Kinematics differences between the flat, kick, and slice serves measured using a markerless motion capture method.

Tennis injuries have been associated with serving mechanics, but quantitative kinematic measurements in realistic environments are limited by current motion capture technologies. This study tested for kinematic differences at the lower back, shoulder, elbow, wrist, and racquet between the flat, kick, and slice serves using a markerless motion capture (MMC) system. Seven male NCAA Division 1 players were tested on an outdoor court in daylight conditions. Peak racquet and joint center speeds occurred sequentially and increased from proximal (back) to distal (racquet). Racquet speeds at ball impact were not significantly different between serve types. However, there were significant differences in the direction of the racquet velocity vector between serves: the kick serve had the largest lateral and smallest forward racquet velocity components, while the flat serve had the smallest vertical component (p < 0.01). The slice serve had lateral velocity, like the kick, and large forward velocity, like the flat. Additionally, the racquet in the kick serve was positioned 8.7 cm more posterior and 21.1 cm more medial than the shoulder compared with the flat, which could suggest an increased risk of shoulder and back injury associated with the kick serve. This study demonstrated the potential for MMC for testing sports performance under natural conditions.

Markerless analysis of front crawl swimming.

Research on motion analysis of swimmers is commonly based on video recordings of the subject's motion, which are analyzed by manual digitization of feature points by an operator. This procedure has two main drawbacks: it is time-consuming, and it is affected by low repeatability. Therefore, the application of video-based, automatic approaches to motion analysis was investigated. A video-based, markerless system for the analysis of arm movements during front crawl swimming was developed. The method proposed by Corazza et al. (2010) was modified in order to be used into water environment. Three dimensional coordinates of shoulder, elbow and wrist joints centers of 5 sprint swimmers performing front crawl swimming were determined. Wrist joint velocity was also calculated. Accuracy and reliability of the proposed technique were evaluated by means of comparison with traditional manual digitization (SIMI Reality Motion Systems GmbH). Root mean square distance (RMSD) values between trajectories estimated with the two techniques were determined. Results show good accuracy for wrist joint (RMSD<56mm), and reliability, evaluated on one subject, comparable to the inter-operator variability associated with the manual digitization procedure. The proposed technique is therefore very promising for quantitative, wide-scale studies on swimmers' motion.

An automated image-based method of 3D subject-specific body segment parameter estimation for kinetic analyses of rapid movements.

Accurate subject-specific body segment parameters (BSPs) are necessary to perform kinetic analyses of human movements with large accelerations, or no external contact forces or moments. A new automated topographical image-based method of estimating segment mass, center of mass (CM) position, and moments of inertia is presented. Body geometry and volume were measured using a laser scanner, then an automated pose and shape registration algorithm segmented the scanned body surface, and identified joint center (JC) positions. Assuming the constant segment densities of Dempster, thigh and shank masses, CM locations, and moments of inertia were estimated for four male subjects with body mass indexes (BMIs) of 19.7-38.2. The subject-specific BSP were compared with those determined using Dempster and Clauser regression equations. The influence of BSP and BMI differences on knee and hip net forces and moments during a running swing phase were quantified for the subjects with the smallest and largest BMIs. Subject-specific BSP for 15 body segments were quickly calculated using the image-based method, and total subject masses were overestimated by 1.7-2.9%.When compared with the Dempster and Clauser methods, image-based and regression estimated thigh BSP varied more than the shank parameters. Thigh masses and hip JC to thigh CM distances were consistently larger, and each transverse moment of inertia was smaller using the image-based method. Because the shank had larger linear and angular accelerations than the thigh during the running swing phase, shank BSP differences had a larger effect on calculated intersegmental forces and moments at the knee joint than thigh BSP differences did at the hip. It was the net knee kinetic differences caused by the shank BSP differences that were the largest contributors to the hip variations. Finally, BSP differences produced larger kinetic differences for the subject with larger segment masses, suggesting that parameter accuracy is more important for studies focused on overweight populations. The new image-based BSP estimation method described in this paper addressed the limitations of currently used geometric and regression methods by using exact limb geometry to determine subject-specific parameters. BSP differences have the largest effect on kinetic analyses of motions with large limb accelerations, for joints farther along the kinematic chain from the known forces and moments, and for subjects with larger limb masses or BMIs.

Shoe-surface friction influences movement strategies during a sidestep cutting task: implications for anterior cruciate ligament injury risk.

BACKGROUND: Increasing the coefficient of friction of the shoe-surface interaction has been shown to lead to increased incidence of anterior cruciate ligament (ACL) injuries, but the causes for this increase are unknown. Previous studies indicate that specific biomechanical measures during landing are associated with an increased risk for ACL injury. HYPOTHESIS: At foot contact during a sidestep cutting task, subjects use different movement strategies for shoe-surface conditions with a high coefficient of friction (COF) relative to a low friction condition. Specifically, the study tested for significant differences in knee kinematics, external knee moments, and the position of the center of mass for different COFs. STUDY DESIGN: Controlled laboratory study. METHODS: Twenty-two healthy subjects (11 male) were evaluated performing a 30 degrees sidestep cutting task on a low friction surface (0.38) and a high friction surface (0.87) at a constant speed. An 8-camera markerless motion capture system combined with 2 force plates was used to measure full-body kinematics, kinetics, and center of mass. RESULTS: At foot contact, subjects had a lower knee flexion angle (P = .01), lower external knee flexion moment (P < .001), higher external knee valgus moment (P < .001), and greater medial distance of the center of mass from the support limb (P < .001) on the high friction surface relative to the low friction surface. CONCLUSION: The high COF shoe-surface condition was associated with biomechanical conditions that can increase the risk of ACL injury. The higher incidence of ACL injury observed on high friction surfaces could be a result of these biomechanical changes. The differences in the biomechanical variables were the result of an anticipated stimulus due to different surface friction, with other conditions remaining constant. CLINICAL RELEVANCE: The risk analysis of ACL injury should consider the biomechanical movement changes that occur for a shoe-surface condition with high friction.

Automatic generation of a subject-specific model for accurate markerless motion capture and biomechanical applications.

A novel approach for the automatic generation of a subject-specific model consisting of morphological and joint location information is described. The aim is to address the need for efficient and accurate model generation for markerless motion capture (MMC) and biomechanical studies. The algorithm applied and expanded on previous work on human shapes space by embedding location information for ten joint centers in a subject-specific free-form surface. The optimal locations of joint centers in the 3-D mesh were learned through linear regression over a set of nine subjects whose joint centers were known. The model was shown to be sufficiently accurate for both kinematic (joint centers) and morphological (shape of the body) information to allow accurate tracking with MMC systems. The automatic model generation algorithm was applied to 3-D meshes of different quality and resolution such as laser scans and visual hulls. The complete method was tested using nine subjects of different gender, body mass index (BMI), age, and ethnicity. Experimental training error and cross-validation errors were 19 and 25 mm, respectively, on average over the joints of the ten subjects analyzed in the study.

Characterizing multisegment foot kinematics during gait in diabetic foot patients.

BACKGROUND: The prevalence of diabetes mellitus has reached epidemic proportions, this condition may result in multiple and chronic invalidating long term complications. Among these, the diabetic foot, is determined by the simultaneous presence of both peripheral neuropathy and vasculopathy that alter the biomechanics of the foot with the formation of callosity and ulcerations. To diagnose and treat the diabetic foot is crucial to understand the foot complex kinematics. Most of gait analysis protocols represent the entire foot as a rigid body connected to the shank. Nevertheless the existing multisegment models cannot completely decipher the impairments associated with the diabetic foot. METHODS: A four segment foot and ankle model for assessing the kinematics of the diabetic foot was developed. Ten normal subjects and 10 diabetics gait patterns were collected and major sources of variability were tested. Repeatability analysis was performed both on a normal and on a diabetic subject. Direct skin marker placement was chosen in correspondence of 13 anatomical landmarks and an optoelectronic system was used to collect the data. RESULTS: Joint rotation normative bands (mean plus/minus one standard deviation) were generated using the data of the control group. Three representative strides per subject were selected. The repeatability analysis on normal and pathological subjects results have been compared with literature and found comparable. Normal and pathological gait have been compared and showed major statistically significant differences in the forefoot and midfoot dorsi-plantarflexion. CONCLUSION: Even though various biomechanical models have been developed so far to study the properties and behaviour of the foot, the present study focuses on developing a methodology for the functional assessment of the foot-ankle complex and for the definition of a functional model of the diabetic neuropathic foot. It is, of course, important to evaluate the major sources of variation (true variation in the subject's gait and artefacts from the measurement procedure). The repeatability of the protocol was therefore examined, and results showed the suitability of this method both on normal and pathological subjects. Comparison between normal and pathological kinematics analysis confirmed the validity of a similar approach in order to assess neuropathics biomechanics impairment.

Posturographic analysis through markerless motion capture without ground reaction forces measurement.

The ability of the central nervous system to control posture and balance has been used with increasing frequency for the diagnosis and/or treatment evaluation of various neuromuscular diseases. Typically this analysis (Posturographic Analysis) is based on tracking the motion of the center of mass (COM) during quiet standing, however direct measurement of the COM has been commonly approximated using the movement of the center of pressure (COP). The purpose of this study was to apply and validate a new method to track the COM (center of mass) and COP (center of pressure) from a visual hull measured using a markerless motion capture (MMC) method. The method was tested by comparing the calculation of the COP from direct measurements of the COP. The deviations between the methods, below 2mm, were small relative to the average range of movement guaranteeing a satisfactory signal to noise ratio. This new method requires only kinematic data through MMC method and without the need of a force plate can identify the influence of individual body segments to motion of the COM.

A framework for the functional identification of joint centers using markerless motion capture, validation for the hip joint.

The objective of the study was to develop a framework for the accurate identification of joint centers to be used for the calculation of human body kinematics and kinetics. The present work introduces a method for the functional identification of joint centers using markerless motion capture (MMC). The MMC system used 8 color VGA cameras. An automatic segmentation-registration algorithm was developed to identify the optimal joint center in a least-square sense. The method was applied to the hip joint center with a validation study conducted in a virtual environment. The results had an accuracy (6mm mean absolute error) below the current MMC system resolution (1cm voxel resolution). Direct experimental comparison with marker-based methods was carried out showing mean absolute deviations over the three anatomical directions of 11.9 and 15.3mm if compared with either a full leg or only thigh markers protocol, respectively. Those experimental results were presented only in terms of deviations between the two systems (marker-based and markerless) as no real gold standard was available. The methods presented in this paper provide an important enabling step towards the biomechanical and clinical applications of markerless motion capture.

Glucose concentration can be predicted ahead in time from continuous glucose monitoring sensor time-series.

A clinically important task in diabetes management is the prevention of hypo/hyperglycemic events. In this proof-of-concept paper, we assess the feasibility of approaching the problem with continuous glucose monitoring (CGM) devices. In particular, we study the possibility to predict ahead in time glucose levels by exploiting their recent history monitored every 3 min by a minimally invasive CGM system, the Glucoday, in 28 type 1 diabetic volunteers for 48 h. Simple prediction strategies, based on the description of past glucose data by either a first-order polynomial or a first-order autoregressive (AR) model, both with time-varying parameters determined by weighted least squares, are considered. Results demonstrate that, even by using these simple methods, glucose can be predicted ahead in time, e.g., with a prediction horizon of 30 min crossing of the hypoglycemic threshold can be predicted 20-25 min ahead in time, a sufficient margin to mitigate the event by sugar ingestion.

The evolution of methods for the capture of human movement leading to markerless motion capture for biomechanical applications.

Over the centuries the evolution of methods for the capture of human movement has been motivated by the need for new information on the characteristics of normal and pathological human movement. This study was motivated in part by the need of new clinical approaches for the treatment and prevention of diseases that are influenced by subtle changes in the patterns movement. These clinical approaches require new methods to measure accurately patterns of locomotion without the risk of artificial stimulus producing unwanted artifacts that could mask the natural patterns of motion. Most common methods for accurate capture of three-dimensional human movement require a laboratory environment and the attachment of markers or fixtures to the body's segments. These laboratory conditions can cause unknown experimental artifacts. Thus, our understanding of normal and pathological human movement would be enhanced by a method that allows the capture of human movement without the constraint of markers or fixtures placed on the body. In this paper, the need for markerless human motion capture methods is discussed and the advancement of markerless approaches is considered in view of accurate capture of three-dimensional human movement for biomechanical applications. The role of choosing appropriate technical equipment and algorithms for accurate markerless motion capture is critical. The implementation of this new methodology offers the promise for simple, time-efficient, and potentially more meaningful assessments of human movement in research and clinical practice. The feasibility of accurately and precisely measuring 3D human body kinematics for the lower limbs using a markerless motion capture system on the basis of visual hulls is demonstrated.

An innovative ski-boot: design, numerical simulations and testing.

The present work is concerned with the design of an innovative ski-boot. In order to optimize ergonomics and biomechanical behavior of the ski-boot it is important to take into account the orientation of the leg with respect to the ground. The SGS system (Stance Geometry System) developed in this work allows the skier to adjust for posture in the frontal plane by rotating the sole of the boot about the antero-posterior axis (ski-boot is then locked in the desired position before skiing). A simplified model of the effect of ski-boot deformation on skiing behavior is used to evaluate the minimal stiffness the system must have. An experimental analysis on the ski slopes was carried out to provide ski-boot deformations and loading data in different skiing conditions, to be used in numerical simulations. Finite Elements Method (FEM) simulations were performed for optimal design of the joint between ski-boot and sole. The active loads and local ski-boot deformations during small- and large-radius turns were experimentally determined and used to validate a FEM model of the ski-boot. The model was used to optimize the design for maximum stiffness and to demonstrate the efficacy of virtual design supported by proper experimental data. Mean loads up to 164% body weight were measured on the outer ski during turning. The new SGS design system allows the adjustment of lateral stance before using the ski-boot, optimizing the ski-boot stiffness through FEM analysis. Innovative aspects of this work included not only the stance geometry system ski-boot but also the setup of a virtual design environment that was validated by experimental evidence. An entire dataset describing loads during skiing has been obtained. The optimized SGS ski-boot increases intrinsic knee stability due to proper adjustment of lateral stance, guaranteeing appropriate stiffness of the ski-boot system. Key PointsLoad acting during different phases of active skiing have been investigated in both qualitative and quantitative ways.The effects of ski-boot - ski-boot sole stiffness during skiing has been investigated.A ski-boot stance geometry system and an innovative design environment have been developed to make skiing easier and safer.