Extrinsic and Intrinsic Index Finger Muscle Attachments in an OpenSim Upper- Extremity Model Jong Hwa Lee, Deanna S. Asakawa, Jack T. Dennerlein & Devin L. Jindrich Annals of Biomedical Engineering The Journal of the Biomedical Engineering Society ISSN 0090-6964 Ann Biomed Eng DOI 10.1007/s10439-014-1141-2 1 23 Your article is protected by copyright and all rights are held exclusively by Biomedical Engineering Society. This e-offprint is for personal use only and shall not be self- archived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com”. 1 23 Author's personal copy Annals of Biomedical Engineering (Ó 2014) DOI: 10.1007/s10439-014-1141-2 Extrinsic and Intrinsic Index Finger Muscle Attachments in an OpenSim Upper-Extremity Model 1 2 3 2 JONG HWA LEE, DEANNA S. ASAKAWA, JACK T. DENNERLEIN, and DEVIN L. JINDRICH 1Department of Mechanical and Aerospace Engineering, Arizona State University, Tempe, AZ, USA; 2Department of Kinesiology, California State University San Marcos, 333 S. Twin Oaks Valley Rd., University Hall 302, San Marcos, CA 92096, USA; and 3Department of Physical Therapy, Movement, and Rehabilitation Sciences, Bouve´College of Health Sciences, Northeastern University, Boston, MA, USA (Received 8 June 2014; accepted 23 September 2014) Associate Editor Peter E. McHugh oversaw the review of this article. Abstract—Musculoskeletal models allow estimation of mus- INTRODUCTION cle function during complex tasks. We used objective methods to determine possible attachment locations for Multitouch human computer interfaces (HCIs), index finger muscles in an OpenSim upper-extremity model. such as the touchscreens of many handheld devices, Data-driven optimization algorithms, Simulated Annealing often involve complex multi-finger gestures or gesture and Hook-Jeeves, estimated tendon locations crossing the 56,58,67 metacarpophalangeal (MCP), proximal interphalangeal sequences. Although the forces involved in (PIP) and distal interphalangeal (DIP) joints by minimizing making individual gestures may be low, long-term and the difference between model-estimated and experimentally- repetitive interactions with touchscreen computing measured moment arms. Sensitivity analysis revealed that devices present the potential for injury.8 However, the multiple sets of muscle attachments with similar optimized biomechanics of coordinated finger movements for moment arms are possible, requiring additional assumptions or data to select a single set of values. The most smooth touchscreen interaction are not well understood. muscle paths were assumed to be biologically reasonable. Consequently, better understanding of finger dynam- Estimated tendon attachments resulted in variance accounted ics, joint forces, and control during multitouch tasks for (VAF) between calculated moment arms and measured could lead to interface designs that reduce injury risks values of 78% for flex/extension and 81% for ab/adduction associated with repetitive finger movements. at the MCP joint. VAF averaged 67% at the PIP joint and 54% at the DIP joint. VAF values at PIP and DIP joints External hand and finger loadings do not directly partially reflected the constant moment arms reported for correspond to internal musculoskeletal loading, which muscles about these joints. However, all moment arm values can be difficult to determine.54 However, anatomically found through optimization were non-linear and non-con- based musculoskeletal models can predict musculoskel- stant. Relationships between moment arms and joint angles etal loading and can help design strategies to reduce in- were best described with quadratic equations for tendons at 16,20,39,44,61 the PIP and DIP joints. jury and improve motor function. Anatomical studies of the elbow and shoulder enabled development 17,23,51 Keywords—Hand, Finger, Arm, Moment arm, Muscle of detailed arm musculoskeletal models. Arm geometry, Musculoskeletal, Optimization, Simulated anneal- models can estimate torques at the shoulder and elbow, ing, Variability, Redundancy. e.g., for development and user training of neural pros- thesis systems.13,22,29,62 Hand models have also been useful for understanding many aspects of function such as finger tapping on computer keyboards.3,5,37,52,53,57,59,69 Although hand models have been helpful in specific contexts, existing dynamic models of the hand often fo- cus on specific fingers and have not been used to understand complex, multi-finger gestures such as those Address correspondence to Devin L. Jindrich, Department of used during multitouch HCI tasks. Kinesiology, California State University San Marcos, 333 S. Twin We therefore seek to develop a musculoskeletal Oaks Valley Rd., University Hall 302, San Marcos, CA 92096, USA. model capable of estimating internal loadings during Electronic mail: [email protected] Ó 2014 Biomedical Engineering Society Author's personal copy LEE et al. multitouch tasks. Because multitouch and gestural compartments. Metacarpal and phalanx geometry, and movements involve not only the fingers, but also the approximated positions and orientations of finger joint entire kinematic chain of the hand and arm, we chose axes, are scaled to a 50th percentile male. Axes of to build upon an existing arm model available on an rotation were determined by fitting long axes of cyl- open access platform (OpenSim 2.3.2, Simbios, Stan- inders to the articular surfaces of the metacarpal and ford, CA.15). The model incorporates information for phalangeal bones.29 muscles at the shoulder and elbow, but it does not yet model intrinsic finger muscles. OpenSim is a homeo- Musculoskeletal Model morphic model: parameters and values correspond directly to anatomical structure and function. There- We added the following muscles or muscle groups to fore, appropriate muscle attachment sites within the the index finger of OpenSim model: terminal extensor anatomy of the OpenSim model must be determined. (TE), extensor slip (ES), radial band (RB), ulnar band Detailed measurements of muscle attachments have (UB), first dorsal interosseous or radial interosseous been made for the hand.3,36 However, muscle attach- (RI), lumbricals (LU), first palmar interosseous or ul- ment locations are specific to the anatomical model nar interosseous (UI), flexor digitorum profundus within which they are expressed, and cannot be directly (FDP), flexor digitorum superficialis (FDS) and transformed to a different model such as OpenSim. extensor digitorum communis (EDC). The index finger For example, the model of An et al.3 is normalized was modeled to have four degrees of freedom (DOFs). only to the middle phalanx in a 2 dimensional (2D) The metacarpophalangeal (MCP) joint has 2 DOFs: sagittal plane, and scaling its attachment locations in a ab/adduction and flex/extension. Both the proximal 3D Cartesian space (c.f. Refs. 24,38) does not result in interphalangeal (PIP) and distal interphalangeal (DIP) continuous moment arms that match experimentally joints are modeled to have one DOF: flex/extension. measured values.34 This poor correspondence could Based on experimental measurements available for result from a lack of important information such as comparison, we limited our analysis to the following joint thickness, position and orientation of rotational range of motion (RoM) at the MCP joint: 0°–90° axes, skeletal structure, and changes associated with (flexion: +) as well as 0°–30° (abduction: +). Simi- transforming from 2 to 3 dimensions among other larly, for PIP and DIP joints we considered 0°–90° factors. (flexion: +) and 50° (flexion: +) respectively.4,14 The To create the most functionally useful model pos- model included the Holzbaur et al.29 wrap objects for sible, we chose to use moment arm data for the index the extrinsic tendons, and we created new wrap objects finger measured in vivo40,50,68 and in situ.4,5,10,14,19 for the intrinsic muscles that conformed to the bone However, measurements of moment arms alone cannot shape. be directly used to develop homeomorphic models because moment arms are indeterminate: many com- Moment Arms binations of origins and insertions, or paths, could result in the same moment arm. The purpose of this Experimentally measured values were used as ref- study was therefore to determine a set of muscle erence moment arms.3–5,14 More recent studies have attachment points for the tendons and intrinsic mus- measured moment arms for one muscle (FDS) using cles of the index finger. We focused on the question: more sophisticated techniques.42 However, we chose to can data-driven optimization find reasonable attach- base our model on datasets reporting both extrinsic ment sites for extrinsic tendons and intrinsic muscles? and intrinsic muscles to maintain consistency of source We hypothesized that Simulated Annealing33 could specimens and measurement techniques among mus- find muscle attachment points for extrinsic and cles. For the MCP joint, we extracted 10 data points intrinsic finger tendons and muscles, resulting in mo- (x: joint angles, y: moment arm values) from published ment arms that match