D4.13.2 3DRSBA Experiment Progress Report v1.0

8/11/2019 D4.13.2 3DRSBA Experiment Progress Report v1.0

http://slidepdf.com/reader/full/d4132-3drsba-experiment-progress-report-v10 1/22

This documents reports on the progress for the EXPERIMEDIA experiment 3DRSBA,

following on the initial report on experiment problem statement and requirements.

It contains the information about the current situation including explanations for each area.

D4.13.2

3DRSBA Experiment Progress Report

2014-05-28

Bertram Müller (3DRSBA)

www.experimedia.eu



EXPERIMEDIA Dissemination level: PU

© Copyright Qualisys and other members of the EXPERIMEDIA consortium 2014 2

Project acronym EXPERIMEDIA

Full title Experiments in live social and networked media experiences

Grant agreement number 287966

Funding scheme Large-scale Integrating Project (IP) Work programme topic Objective ICT-2011.1.6 Future Internet Research and Experimentation

(FIRE)

Project start date 2011-10-01

Project duration 36 months

Activity 4 Experimentation

Workpackage 4.13 EX13 - 3DRSBA: 3D Remote Sports Biomechanics Analysis

Deliverable lead organisation Qualisys

Authors Bertram Müller (3DRSBA)

Reviewers Stephen C. Phillips (IT Innovation)

Version 1.0

Status Final

Dissemination level PU: Public

Due date PM31 (2014-04-30)

Delivery date 2014-05-28





Table of Contents

1. Introduction ........................................................................................................................................ 4

2. Experiment Architecture and Implementation .............................................................................. 5

3. Experiment Progress .......................................................................................................................... 7

4. Future Plans ....................................................................................................................................... 15

5. Conclusion ......................................................................................................................................... 16

Appendix A. The biomechanical model .......................................................................................... 17

A.1. Marker Placement ................................................................................................................... 17

Appendix B. Lime survey questions ................................................................................................. 18

B.1. English Version (Lime Survey includes Spanish translation) ........................................... 18

Appendix C. List of most important literature for the model definition .................................... 19

Appendix D.

External document: "D4.13.2 3DRSBA Experiment Progress Report_Annex D.pdf"





1. Introduction

This deliverable reports on the progress of the EXPERIMEDIA experiment of 3D R emote

Sports Biomechanic A nalysis (3DRSBA). It follows the experiment description given in

"D4.13.1 - 3DRSBA Experiment Problem Statement and Requirements", and comments on thedifferent areas described.

The goal of 3DRSBA is to bring biomechanical analysis to the athlete in order to facilitate

screening for possible risk of lesions. It is based on the clinical need of injury prevention in

athletes associated with intense training routines.

The experiment is using modern technology used in biomechanical laboratories and taken off to

new areas, such the training field, by using fast internet connections and modern multimedia and

remote control tools.

The experiment itself consists of three general components:

The feasibility to use remote control techniques in biomechanical analysis;

The clinical viability of this approach, including clients satisfaction;

The easier presentation of such complex biomechanical data to non-experts.





2. Experiment Architecture and Implementation

The experiment consists of several stages:

1)

Installation of a modern 3D-capture system at CAR. The initial setup is situated in thebiomechanical laboratory at CAR and integrating with other existing systems. The

integration is necessary for the validation of the biomechanical model before it can be

used in the field. (Figure 1)

2)

Development of a biomechanical model, which could be used outside the laboratory without the usual additional systems available at the lab, but with consistency in the data.

3) Integration of capture setup with the core components of EXPERIMEDIA (Figure 2).

4) Initial testing of the setup inside the laboratory, including the remote control test from an

outside location.

5) Fine-tuning of the model and designing of the Project Automated Framework (PAF) for

fast preparation of the data (Figure 3).

6) Data collection in real-time situation and analysis.

Figure 1: A set of IR cameras (upper right) are capturing markers (upper left). The control programme istransferring the 3D data of a single marker included in a biomechanical model to 3D motion information

as seen at the bottom.





Figure 2: Integration of Experiment setup with EXPERIMEDIA core components.

Figure 3: Shows the full 3D workflow processing the 3D data from image to analysis.





3. Experiment Progress

A data-protection agreement between all partners of the project has been designed and signed,

including the definitions of the project and the ethical considerations. Special consideration has

been taken into account related to privacy of the individual and the dissemination interest ofEXPERIMEDIA. A project related confidentiality agreement for the athletes has been designed

and implemented. (D4.13.2 3DRSBA Experiment Progress Report_Annex C.pdf)

The project has been concretised between partners and the work-plan has been fine-tuned. This

included the experiment itself as well as the inclusion of the EXPERIMEDIA work frame

(Figure 2). The QoE integration will use the Lime-survey pack from EXPERIMEDIA for a

questionnaire. The QoS integration will use Version 2 of the ECC, recently presented.

Integration into the Qualisys software and the necessary programming is studied to date. An

initial version will be used with the first Process-Automated Framework (PAF) version.

The initial set-up of the 3D capture system has been done. Integration with existing hardware at

CAR has produced slight delays, which have been overcome. Those delays were also due to the

need that the initial Wi-Fi connection with the capture computer running a new system version

needed specialised IT installations. With support from the IT department at CAR those

problems had been solved. The system is now fully functional.

The experiment procedures as stated in deliverable D4.13.1 have been initiated and the current

situation is presented in the following listing:

Remote control

1) Familiarisation with the 3D system and the biomechanical software packages

necessary to treat the data.

The setup of the system at CAR had been done. Integration of the system into the existing

systems at CAR had produced a slight delay, but had been resolved to full satisfaction for all

participants. This includes:

The set-up of the cameras and for determining the best positions and settings for the

local situation at the biomechanics laboratory; The connection with the local force-plates and the synchronisation with the cameras;

Installation of capture programme (QTS), Camera server (QTM server), modelling

Software (Visual 3D), Remote control (teamviewer), connection with AD controller and

related software;

Defining and establishing the general and local co-ordinate systems and quality checks,

including test capture sessions;

Familiarisation of all operators with all distinctive software packages. The complexity of

those packages leads this to be continuous process;

Establishing the initial approach for the PAF development.





For easier familiarisation with the automated process routines Qualisys has developed in other

occasions, a running PAF was provided to CAR. Subsequent hardware changes were initiated by

the biomechanics laboratory at their treadmill for increasing capture quality. It also allowed using

the system for directly with athletes (Figure 4).

2) Testing the remote control protocol relating to the amount of data transmitted

and the effects of transmission delays on the experiment.

Initial tests were performed, including connections to outside locations (expert consultation and

support) as well as using the high speed network capabilities at CAR. The results were very

promising and have directed Qualisys to continue the development of two applications for

Apple/Android and adapt those both for improving the support possibilities for the

biomechanist at the Motion laboratory when an outside operator is using the system, e.g. at the

training site.

The first application ( viewfinder: Figure 5) allows the remote access to each individual capture-

camera. It has the options to zoom in to the capture space as well as allowing the user to change

the camera settings remotely for better capture quality. Information about the camera

identification as well as the amount of markers visible is shown on the screen.

Figure 4: Running athlete at the left and QTM PAF at the right: First column represents thePAF Framework with structure and indicators of procedures done (green) and missing (red).

In the middle is the model representation with automated marker recognition at the rightcolumn.





The second application ( QTM remote: Figure 6) has been adapted for remotely controlling the

capturing process. Originally, the capture is initiated by either pressing a button on the capture

PC or having a press-button connected to a defined camera. The new application allows theindependent connection using Wi-Fi connection providing the control person to be best

positioned for the capture process, e.g. supervising the capture from different angles with the

need of going back and forward to the PC to start the sequence.

Figure 5: QTM viewfinder with display of markers within the capture space (right) and optionsto change camera parameters (left).

Figure 6: QTM remote: Application for initiating and stopping the capture. The event marker can be usedto define important moments in the capture.





Whilst both applications have been tested for functionality, it will also be tested for improving

the handling of the system for the screening project.

3) Setting up single and multiple sites to test the effect of such approach on the

biomechanical expert.

This part is not yet initiated. The current side of testing is within the biomechanics laboratory.

Once the model and the first stage of automation are established, the system will be tested under

different light conditions in order to determine working conditions.

Biomechanical Model

1) Evaluation of current screening methods available.

In Appendix C the most important scientific articles are listed. Related to the experience gained

by CAR for screening procedures, the scientific baseline has been established in the first monthsof the project. Several aspects are noted:

Several centres in the world are interested in the screening process for risk factors of

lesions at the knee;

Several, but no uniform methods are tested;

There is no general gold standard established;

Strong indication is given for the type of motion to be performed by the athlete in order

to achieve adequate data: Drop Jumps (DJ) and Side cutting (SC) manoeuvres;

No fixed marker-set for optical systems has been established as best suited, but one hasbeen found which included a profound test-retest protocol.

Especially the last point is important, as it improves the quality of reproducibility and data

validity (Robinson et al). For the screening project it also provides an excellent starting point for

the modelling, as the type and amount of validity studies can be reduced at CAR. This gains time

in the project-workflow, whilst not compromising scientific quality.

Therefore, an initial test protocol, including a marker-set, has been established on which an

iterative approach can be used in defining the threshold of injury risk by CAR. In this process

the area between low risk group and high risk group can be narrowed down in the future. This

allows the screening to be used from the beginning whilst at the same time staying on the safe

side, clinically. As current models mentioned in the literature are only tested inside the

biomechanics laboratory, it has been decided that the Project Automated Framework (PAF) to

be developed should be applicable in both situations, either outside or inside. This would

facilitate the future development of the screening tool by CAR outside EXPERIMEDIA, and

also allow improving the clinical analysis and the comparison of the data.

2) Evaluation of existing protocols for the use in the screening process.

As for the screening methods, little consistent information has been found for the protocols

used in screening. Based on the experience at CAR and information from other scientific centres





being contacted had established a draft version of the protocol. This protocol includes

information about:

Structure of the screening process, including:

o

System preparation including set-up and calibration;o Preparation for the athlete (marker placements, warm-up) ;

o Test manoeuvres (number and times);

o Analysis workflow.

Quality assurance guidelines for the measurements;

The marker placement mapping;

Modell description and calibration;

Scientific background to the statements made in the protocol.

The screening protocol will include all the details about the methodology being used, but notabout the clinical reasoning at the analysis, as this depends on the expert using the system as well

as the additional data available. To facilitate the latter, a clinical questionnaire will be provided

using the lime-survey tool of EXPERIMEDIA, as it is explained in the chapter about the core

components.

Two major aspects have to be considered in the model used within the screening protocol: First

the general relation between superficial marker position and underlying anatomy, and secondly

the application on each athlete. The process responsible for the latter is the nominated quality

assurance. This also includes a guideline for increase reproducibility of the data.

3) Initial test with hardware/system.

Besides the general hardware test, as explained earlier, specific hardware/functional tests were

performed in order to set a baseline for the development of the specific screening protocol. In

this process, 12 capture session (7 male, 5 female) with a minimum of two hours each was

performed inside the motion laboratory. These capture sessions served the purpose of aligning

the system with the expected motion patterns of the screening protocol (jumping, side cutting,

frontal de-acceleration and reverse movements) as well as gaining experience with different

marker set up's and positioning on the human body for best capture results.

4) Developing the screening routine.

The protocol of the screening protocol includes the definition of the motion best fitted to detect

alterations at knee level, indicating injury risk factor for best analysis and risk detection. From

literature review as well as previous experience at CAR with video analysis, two movements were

selected to be most suited. The first one is a so called drop jump, which is a vertical jump from a

high of about 30-50cm. The second, called side-cutting, is a motion when running in one

direction is changed suddenly, changing direction on a single leg and moving sideways. The first

one has been chosen for previous experience, whilst the latter was chosen for the increased

changes on the knee control. Whilst this provides better data as the drop jump, only 3D





measurements are able to measure it precisely. The number of repetitions and the prior warm-up

also has to be established in the protocol.

Based on the aforementioned tests, including the 120 captures, parallel development lines were

initiated. The first dealt with the questions regarding the marker placement and analysis results,

whilst the second one investigated quality control mechanisms and model variations.

Figure 7 shows the first part of the capture process until the modelling stage. In this stage the

relation between anatomy and model representation needs to be established, in Figure 8 two

aspects are shown. The set-up is using the marker set as seen in Annex A.1.

A first draft of the protocol has been established and the development of the procedures used

for data preparation and data presentation (PAF) has been initiated. This version requires testing

which is now initiated at CAR. As the details of the PAF are of strong commercial interest, the

Figure 7: Left: markers placed on the athlete. Middle: capturing the marker and exporting it to themodelling software (right).

Figure 8: Left side shows a model where the knee position is correct in the right knee, butdisplaced at the left knee. This indicates model incongruences. The right side shows a modelling

strategy using different model position is order to detect best representation (at the right foot)





material is dealt with confidentially between CAR and Qualisys. Documentation of the process is

hosted at CAR.

Visualisation

8) Once the model (including marker placement is fixed), a visualisation protocol will be established. This includes the visualisation details for the avatar, the amount and

type of additional data and presentation.

The integration with the 3DCC component has been initiated. The idea is to provide a better

presentation for the end-user by using this EXPERIMEDIA component. However, there are

aspects which suggest incompatibility. This is due to the different marker configurations used for

biomechanical modelling and animation, the latter necessary for avatar creation. As the intention

of the biomechanical model is to be as less demanding as possible, the use of additional markers

in order to improve the generation of the avatar would increase a preparation time for the

capture and more time for the athlete to be tested. Intentions are made to overcome this

situation, but chances are limited.

However, as for the general presentation of the data, the PAF packaged will include graphs with

3D imaged for clinical assessment. The necessary information to be presented is in development.

9) Establishing initial design.

This is in progress and forms an integral part of the PAF development.

10) Developing system and testing.

Following the first set-up and PAF, this will be an iterative process within the PAF development.

Integration with core-components

The integration with the EXPERIMEDIA core components has been initialised with different

results. Integration into the ECC includes the different aspects for QoE and QoS.

For the QoE a survey conducted through Lime Survey has been developed (Appendix B). This

will investigate the user acceptance regarding the screening procedure. At the GA at CAR, it was

proposed to go back to the initial plan of using the Babylon interface. As this might improve the

data connection between QoS and QoE this was accepted and will be developed further. The

original concept of QoS integration will be adapted to the new structure. The exact definitions

on the metadata to be used were also dependent on the outcome information of the

biomechanical model; therefore complete integration had to wait until this stage.

The use of Lime Survey will be changed to be used for clinical analysis at CAR. Based on a

clinical questionnaire for the athletes, the motion analysis can related to the situation of

wellbeing of the athlete. This will facilitate the workflow at the clinical service at CAR and also

improve the analytical outcome of the screening process.





The use of the 3DCC component for use in visualisation is still in discussion, as the first results

did not show improvement over the current commercial product used (Visual 3D). This has

been discussed at the GA at CAR and a new proposal is investigated by Qualisys.

Dissemination

Dissemination of the experiment has been started. It was presented by Ventura Ferrer

(Biomechanics Lab, CAR) at the XXIII International Conference on Sports Rehabilitation and

Traumatology, organised in Milan in March 22-24.

The system has also been used as a training tool in the education for master students for several

regional Universities (University of Barcelona, Gimbernat, Blanquerna, Ramon Llull). Olympic

Committee coaches trained at CAR were also introduced to the system and its capabilities.

The setup and the function of the remote components were successfully presented at the GA at

CAR in May 2014. This demonstration also included the remote life demonstration for

calibration, capturing and processing the screening data.





4. Future Plans

Having established the model and methodological needs for the screening process, a first

automated process-pipeline will be created. This protocol will be tested in July with two football

clubs in the intended manner. Prior to this, the function of the protocol will be tested within thebiomechanics laboratory. These tests include the system set-up outside the laboratory.

With the first version of the pipeline, the integration with the ECC can be implemented and

tested. This includes a QoE/QoS-Babylon application (tablet), measuring the timing values for

each athlete at the test and a small questionnaire of user acceptance at the end of the test. The

questionnaire will be adapted, as Babylon cannot use text fields and writing on a tablet is limited

compared with using a keyboard in a web based application.

Further QoS data will be streamed coming from the Qualisys software and can be cross-

referenced to the Babylon data.

Lime Survey will be used for an analytical questionnaire, improving the outcome quality from the

screening. The treatment of this data type had been discussed with K.U.Leuven at the GA at

CAR. It was established that this fits perfectly in the data-treatment procedures for the

experiment. As this survey is more extensive than the original questionnaire, athletes will not be

asked to fill it in at the screening side, but will be provided with the access information for later

use. Therefore, the questionnaire is not used for the initial on-side conclusion, but for use in the

final report send to the clubs. The methods to inform the biomechanical laboratory about

questionnaires answered needs to be investigated. The goal is that the Laboratory will be

informed whenever a questionnaire was filled out, so the information can be used in the analysis. At the questionnaire, an identifier will be used, which can only be used at CAR for the relation to

the capture data.

As for the 3DCC, suggestion will be made quickly in the next development stages.

The remote control will be tested with the system at CAR, within the laboratory as well as in the

field close to the athlete.





5. Conclusion

Even with the increased time needed to specify all details of the project, the experiment is well

under way. Initial data on the scientific part are promising and continue to be optimised. The

timing is within the work frame for the field tests in July.

Integration with the core components are in process and being under development.

The development of the PAF will already provide increased possibilities for commercial use.

Besides the development of the biomechanical model, the user acceptance for the screening

outside the laboratory is essential. Additionally, it will be compared to existing simple forms of

screening using normal video. The relation between using a simple and quick, but imprecise

system versus a complex, precise system with increased set-up time is to be evaluated in order to

apply this methodology on a daily basis.

Dissemination will be when presenting the scientific results and the methodologies offered at

CAR as well as from the commercial point of view for Qualisys offering a new commercial PAF

to clients of the 3D system.





Appendix A. The biomechanical model

A.1. Marker Placement





Appendix B. Lime survey questions

B.1. English Version (Lime Survey includes Spanish translation)

1) Which type of sport are you training in? (Text or fields)

2)

For how many years are you active in your sport? (Field)

3) Were the EXPERIMEDIA project (including the test) and its purpose explained to you?

(1-5)

4) Was the explanation of the project to your satisfaction? (1-5)

5) Did the experiment and the explanations match? (1-5)

6) If not, what has been different: (Text)

7) Do you think that this type of screening-test would be beneficial to your sport? (1-5)

8) Do you think that this type of screening-test would improve the clinical service given at

CAR? (1-5)

9)

Do you think that this type of screening-test would beneficial to you personally? (1-5)10) Did you receive any biomechanical service before? (Yes/No)

11) If yes, how often per year? (1, 2, 3, more than 3)

12) Is the duration of the test acceptable? (1-5)

13) Was the warm-up time sufficient for you to be prepared? (Yes/No)

14) Did you find the test tiring for you? (Yes/No)

15) Did the test have negative influence to your training schedule? (Yes/No)

16) If yes, what would you change? (Text)

17) Do you believe that regular screening would help you in the process of preventing

injuries? (1-5)

18)

Any other remark you would like? (Text)





Appendix C. List of most important literature for the

model definition

Ball KA, Pierrynowski MR. Classification of errors in locating a rigid body. J Biomech1996;29(9):1213 – 7.

Bates NA, Ford KR, Myer GD, Hewett TE. Impact differences in ground reaction force and

center of mass between the first and second landing phases of a drop vertical jump and their

implications for injury risk assessment. J Biomech 2013;46(7):1237 – 41.

Bencke J, Zebis MK. The influence of gender on neuromuscular pre-activity during side-cutting.

Journal of Electromyography and Kinesiology 2011;21(2):371 – 5.

Cappello A, Cappozzo A, La Palombara PF, Lucchetti L, Leardini A. Multiple anatomical

landmark calibration for optimal bone pose estimation. Human Movement Science 1997;16(2 – 3):259 – 74.

Carson DW, Ford KR. Sex Differences in Knee Abduction During Landing. Sports Health

2011;3(4):373 – 82.

Cimolin V, Galli M. Summary measures for clinical gait analysis: A literature review. Gait &

Posture [Internet] 2014 [cited 2014 Mar 13];Available from:

http://linkinghub.elsevier.com/retrieve/pii/S0966636214000381

Earl JE, Monteiro SK, Snyder KR. Differences in lower extremity kinematics between a bilateral

drop-vertical jump and a single-leg step-down. J Orthop Sports Phys Ther 2007;37(5):245 – 52.

Etnoyer J, Cortes N, Ringleb SI, Van Lunen BL, Onate JA. Instruction and Jump-Landing

Kinematics in College-Aged Female Athletes Over Time. Journal of Athletic Training

2013;48(2):161 – 71.

Graf ES, Stefanyshyn DJ. The shifting of the torsion axis of the foot during the stance phase of

lateral cutting movements. Journal of Biomechanics 2012;45(15):2680 – 3.

Grip H, Häger C. A new approach to measure functional stability of the knee based on changes

in knee axis orientation. Journal of Biomechanics 2013;46(5):855 – 62.

Holden JP, Chou G, Stanhope SJ. Changes in knee joint function over a wide range of walking

speeds. Clinical Biomechanics 1997;12(6):375 – 82.

Holm DJ, Stålbom M, Keogh JWL, Cronin J. Relationship Between the Kinetics and Kinematics

of a Unilateral Horizontal Drop Jump to Sprint Performance: Journal of Strength and

Conditioning Research 2008;22(5):1589 – 96.

Hopkins WG. Measures of reliability in sports medicine and science. Sports Med 2000;30(1):1 –

15.





Hurd WJ, Axe MJ, Snyder-Mackler L. A 10-year prospective trial of a patient management

algorithm and screening examination for highly active individuals with anterior cruciate ligament

injury: Part 1, outcomes. Am J Sports Med 2008;36(1):40 – 7.

Hurd WJ, Axe MJ, Snyder-Mackler L. A 10-Year Prospective Trial of a Patient Management

Algorithm and Screening Examination for Highly Active Individuals with ACL Injury. Part II:Determinants of Dynamic Knee Stability. Am J Sports Med 2008;36(1):48 – 56.

Ida H, Nagano Y, Akai M, Ishii M, Fukubayashi T. Estimation of tibiofemoral static zero

position during dynamic drop landing. The Knee 2013;20(5):339 – 45.

Jamison ST, McNally MP, Schmitt LC, Chaudhari AMW. The effects of core muscle activation

on dynamic trunk position and knee abduction moments: Implications for ACL injury. Journal

of Biomechanics 2013;46(13):2236 – 41.

Kai S, Sato T, Koga Y, Omori G, Kobayashi K, Sakamoto M, et al. Automatic construction of

an anatomical coordinate system for three-dimensional bone models of the lower extremities –

Pelvis, femur, and tibia. Journal of Biomechanics 2014;47(5):1229 – 33.

Kiernan D, Malone A, O Brien T, Simms CK. A 3-dimensional rigid cluster thorax model for

kinematic measurements during gait. Journal of Biomechanics [Internet] 2014 [cited 2014 Mar

12];Available from: http://linkinghub.elsevier.com/retrieve/pii/S0021929014001146

Knudson DV. Authorship and sampling practice in selected biomechanics and sports science

journals. Percept Mot Skills 2011;112(3):838 – 44.

Kristianslund E, Krosshaug T, Mok K-M, McLean S, van den Bogert AJ. Expressing the jointmoments of drop jumps and sidestep cutting in different reference frames – does it matter?

Journal of Biomechanics 2014;47(1):193 – 9.

Lam M-H, Fong DT, Yung PS, Ho EP, Chan W-Y, Chan K-M. Knee stability assessment on

anterior cruciate ligament injury: Clinical and biomechanical approaches. Sports Med Arthrosc

Rehabil Ther Technol 2009;1:20.

Laughlin WA, Weinhandl JT, Kernozek TW, Cobb SC, Keenan KG, O’Connor KM. The effects

of single-leg landing technique on ACL loading. Journal of Biomechanics 2011;44(10):1845 – 51.

Lees A, Vanrenterghem J, Clercq DD. Understanding how an arm swing enhances performance

in the vertical jump. Journal of Biomechanics 2004;37(12):1929 – 40.

Malfait B, Sankey S, Azidin RMFR, Deschamps K, Vanrenterghem J, Robinson MA, et al. How

Reliable Are Lower Limb Kinematics and Kinetics during a Drop Vertical Jump? Med Sci Sports

Exerc 2013;

Mapelli A, Zago M, Fusini L, Galante D, Colombo A, Sforza C. Validation of a protocol for the

estimation of three-dimensional body center of mass kinematics in sport. Gait & Posture

2014;39(1):460 – 5.





McLean SG, Beaulieu ML. Complex integrative morphological and mechanical contributions to

ACL injury risk. Exerc Sport Sci Rev 2010;38(4):192 – 200.

Milner CE, Westlake CG, Tate JJ. Test-retest reliability of knee biomechanics during stop jump

landings. J Biomech 2011;44(9):1814 – 6.

Myer GD, Ford KR, Khoury J, Succop P, Hewett TE. Development and validation of a clinic-

based prediction tool to identify female athletes at high risk for anterior cruciate ligament injury.

Am J Sports Med 2010;38(10):2025 – 33.

Pain MTG. Dynamic changes in moments of inertia of the shank during drop landings

[Internet]. In: Proceedings of the XXIV. Congress of the International Society of Biomechanics.

Natal, Brazil: 2013. Available from: http://isbweb.org/images/stories/conferences/isb-

congresses/2013/oral/sb-jumping.08.pdf

Pataky TC, Robinson MA, Vanrenterghem J. Vector field statistical analysis of kinematic and

force trajectories. Journal of Biomechanics 2013;46(14):2394 – 401.

Robinson MA, Donnelly CJ, Tsao J, Vanrenterghem J. A comparison of direct and inverse

kinematic modelling approaches and their influence on knee abduction moment estimates and

acl injury risk classification. [Internet]. In: Proceedings of the XXIV. Congress of the

International Society of Biomechanics. Natal, Brazil: 2013. Available from:

http://isbweb.org/images/stories/conferences/isb-congresses/2013/oral/cb-acl-pain.02.pdf

Robinson MA, Vanrenterghem J. An evaluation of anatomical and functional knee axis definition

in the context of side-cutting. Journal of Biomechanics 2012;45(11):1941 – 6.

Roos P, Button K, van Deursen R. Motor control strategies to reduce knee moments in the

injured leg during a double leg squat in anterior cruciate injured patients [Internet]. In:

Proceedings of the XXIV. Congress of the International Society of Biomechanics. Natal, Brazil:

2013. Available from: http://isbweb.org/images/stories/conferences/isb-

congresses/2013/oral/cb-acl-pain.05.pdf

Russell KA, Palmieri RM, Zinder SM, Ingersoll CD. Sex Differences in Valgus Knee Angle

During a Single-Leg Drop Jump. J Athl Train 2006;41(2):166 – 71.

Sankey S, Malfait B, Firhad RM, Raja-Azadin RM, Deschamps K, Robinson M, et al. Thereliability of biomechanical analysis in dynamic sidecutting tasks. In: Proceedings of the XXIV.

Congress of the International Society of Biomechanics. Natal, Brazil: 2013.

Sell TC, Ferris CM, Abt JP, Tsai Y-S, Myers JB, Fu FH, et al. The effect of direction and reaction

on the neuromuscular and biomechanical characteristics of the knee during tasks that simulate

the noncontact anterior cruciate ligament injury mechanism. Am J Sports Med 2006;34(1):43 – 54.

Sharma L, Lou C, Felson DT, Dunlop DD, Kirwan-Mellis G, Hayes KW, et al. Laxity in healthy

and osteoarthritic knees. Arthritis Rheum 1999;42(5):861 – 70.

Shin CS, Chaudhari AM, Andriacchi TP. Valgus plus internal rotation moments increase anteriorcruciate ligament strain more than either alone. Med Sci Sports Exerc 2011;43(8):1484 – 91.





Shultz SJ, Anh-Dung N, Levine BJ. The Relationship between Lower Extremity Alignment

Characteristics and Anterior Knee Joint Laxity. Sports Health 2009;1(1):54 – 60.

Shultz SJ, Schmitz RJ, Benjaminse A, Chaudhari AM, Collins M, Padua DA. ACL Research

Retreat VI: An Update on ACL Injury Risk and Prevention. J Athl Train 2012;47(5):591 – 603.

Shultz SJ, Schmitz RJ, Beynnon BD. Variations in Varus/Valgus and Internal/External

Rotational Knee Laxity and Stiffness across the Menstrual Cycle. J Orthop Res 2011;29(3):318 –

25.

Stief F, Böhm H, Michel K, Schwirtz A, Döderlein L. Reliability and accuracy in three-

dimensional gait analysis: a comparison of two lower body protocols. J Appl Biomech

2013;29(1):105 – 11.

Tiemessen IJ, Kuijer PPF, Hulshof CT, Frings-Dresen MH. Risk factors for developing jumper’s

knee in sport and occupation: a review. BMC Res Notes 2009;2:127.

Tsai LC, Sigward SM, Pollard CD, Fletcher MJ, Powers CM. The effects of fatigue and recovery

on knee kinetics and kinematics during side-step cutting. Journal of Biomechanics 2007;40:S102.

Vanrenterghem J, Gormley D, Robinson M, Lees A. Solutions for representing the whole-body

centre of mass in side cutting manoeuvres based on data that is typically available for lower limb

kinematics. Gait Posture 2010;31(4):517 – 21.

Vanrenterghem J, Lees A, Lenoir M, Aerts P, De Clercq D. Performing the vertical jump:

Movement adaptations for submaximal jumping. Human Movement Science 2004;22(6):713 – 27.

Vanrenterghem J, Malfait B, Sankey S, Raja-Azadin RM, Deschamps K, Robinson M, et al. Knee

joint kinematics and kinetics of drop vertical jumps: reliability and its clinical relevance [Internet].

2013 [cited 2014 Mar 12];Available from: https://lirias.kuleuven.be/handle/123456789/399495

Vanrenterghem J, Venables E, Pataky T, Robinson MA. The effect of running speed on knee

mechanical loading in females during side cutting. Journal of Biomechanics 2012;45(14):2444 – 9.

Wang H, Fleischli JE, Nigel Zheng N. Effect of lower limb dominance on knee joint kinematics

after anterior cruciate ligament reconstruction. Clin Biomech (Bristol, Avon) 2012;27(2):170 – 5.

Zhang L-Q, Shiavi RG, Limbird TJ, Minorik JM. Six degrees-of-freedom kinematics of ACLdeficient knees during locomotion-compensatory mechanism. Gait Posture 2003;17(1):34 – 42.

D4.13.2 3DRSBA Experiment Progress Report v1.0

Documents