated with sprint velocity

Sprint performance is multifactorial in nature and is dependent on a variety of coordination and motor control features. During the sequential phases of a sprint, the athlete completes a series of spatiotemporal coordination strategies to achieve the fastest possible velocity. The overall aim of the study was to leverage wearable sensor technology and data- driven tools to objectively assess the kinematic and neuromuscular determinants of optimal sprint velocity from a large dataset of university-aged sprinters. To achieve this, we recruited participants to run three 60 m sprints as fast as possible, while being outfitted with wireless electromyography (EMG) and a full-body inertial measurement unit (IMU) suit to obtain full- body 3D kinematics. Five strides about peak sprint velocity were selected and used for inputs into a principal components analysis (PCA). Significant stepwise multivariable regression models were generated for both kinematic and EMG features identified using PCA, with the kinematic model outperforming the EMG model as the kinematic model displayed a higher R2 value. This suggests that the kinematic dataset used in this study is a better predictor of sprint performance when compared to the EMG dataset, and that both may be viable options in the development of data-driven objective sprint coaching tools

The Use of an Optical Measurement System to Monitor Sports Performance

The purpose of this study was to compare ground contact time between an optical measurement system and a force platform. Participants in this study included six collegiate level athletes who performed drop jumps and sprint strike steps for a total of 15 repetitions each. Ground contact data was simultaneously collected from an optical measurement system and a force platform, at a sampling frequency of 1000 Hz. Data was then analyzed with Pearson’s correlation and paired sample t-tests. The measures from the optical measurement system were found to be significantly higher (p \u3c 0.001) than measures from the force platform in both conditions. Although significantly different, the extremely large relationships (0.979, 0.993) found between the two devices suggest the optical sensor is able to detect similar changes in performance to that of a force platform. Practitioners may continue to utilize optical sensors to monitor performance as it may provide a superior user-friendly alternative to more traditional based monitoring procedures, but must comprehend the inherent limitations due to the design of the optical sensors

HALF A CENTURY IN SPORTS BIOMECHANICS: BRIDGING THE GAP BETWEEN RESEARCHERS AND PRACTITIONERS

The lecture will analyse the development of the relationship between sports biomechanics and coaching over a period of 50 years. The key tenants of the Society's aims and ambitions will be central to the lecture. Foundations of the field of study as introduced by Geoffrey Dyson will be reviewed. Changes in methods of data collection and analysis will be considered alongside developments in computing from mainframe to smartphone. Examples will be drawn from studies throughout the period to illustrate the progress which has been made, with the challenges still to be met being highlighted along the way. The lecture will be a personal analysis of the subject's development through a summary of ideas and experiences which have influenced my thinking on the complex relationship between enhancing understanding of movement and transferring these ideas into practice

The Use Of Inertial Measurement Units To Perform Kinetic Analyses Of Sprint Acceleration And Change Of Direction Tasks

Inertial measurement units (IMUs) are becoming more popular for field-based human movement analysis. However, their ability to track kinetic (i.e., 3-dimensional ground reaction force, F) and kinematic parameters used to evaluate sprint performance has not been assessed. Thus, the purpose of this thesis was three-fold. First was to assess the criterion validity of IMU estimates of the magnitude and direction of F during accelerative running tasks by comparison to a force plate. The second was to determine the concurrent validity of a novel IMU-based sprint velocity estimation algorithm. The third was to determine the concurrent validity of IMU estimates of kinetic determinates of sprint acceleration performance. For the first study, IMU estimates of continuous, step-average, and peak F while subjects performed linear sprint start and change of direction tasks were compared to the same measured by a force plate. For the second and third studies, a recently validated position-time method was used as the reference to which IMU estimates of continuous, average interval, and peak velocity as well as other performance variables (e.g., power, ratio of force, etc.) were compared. The results of these studies suggest the potential use of IMUs to assess sprint performance in the field

Development of a wearable sensor system for dynamically mapping the behavior of an energy storing and returning prosthetic foot

It has been recognized that that the design and prescription of Energy Storing and Returning prosthetic running feet are not well understood and that further information on their performance would be beneficial to increase this understanding. Dynamic analysis of an amputee wearing a prosthetic foot is typically performed using reflective markers and motion-capture systems. High-speed cameras and force plates are used to collect data of a few strides. This requires specialized and expensive equipment in an unrepresentative environment within a large area. Inertial Measurement Units are also capable of being used as wearable sensors but suffer from drift issues. This paper presents the development of a wearable sensing system that records the action of an Energy Storing and Returning prosthetic running foot (sagittal plane displacement and ground contact position) which could have research and/or clinical applications. This is achieved using five standalone pieces of apparatus including foot-mounted pressure sensors and a rotary vario-resistive displacement transducer. It is demonstrated, through the collection of profiles for both foot deflection and ground contact point over the duration of a stride, that the system can be attached to an amputee’s prosthesis and used in a non-laboratory environment. It was found from the system that the prosthetic ground contact point, for the amputee tested, progresses along the effective metatarsal portion of the prosthetic foot towards the distal end of the prosthesis over the duration of the stride. Further investigation of the effective stiffness changes of the foot due to the progression of the contact point is warranted

A general relationship links gait mechanics and running ground reaction forces

The relationship between gait mechanics and running ground reaction forces is widely regarded as complex. This viewpoint has evolved primarily via efforts to explain the rising edge of vertical force– time waveforms observed during slow human running. Existing theoretical models do provide good rising-edge fits, but require more than a dozen input variables to sum the force contributions of four or more vague components of the body’s total mass (mb). Here, we hypothesized that the force contributions of two discrete body mass components are sufficient to account for vertical ground reaction force– time waveform patterns in full (stance foot and shank, m1=0.08mb; remaining mass, m2=0.92mb). We tested this hypothesis directly by acquiring simultaneous limb motion and ground reaction force data across a broad range of running speeds (3.0–11.1 m s−1 ) from 42 subjects who differed in body mass (range: 43–105 kg) and foot-strike mechanics. Predicted waveforms were generated from our two-mass model using body mass and three stride-specific measures: contact time, aerial time and lower limb vertical acceleration during impact. Measured waveforms (N=500) differed in shape and varied by more than twofold in amplitude and duration. Nonetheless, the overall agreement between the 500 measured waveforms and those generated independently by the model approached unity (R2 =0.95 ±0.04, mean±s.d.), with minimal variation across the slow, medium and fast running speeds tested (ΔR2 ≤0.04), and between rear-foot (R2 =0.94±0.04, N=177) versus fore-foot (R2 =0.95±0.04, N=323) strike mechanics. We conclude that the motion of two anatomically discrete components of the body’s mass is sufficient to explain the vertical ground reaction force–time waveform patterns observed during human running

A Numerical Feasibility Study of Kinetic Energy Harvesting from Lower Limb Prosthetics

With the advancement trend of lower limb prosthetics headed towards bionics (active ankle and knee) and smart prosthetics (gait and condition monitoring), there is an increasing integration of various sensors (micro-electromechanical system (MEMS) accelerometers, gyroscopes, magnetometers, strain gauges, pressure sensors, etc.), microcontrollers and wireless systems, and power drives including motors and actuators. All of these active elements require electrical power. However, inclusion of a heavy and bulky battery risks to undo the lightweight advancements achieved by the strong and flexible composite materials in the past decades. Kinetic energy harvesting holds the promise to recharge a small on-board battery in order to sustain the active systems without sacrificing weight and size. However, careful design is required in order not to over-burden the user from parasitic effects. This paper presents a feasibility study using measured gait data and numerical simulation in order to predict the available recoverable power. The numerical simulations suggest that, depending on the axis, up to 10s mW average electrical power is recoverable for a walking gait and up to 100s mW average electrical power is achievable during a running gait. This takes into account parasitic losses and only capturing a fraction of the gait cycle to not adversely burden the user. The predicted recoverable power levels are ample to self-sustain wireless communication and smart sensing functionalities to support smart prosthetics, as well as extend the battery life for active actuators in bionic systems. The results here serve as a theoretical foundation to design and develop towards regenerative smart bionic prosthetics

Biomechanics of Sport Rehabilitation

It is well known that athletes are frequently injured due to the large stress present in most sport performances as well as accidents of different nature. In most cases such lesions involve muscles, ligaments, joint, bones and in several cases also peripheral nerves. In all these cases clinical treatments for restoring the athlete's capabilities are applied: casting, immobilisation, surgical intervention, traditional and specific rehabilitation procedures. A question of great relevance concerns how and when the complete motor recovery of the athlete has been reached, In fact the parameters which are normally used to assess the complete recovery of a normal subject are not sufficient to assess the recovery of a high level athlete, considering the complex mechanical demand which the musculo-skeletal apparatus must satisfy to reach the required performance. In other words, after an accident, the motor recovery accepted for a normal subject can be absolutely inadequate for an athlete. It is therefore necessary to identify new techniques to assess the efficiency of the rehabilitation procedures in the sport domain. Recent technological developments make it possible simultaneous measurements and processing of a set of biomechanical variables related to kinematics, kinetics. and EMG activity during high level performance, so that the deviation from normality can be assessed, where normality is considered the reference pattern of the athlete when expressing a good performance and in the best shape. Such a quantitative evaluation of motor efficiency in .athletes is also important considering that in many cases of accident is difficult to differentiate the role of pure physiological deficiencies from the psychological ones which are often consistent in limiting the possibility of reaching results previously obtained. In order to reach this goal, it IS important to define suitable protocols to monitor the motor apparatus behaviour when performing selected exercises. In this presentation, the methodological approach used to set up the aforementioned protocols will be discussed. Examples of application for the evaluation of basic motor actions (vertical jumping, running) and of specific sport actions (cycling, sprint start, tennis) be illustrated with particular reference to performance assessment and rehabilitative applications