A Proposed New Obstacle-Set Algorithm for Modeling Deltoid

1. A Proposed New Obstacle-Set Algorithm for Modeling Deltoid Tiffany Xu Mentor: Dr. Brian Garner

2. Presentation Outline • I, Introduction to muscle modeling and why that is needed? • II, Application areas of muscle modeling. • III, Introduction to four mostly used muscle modeling methods. • IV, Studies carried out using the obstacle-set model. • Description of muscle modeling using obstacle-set model. • Difficulties encountered in modeling deltoid. • V, A new obstacle-set model. • Algorithm/methods. • Results/comparison with data from other studies. • Advantage of the new obstacle-set model. • VI, Conclusion. • VII, Questions.

3. Introduction to Muscle Modeling • In order to understand how each muscle works to influence our body behavior, all the following factors need to be studied: • Point of force application • Direction of force application • Force magnitude • But, not all of those factors could be obtained directly, which is why computer simulation of muscle activity emerges as a popular method to approximate the muscle moment arm. Through out the study of muscle mechanics, muscle moment arm is an eternal topic. Proper representation of muscle paths in musculoskeletal models is important for accurately modeling the magnitude and line-of-action of muscle forces.

4. Applications of Muscle Modeling Biomechanics (North Carolina State University, ergonomics research) Computer graphics [1] Patria A. Hume, Justin Keogh and Duncan Reid, The Role of Biomechanics in Maximizing Distance and Accuracy of Golf Shots. Sports Med 2005，35（5）: 429-449. [2] Arpad Illyes, Rita M. Kiss, Shoulder Muscle Activity During Pushing, Pulling, Elevation and Overhead Throw. Journal of Electromyography and Kinesiology 15(2005) 282-289. [3] Marcus G. Pandy, Computer Modeling and Simulation of Human Movement. Annual Reviews of Biomedical Engineering, 2001. 3:245-73.

5. Straight-line model Four Mostly Used Muscle Wrapping Methods Centroid line model 3D model via finite element algorithm Obstacle-set model Difficulty of Simulating the Muscle Path: Tension between desire to have model accuracy, and desire to have simplicity and computational efficiency.

6. Obstacle-set Model The muscle path in this method is formed by several segments of straight lines and curved lines joined together by via points. And the anatomical constrains are modeled by cylinder, sphere, stub, or other combination of those geometries.

7. Obstacle-set Model Has A Limitation in Modeling Broad Muscle • However, modeling some broad muscles crossing joints with wide ranges of motion can be difficult owing to: • Broad muscles are modeled with multiple bands. • Each band’s path is computed independently. • The independent bands of the deltoid have a tendency to slip around to unrealistic positions behind the sphere.

8. New Obstacle-set Algorithm --improvement was made The aim of this study was to develop a new obstacle-set algorithm that accounts for connectivity between muscle fibers, that will keep the fibers staying on the surface of the obstacle-set without any slip.

9. New Obstacle-set Algorithm for Modeling Deltoid • Origin siteson a fixed clavicle/scapula bone, and insertion sites on a moving humerus, were defined. • A sphere obstaclewas defined to represent anatomy underneath the deltoid. • Reference planes were specified. • Fixed angles between the path and reference planes were chosen to reflect the breadth of the deltoid muscle betweenbands. • Minimum-distance path of each muscle band around the sphere and within a “path plane” was calculated.

10. New Obstacle-set Algorithm for Modeling Deltoid The muscle paths were then applied onto the bone structure reconstructed from the Visible Human Project data. Anterior, medial, and posterior muscle path planes and their orientation; reference planes and their orientations. Sphere as the obstacle

11. Process of Simulation 60o 0o 30o • Move/rotate the humerus • Orientation of the anterior muscle path plane determined • Orientation of the medial and posterior muscle path planes changed • Minimum length of each muscle path computed • Above steps repeated to find the orientation value of the anterior muscle path plane which minimized the sum of the path lengths

12. Results of the New Obstacle-set Model • No slip. • Computational time was less than a millisecond. • Wide range of shoulder joint motion. • Realistic configurations of the hypothetical deltoid.

13. Results of the New Obstacle-set Model Why Say It Is Realistic? Abduction moment arm for anterior, medial and posterior deltoid from this new obstacle-set model, compared with experimental data from other two studies. -- Obstacle-set -- Liu -- Otis 1/3, Moment arm of anterior deltoid during abduction

14. Results of the New Obstacle-set Model -- Obstacle-set -- Liu -- Otis -- Obstacle-set -- Liu -- Otis 2/3, Moment arm of medial deltoid during abduction 3/3, Moment arm of posterior deltoid during abduction

15. Advantage of the New Obstacle-set Algorithm • Advantages of this algorithm include: • simplicity • realism • computational efficiency • connectivity between muscle fibers taken into account • flexible algorithm, so that an arbitrarily large number of muscle bands could be used to model broad muscles.

16. Conclusion Compared to other modeling methods, the new obstacle-set algorithm, is not only simple and fast, but also flexible and realistic. This improved obstacle-set model, handles the problem of slip that happened in the original one. The derived connectivity algorithm keeps the fibers of a broad muscle staying on surface of the sphere-shaped obstacle, which makes the new obstacle-set model robust. Comparison to the experimental data reveals a good approximation of the moment arm. But more experimental data needs to be studied and compared with, so that the realisticness of this new model could be improved.

17. Thank you! Any Questions? References: [1] Garner B.A., Pandy M.G., The Obstacle-Set Method for Representing Muscle Paths in Musculoskeletal Models. Computer Methods in Biomechanics and Biomedical Engineering, Vol. 3, pp. 1-30. [2] Silva S. Blemker and Scott L. Delp, Three-Dimensional Representation of Complex Muscle Architectures and Geometries. Annals of Biomedical Engineering, Vol. 33, No. 5, May 2005 pp.661-673. [3] Garner, B. A. and Pandy, M.G., A kinematic model of the upper limb based on the visible Human Project dataset. Computer Methods in Biomechanics and Biomedical Engineering. [4] Brian A. Garner and Marcus G. Pandy, Musculoskeletal Model of the Upper Limb Based on the Visible Human Male Dataset. Computer Methods in Biomechanics and Biomedical Engineering, Vol. 4, pp.93-126. [5] JC Otis, CC Jiang, TL Wickiewicz, MG Peterson, RF Warren and TJ Santner,Changes in the moment arms of the rotator cuff and deltoid muscles with abduction and rotation. Department of Biomechanics, Hospital for Special Surgery, New York, N.Y. 10021.