In Sweden almost three persons over the age of 65 years dies every daybecause of fall injuries. The overall societal costs of elderly fall accidentswere estimated to to be 14 billion SEK, and if no action is taken this cost isestimated to increase to 22 billion SEK until 2050. The individual decreasein life of quality due to pain, decrease of independence and, for those stillworking, a decrease in income is of course also well worth considering.It is well known that multitasking while walking will decrease attentionon the surroundings and gait behaviour which increases the risk of falling. Itis known that walking uses both sensory input and visual inputs to guide themotion. The visual input prepares the body to adjust itself before a step istaken to optimize the outcome.This study aimed to investigate the effect of multitasking on gaze strategiesand gait performance. Five healthy adults walked over a setup of ramps and astep while performing three different levels of cognitive loading: just walking,walking and performing mental arithmetic’s and walking and scrolling on amobile cell phone.The eye tracking device Pupil Core (Pupil Labs, Berlin, Germany) wasused to capture the gaze points of the participants and Vicon Nexus togetherwith force plates were used to capture data to compute the kinematics of theparticipants during the walking.The results revealed that four out of four participants had a lower ratio ofgaze fixations on objects of interest when scrolling on the phone comparedto just walking, and three out of four participants had a lower ratio of gazefixations on objects of interest when doing mental arithmetic’s compared tojust walking. Simultaneously the gait parameters and kinematics changed in away that might increase the risk of falling. Four out of four participants had adecrease in average stride length and average stride velocity when walkingwhile scrolling on a phone and a decrease in average stride velocity whenperforming mental arithmetic’s compared to just walking. Three out of fourparticipants had a decrease in average stride length when performing mentalarithmetic’s compared to just walking.Since the participant number was low more studies are needed to confirmthese results. The experimental design would benefit from adjustments to tryto separate the effect on gaze behaviour between altered cognitive loading andaltered gait pattern, but are a good base to use for further studies.

Simulating the motion of a non-rigid body under external forces is a difficult problem because of the complexity and flexibility of the non-rigid geometry and its associated dynamics. Physically based animation of objects moving in the wind is computationally expensive, so simulation-based approaches oversimplify the model by ignoring important effects, such as tree's sheltering. Motion capture records actual responses of a non-rigid body to external forces and helps solve these problems. Mainly focusing on natural trees and ropes as instances of non-rigid bodies, we present a new approach to building motion for objects in wind using incomplete motion capture data from non-rigid bodies. The incomplete motion capture data are automatically labeled by a cluster-based algorithm while noises are removed. For places with no motion capture data, we estimate forces and motion by interpolating the motion capture data according to the object's characteristics. We discuss a physically or statistically based approach to animate the whole non-rigid object. Basing our work on the collected motion capture data and the estimated motions, we can produce visually plausible and scalable animations of non-rigid objects under external forces at interactive frame rates.

Musculoskeletal models and simulations allow for the estimation of forces acting on muscles and joints during human movement and athletic performance. In order to improve the accuracy of these models for a specific application, knowledge about subject-specific in vivo properties of human muscle and tendon is needed. This study presents a method for estimating in vivo mechanical properties of human tendon in the lower leg, using a combination of ultrasound imaging and motion capture. Key mechanical parameters — such as tendon stiffness, moment arm, slack length and force-strain relationship — and the contribution of tendon elongation to ankle mobility of the medial gastrocnemius (MG) and soleus (SOL) aspects of the Achilles tendon were obtained in vivo in 8 typically-developed adults, and the applicability of the method on the tibialis anterior (TA) tendon was investigated. In contrast to previous studies using a comparable method, variable tendon moment arm lengths during passive movement of the ankle joint was taken into consideration. As a novelty, the passive mechanical properties of the Achilles tendon were obtained in vivo in 4 hemiplegic post-stroke subjects and compared to the 8 typically-developed subjects. The estimated mechanical parameters of the MG and SOL aspects of the Achilles tendon were consistent with findings in the literature. In order to estimate stiffness of the TA tendon, it was shown that a larger range of motion (ROM) of the foot during the passive rotation experiments is needed. The comparison between typically-developed and hemiplegic post-stroke subjects revealed significantly lower tendon stiffness and slack angle, and significantly higher contribution of tendon elongation to ankle mobility in the post-stroke group. The developed method enables estimation of in vivo mechanical properties of tendon in the lower leg and contributes to improving the accuracy of subject-specific musculoskeletal models and simulations. / Person-specific biomechanical models

Osteoarthritis (OA) is a degenerative condition of cartilage and is the leading cost of disability in the United States. Motion analysis experiments in combination with knee-joint finite element (FE) analysis may be used to identify exercises that maintain knee-joint osteochondral (OC) loading at safe levels for patients at high-risk for knee OA, individuals with modest OC defects, or patients rehabilitating after surgical interventions. Therefore, a detailed total knee-joint FE model was developed by modifying open-source knee-joint geometries in order to predict OC tissue stress and strain during the stance phase of gait. The model was partially validated for predicting the timing and locations of maximum contact parameters (contact pressure, contact area, and principal Green-Lagrangian strain), but over-estimated contact parameters compared with both published in vivo studies and other FE analyses of the stance phase of gait. This suggests that the model geometry and kinematic boundary conditions utilized in this FE model are appropriate, but limitations in the material properties used, as well as potentially the loading boundary conditions represent primary areas for improvement.

No / We introduce a new "marker-based" model for use in capturing equine movement. This model is informed by a sound biomechanical study of the animal and can be deployed in the pursuit of many undertakings. Unlike many other approaches, our method provides a high level of automation and hides the intricate biomechanical knowledge required to produce realistic results. Due to this approach, it is possible to acquire solved data with minimal manual intervention even in real-time conditions. The approach introduced can be replicated for the production of many other animals. The model is first informed by the veterinary world through studies of the subject's anatomy. Second, further medical studies aimed at understanding and addressing surface processes, inform model creation. The latter studies address items such as skin sliding. If not otherwise corrected these processes may hinder marker based capture. The resultant model has been tested in feasibility studies for practicality and subject acceptance during production. Data is provided for scrutiny along with the subject digitally captured through a variety of methods. The digital subject in mesh form as well as the motion capture model aid in comparison and show the level of accurateness achieved. The video reference and digital renders provide an insight into the level of realism achieved.

Yes / Aims: To create a gait database with optimum accuracy of joint rotational data and an accu-rate representation of 3D volume, and explore the potential of using the database in studying the relationship between static and dynamic features of a human’s gait. Study Design: The study collected gait samples from 38 subjects, in which they were asked to walk, run, walk to run transition, and walk with a bag. The motion capture, video, and 3d measurement data extracted was used to analyse and build a correlation between features. Place and Duration of Study: The study was conducted in the University of Bradford. With the ethical approval from the University, 38 subjects’ motion and body volumes were recorded at the motion capture studio from May 2011- February 2013. Methodology: To date, the database includes 38 subjects (5 females, 33 males) conducting walk cycles with speed and load as covariants. A correlation analysis was conducted to ex-plore the potential of using the database to study the relationship between static and dynamic features. The volumes and surface area of body segments were used as static features. Phased-weighted magnitudes extracted through a Fourier transform of the rotation temporal data of the joints from the motion capture were used as dynamic features. The Pearson correlation coefficient is used to evaluate the relationship between the two sets of data. Results: A new database was created with 38 subjects conducting four forms of gait (walk, run, walk to run, and walking with a hand bag). Each subject recording included a total of 8 samples of each form of gait, and a 3D point cloud (representing the 3D volume of the subject). Using a Pvalue (P<.05) as a criterion for statistical significance, 386 pairs of features displayed a strong relationship. Conclusion: A novel database available to the scientific community has been created. The database can be used as an ideal benchmark to apply gait recognition techniques, and based on the correlation analysis, can offer a detailed perspective of the dynamics of gait and its relationship to volume. Further research in the relationship between static and dynamic features can contribute to the field of biomechanical analysis, use of biometrics in forensic applications, and 3D virtual walk simulation.

Traumatic brain injury (TBI) is a leading cause of disability in the United States (Coronado et al., 2011). There is a recognized need for better motor assessments to help mitigate these disabilities. Advances in markerless motion capture and in magnetic resonance imaging (MRI) provide an opportunity to improve clinical assessments, and link them to damage measured in MRI scans. The primary aims of this research were to 1) develop a quantitative motor assessment (QMA), and seed a normative database to enable comparison of impaired behavior to unimpaired, 2) test the sensitivity of the QMA, and 3) link QMA results to underlying TBI damage.The QMA developed in Aim 1 consisted of five tests: finger oscillation, tremor, visually guided movement, reaction time, and balance. We administered the QMA and traditional analgous tests to 132 healthy 18-50 year olds. We later added a coginitive motor integration (CMI) test and a stength-dexterity pinch test, then administered them to 31 (16 male, mean age = 24.7) healthy individuals. We seeded a normative database for the QMA and CMI measures. (A normative database for the pinch test already exists.) Correlations between the QMA and traditional tests were weak but the QMA results followed expected trends.In the second aim, 31 (16 male, mean age = 24.7 years) individuals with TBI completed all of the motor tests, and age- and gender-matched controls completed the CMI and pinch tests. We tested the sensivity of the QMA, the CMI and pinch tests, and traditional tests by their ability to correctly identify TBI subjects based solely on test results. The QMA was more sensitive than the other test groups. In Aim 3, we performed a stepwise regression to evaluate the relationship between motor deficits and brain injury, using motor test results and MRI images from the TBI and control groups. We found significant relationships between deficits in precision and increases in superior lateral ventricular volumes, deficits in pointing tasks and decreases in fractional anisotropy (FA) in the corticospinal tract, deficits in rhythmicity during finger oscillation and decreased FA in the thalamocortical tract. There were also relationships between each of the motor deficit measures and the FA values in the corpus callosum. This was the first step in showing that a quantitative motor assessment using markerless motion capture is feasible. The QMA is sensitive and can be linked to underlying brain damage. Though the QMA is not yet ready for clinical use, this research provides insights that will help address gaps in TBI rehabilitation.

At least 2.6 billion people all over the world suffer from nearsightedness, among whom 312 million are under 19 years old. Just like other vision problems, uncorrected nearsightedness brings inconvenience to many human daily activities including walking. However, the influence of nearsightedness on gait patterns and gaze behaviours remains barely discovered. This project aimed to study the influence of nearsightedness on human visuomotor coordination in different environmental settings. An integrated system combining motion capture and eye-tracking was implemented for measuring gait and gaze simultaneously. Twelve participants were recruited to perform a protocol consisting of walking tasks in various visual and environmental conditions. Nine of the participants were eligible for data analysis. Gaze time distribution and gait cycle parameters were compared between participant groups (five with normal vision, four nearsighted), and among different walking tasks. Results revealed that comparing with the control group, the nearsighted participants made shorter and slower steps, as well as spent more time looking at the walking path. The walking path also affected the gait and gaze behaviours, with shorter step length and longer step time observed when the participants were walking uphill, while increased gaze attention was paid downhill. The practicality of combining gait analysis with eye-tracking was proved in this project, laying a foundation for future studies of visuomotor coordination.

Biometrics is a unique physical or behavioral characteristic of a person. This unique attribute, such as fingerprints or gait, can be used for identification or verification purposes. Gait is an emerging biometrics with great potential. Gait recognition is based on recognizing a person by the manner in which they walk. Its potential lays in that it can be captured at a distance and does not require the cooperation of the subject. This advantage makes it a very attractive tool for forensic cases and applications, where it can assist in identifying a suspect when other evidence such as DNA, fingerprints, or a face were not attainable. Gait can be used for recognition in a direct manner when the two samples are shot from similar camera resolution, position, and conditions. Yet in some cases, the only sample available is of an incomplete gait cycle, low resolution, low frame rate, a partially visible subject, or a single static image. Most of these conditions have one thing in common: static measurements. A gait signature is usually formed from a number of dynamic and static features. Static features are physical measurements of height, length, or build; while dynamic features are representations of joint rotations or trajectories. The aim of this thesis is to study the potential of predicting dynamic features from static features. In this thesis, we have created a database that utilizes a 3D laser scanner for capturing accurate shape and volumes of a person, and a motion capture system to accurately record motion data. The first analysis focused on analyzing the correlation between twenty-one 2D static features and eight dynamic features. Eleven pairs of features were regarded as significant with the criterion of a P-value less than 0.05. Other features also showed a strong correlation that indicated the potential of their predictive power. The second analysis focused on 3D static and dynamic features. Through the correlation analysis, 1196 pairs of features were found to be significantly correlated. Based on these results, a linear regression analysis was used to predict a dynamic gait signature. The predictors chosen were based on two adaptive methods that were developed in this thesis: "the top-x" method and the "mixed method". The predictions were assessed for both for their accuracy and their classification potential that would be used for gait recognition. The top results produced a 59.21% mean matching percentile. This result will act as baseline for future research in predicting a dynamic gait signature from static features. The results of this thesis bare potential for applications in biomechanics, biometrics, forensics, and 3D animation.

The use of motion capture, virtual reality and 3D animation are widely used within the entertainment sector, and simulation for training in a variety of industries. As the knowledge and technology for digital visualizations are continuously improving, the interest and areas of application are growing as well. An increasing amount of research has been conducted lately within the area of application for dance and dance pedagogy, and this study aims to investigate the possibilities that are within this area of visualizations for dance. We prepared a simple visualization prototype using recorded motion capture data of two dancers. In the next stage, participants got to discuss the prototype in an interview format. Based on the data gathered from the interviews, we could conclude some opportunities, limitations and areas of application for dance visualizations using motion capture. The conclusion was that motion capture has many opportunities to be used as a tool in dance education, given that the visualizations are done with enough level of detail This study is laying a foundation for continued research within the area, and gives an idea of the current interest among dancers who are active in dance education. / Användningen av motion capture, virtual reality och 3D animering är vida använt inom underhållningsbranschen och simulering som träning inom olika branscher. Medan kunskapen och tekniken inom digitala visualiseringar fortsätter utvecklas, så ökar även intresset och applikationsområdena. På sistone har mer forskning inom applicering på specifikt dans och danspedagogik gjorts, och den här studien fortsätter undersöka möjligheterna som finns inom området. Genom att ta fram enkla visualiseringar av dans inspelat med motion capture, användes detta som material som deltagarna i studien fick diskutera kring under en intervju. Utifrån dessa kunde slutsatser dras kring de användningsområden deltagarna såg med visualiseringarna, samt möjligheter och begränsningar. Slutsatsen var att motion capture har stora möjligheter för att fungera som ett verktyg i dansundervisning, om visualiseringarna görs tillräckligt utförliga och detaljerade. Den här studien lägger en grund för fortsatt forskning inom området och ger en bild av det nuvarande intresset bland dansare som har undervisning och pedagogik inom dans som sysselsättning.