1
|
McFarland DC, Binder-Markey BI, Nichols JA, Wohlman SJ, de Bruin M, Murray WM. A Musculoskeletal Model of the Hand and Wrist Capable of Simulating Functional Tasks. IEEE Trans Biomed Eng 2023; 70:1424-1435. [PMID: 36301780 PMCID: PMC10650739 DOI: 10.1109/tbme.2022.3217722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
OBJECTIVE The purpose of this work was to develop an open-source musculoskeletal model of the hand and wrist and to evaluate its performance during simulations of functional tasks. METHODS The current model was developed by adapting and expanding upon existing models. An optimal control theory framework that combines forward-dynamics simulations with a simulated-annealing optimization was used to simulate maximum grip and pinch force. Active and passive hand opening were simulated to evaluate coordinated kinematic hand movements. RESULTS The model's maximum grip force production matched experimental measures of grip force, force distribution amongst the digits, and displayed sensitivity to wrist flexion. Simulated lateral pinch strength replicated in vivo palmar pinch strength data. Additionally, predicted activations for 7 of 8 muscles fell within variability of EMG data during palmar pinch. The active and passive hand opening simulations predicted reasonable activations and demonstrated passive motion mimicking tenodesis, respectively. CONCLUSION This work advances simulation capabilities of hand and wrist models and provides a foundation for future work to build upon. SIGNIFICANCE This is the first open-source musculoskeletal model of the hand and wrist to be implemented during both functional kinetic and kinematic tasks. We provide a novel simulation framework to predict maximal grip and pinch force which can be used to evaluate how potential surgical and rehabilitation interventions influence these functional outcomes while requiring minimal experimental data.
Collapse
|
2
|
Lee JH, Asakawa DS, Dennerlein JT, Jindrich DL. Correction: Finger Muscle Attachments for an OpenSim Upper-Extremity Model. PLoS One 2022; 17:e0267620. [PMID: 35442988 PMCID: PMC9020702 DOI: 10.1371/journal.pone.0267620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
|
3
|
Saito T, Ogihara N, Takei T, Seki K. Musculoskeletal Modeling and Inverse Dynamic Analysis of Precision Grip in the Japanese Macaque. Front Syst Neurosci 2021; 15:774596. [PMID: 34955770 PMCID: PMC8693514 DOI: 10.3389/fnsys.2021.774596] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Accepted: 11/12/2021] [Indexed: 12/01/2022] Open
Abstract
Toward clarifying the biomechanics and neural mechanisms underlying coordinated control of the complex hand musculoskeletal system, we constructed an anatomically based musculoskeletal model of the Japanese macaque (Macaca fuscata) hand, and then estimated the muscle force of all the hand muscles during a precision grip task using inverse dynamic calculation. The musculoskeletal model was constructed from a computed tomography scan of one adult male macaque cadaver. The hand skeleton was modeled as a chain of rigid links connected by revolute joints. The path of each muscle was defined as a series of points connected by line segments. Using this anatomical model and a model-based matching technique, we constructed 3D hand kinematics during the precision grip task from five simultaneous video recordings. Specifically, we collected electromyographic and kinematic data from one adult male Japanese macaque during the precision grip task and two sequences of the precision grip task were analyzed based on inverse dynamics. Our estimated muscular force patterns were generally in agreement with simultaneously measured electromyographic data. Direct measurement of muscle activations for all the muscles involved in the precision grip task is not feasible, but the present inverse dynamic approach allows estimation for all the hand muscles. Although some methodological limitations certainly exist, the constructed model analysis framework has potential in clarifying the biomechanics and neural control of manual dexterity in macaques and humans.
Collapse
Affiliation(s)
- Tsuyoshi Saito
- Department of Mechanical Engineering, Faculty of Science and Technology, Keio University, Yokohama, Japan
| | - Naomichi Ogihara
- Department of Mechanical Engineering, Faculty of Science and Technology, Keio University, Yokohama, Japan.,Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo, Japan
| | - Tomohiko Takei
- Brain Science Institute, Tamagawa University, Tokyo, Japan
| | - Kazuhiko Seki
- Department of Neurophysiology, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan
| |
Collapse
|
4
|
Melzner M, Engelhardt L, Simon U, Dendorfer S. Electromyography Based Validation of a Musculoskeletal Hand Model. J Biomech Eng 2021; 144:1115820. [PMID: 34386814 DOI: 10.1115/1.4052115] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Indexed: 11/08/2022]
Abstract
Regarding the prevention of injuries and rehabilitation of the human hand, musculoskeletal simulations using an inverse dynamics approach allow for insights of the muscle recruitment and thus acting forces on the hand. Currently, several hand models from various research groups are in use, which are mainly validated by the comparison of numerical and anatomical moment arms. In contrast to this validation and model-building technique by cadaver studies, the aim of the present study is to further validate a recently published hand model [1] by analyzing numerically calculated muscle activities in comparison to experimentally measured electromyographical signals of the muscles. Therefore, the electromyographical signals of 10 hand muscles of five test subjects performing seven different hand movements were measured. The kinematics of these tasks were used as input for the hand model, and the numerical muscle activities were computed. To analyze the relationship between simulated and measured activities, the time difference of the muscle on- and off-set points were calculated, which resulted in a mean on- and off-set time difference of 0.58 s between the experimental data and the model. The largest differences were detected for movements that mainly addressed the wrist. One major issue comparing simulated and measured muscle activities of the hand is cross-talk. Nevertheless, the results show that the hand model fits the experiment quite accurately despite some limitations and is a further step towards patient-specific modelling of the upper extremity.
Collapse
Affiliation(s)
- Maximilian Melzner
- Laboratory for Biomechanics, OTH Regensburg, Germany and Regensburg Center of Biomedical Engineering, Germany, Galgenbergstr. 30, 93053 Regensburg, Germany
| | - Lucas Engelhardt
- Scientific Computing Centre Ulm (UZWR), Ulm University, Germany and Institute of Orthopaedic Research and Biomechanics, Centre for Trauma Research Ulm, Germany, Helmholtzstr. 20, 89081 Ulm, Germany
| | - Ulrich Simon
- Scientific Computing Centre Ulm (UZWR), Ulm University, Germany, Helmholtzstr. 20, 89081 Ulm, Germany
| | - Sebastian Dendorfer
- Laboratory for Biomechanics, OTH Regensburg, Germany and Regensburg Center of Biomedical Engineering, Germany, Laboratory for Biomechanics, OTH Regensburg, Galgenbergstr. 30, 93053 Regensburg, Germany
| |
Collapse
|
5
|
Engelhardt L, Melzner M, Havelkova L, Fiala P, Christen P, Dendorfer S, Simon U. A new musculoskeletal AnyBody™ detailed hand model. Comput Methods Biomech Biomed Engin 2020; 24:1-11. [PMID: 33300810 DOI: 10.1080/10255842.2020.1851367] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 10/13/2020] [Accepted: 11/11/2020] [Indexed: 10/22/2022]
Abstract
Musculoskeletal research questions regarding the prevention or rehabilitation of the hand can be addressed using inverse dynamics simulations when experiments are not possible. To date, no complete human hand model implemented in a holistic human body model has been fully developed. The aim of this work was to develop, implement, and validate a fully detailed hand model using the AnyBody Modelling System (AMS) (AnyBody, Aalborg, Denmark). To achieve this, a consistent multiple cadaver dataset, including all extrinsic and intrinsic muscles, served as a basis. Various obstacle methods were implemented to obtain with the correct alignment of the muscle paths together with the full range of motion of the fingers. These included tori, cylinders, and spherical ellipsoids. The origin points of the lumbrical muscles within the tendon of the flexor digitorum profundus added a unique feature to the model. Furthermore, the possibility of an entire patient-specific scaling based on the hand length and width were implemented in the model. For model validation, experimental datasets from the literature were used, which included the comparison of numerically calculated moment arms of the wrist, thumb, and index finger muscles. In general, the results displayed good comparability of the model and experimental data. However, the extrinsic muscles showed higher accordance than the intrinsic ones. Nevertheless, the results showed, that the proposed developed inverse dynamics hand model offers opportunities in a broad field of applications, where the muscles and joint forces of the forearm play a crucial role.
Collapse
Affiliation(s)
- Lucas Engelhardt
- Scientific Computing Centre Ulm (UZWR), Ulm University, Ulm, Germany
| | - Maximilian Melzner
- Laboratory for Biomechanics, Ostbayerische Technische Hochschule (OTH) Regensburg, Regensburg, Germany
- Regensburg Center of Biomedical Engineering, OTH and University Regensburg, Regensburg, Germany
| | - Linda Havelkova
- New Technologies Research Centre, University of West Bohemia (UWB), Plzen, Czech Republic
| | - Pavel Fiala
- Department of Anatomy, Faculty of Medicine in Pilsen, Charles University, Plzen, Czech Republic
| | - Patrik Christen
- Institute for Biomechanics, ETH Zurich, Zurich, Switzerland
- Institute for Information Systems, University of Applied Sciences and Arts Northwestern, Brugg, Switzerland
| | - Sebastian Dendorfer
- Laboratory for Biomechanics, Ostbayerische Technische Hochschule (OTH) Regensburg, Regensburg, Germany
- Regensburg Center of Biomedical Engineering, OTH and University Regensburg, Regensburg, Germany
| | - Ulrich Simon
- Scientific Computing Centre Ulm (UZWR), Ulm University, Ulm, Germany
| |
Collapse
|
6
|
Metcalf CD, Phillips C, Forrester A, Glodowski J, Simpson K, Everitt C, Darekar A, King L, Warwick D, Dickinson AS. Quantifying Soft Tissue Artefacts and Imaging Variability in Motion Capture of the Fingers. Ann Biomed Eng 2020; 48:1551-1561. [PMID: 32076882 PMCID: PMC7154021 DOI: 10.1007/s10439-020-02476-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 02/05/2020] [Indexed: 10/29/2022]
Abstract
This study assessed the accuracy of marker-based kinematic analysis of the fingers, considering soft tissue artefacts (STA) and marker imaging uncertainty. We collected CT images of the hand from healthy volunteers with fingers in full extension, mid- and full-flexion, including motion capture markers. Bones and markers were segmented and meshed. The bone meshes for each volunteer's scans were aligned using the proximal phalanx to study the proximal interphalangeal joint (PIP), and using the middle phalanx to study the distal interphalangeal joint (DIP). The angle changes between positions were extracted. The HAWK protocol was used to calculate PIP and DIP joint flexion angles in each position based on the marker centroids. Finally the marker locations were 'corrected' relative to the underlying bones, and the flexion angles recalculated. Static and dynamic marker imaging uncertainty was evaluated using a wand. A strong positive correlation was observed between marker- and CT-based joint angle changes with 0.980 and 0.892 regression slopes for PIP and DIP, respectively, and Root Mean Squared Errors below 4°. Notably for the PIP joint, correlation was worsened by STA correction. The 95% imaging uncertainty interval was < ± 1° for joints, and < ± 0.25 mm for segment lengths. In summary, the HAWK marker set's accuracy was characterised for finger joint flexion angle changes in a small group of healthy individuals and static poses, and was found to benefit from skin movements during flexion.
Collapse
Affiliation(s)
- C D Metcalf
- Faculty of Environmental & Life Sciences, University of Southampton, Southampton, UK
| | - C Phillips
- Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, UK
| | - A Forrester
- Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, UK
| | - J Glodowski
- Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, UK
| | - K Simpson
- Faculty of Environmental & Life Sciences, University of Southampton, Southampton, UK
| | - C Everitt
- University Hospital Southampton, Southampton, UK
| | - A Darekar
- University Hospital Southampton, Southampton, UK
| | - L King
- University Hospital Southampton, Southampton, UK
| | - D Warwick
- University Hospital Southampton, Southampton, UK
| | - A S Dickinson
- Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, UK.
| |
Collapse
|
7
|
Ma’touq J, Hu T, Haddadin S. A validated combined musculotendon path and muscle-joint kinematics model for the human hand. Comput Methods Biomech Biomed Engin 2019; 22:727-739. [DOI: 10.1080/10255842.2019.1588256] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Affiliation(s)
- Jumana Ma’touq
- Institute of Automatic Control, Gottfried Wilhelm Leibniz Universität Hannover, Hannover, Germany
| | - Tingli Hu
- Munich School of Robotics and Machine Intelligence, Technical University of Munich, Munich, Germany
- Chair of Robotics Science and Systems Intelligence, Technical University of Munich, Munich, Germany
| | - Sami Haddadin
- Munich School of Robotics and Machine Intelligence, Technical University of Munich, Munich, Germany
- Chair of Robotics Science and Systems Intelligence, Technical University of Munich, Munich, Germany
| |
Collapse
|
8
|
Mirakhorlo M, Van Beek N, Wesseling M, Maas H, Veeger HEJ, Jonkers I. A musculoskeletal model of the hand and wrist: model definition and evaluation. Comput Methods Biomech Biomed Engin 2018; 21:548-557. [DOI: 10.1080/10255842.2018.1490952] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Affiliation(s)
- M. Mirakhorlo
- Department of Human Movement Sciences, VU University, Amsterdam, the Netherlands
| | - N. Van Beek
- Department of Human Movement Sciences, VU University, Amsterdam, the Netherlands
| | - M. Wesseling
- Department of Human Movement Sciences, KU Leuven, Leuven, Belgium
| | - H. Maas
- Department of Human Movement Sciences, VU University, Amsterdam, the Netherlands
| | - H. E. J. Veeger
- Department of Human Movement Sciences, VU University, Amsterdam, the Netherlands
- Department of Biomechanical Engineering, Delft University of Technology, Delft, the Netherlands
| | - I. Jonkers
- Department of Human Movement Sciences, KU Leuven, Leuven, Belgium
| |
Collapse
|
9
|
MacIntosh AR, Keir PJ. An open-source model and solution method to predict co-contraction in the finger. Comput Methods Biomech Biomed Engin 2017; 20:1373-1381. [DOI: 10.1080/10255842.2017.1364732] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
| | - Peter J. Keir
- Department of Kinesiology, McMaster University, Hamilton, Canada
| |
Collapse
|
10
|
Synek A, Pahr DH. The effect of the extensor mechanism on maximum isometric fingertip forces: A numerical study on the index finger. J Biomech 2016; 49:3423-3429. [PMID: 27653376 DOI: 10.1016/j.jbiomech.2016.09.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2016] [Revised: 08/29/2016] [Accepted: 09/07/2016] [Indexed: 11/15/2022]
Abstract
The extensor mechanism is a tendinous network connecting intrinsic and extrinsic muscles of the finger and its function has not yet been fully understood. The goal of this study was to assess the effect of the extensor mechanism on the maximum isometric fingertip forces - a parameter which is essential for grasping. For this purpose, maximum fingertip forces in all directions (i.e. feasible force sets) of two musculoskeletal models of the index finger were compared: the wEM model included a full representation of the extensor mechanism, whereas in the noEM model the extensor mechanism was replaced by a single extensor tendon without connectivity to intrinsic muscles. The feasible force sets were computed in the flexion-extension plane for nine postures. Forces in four predefined directions (palmar, proximal, dorsal, and distal), and the peak resultant forces were evaluated. Averaged forces in all four predefined directions were considerably larger in the wEM model (+187.6%). However, peak resultant forces were slightly lower in the wEM model (-4.3% on average). The general advantage of the wEM model could be explained by co-contraction of intrinsic and extrinsic extensor muscles which allowed reaching larger activation levels of the extrinsic flexors. Only within a narrow range of force directions the co-contraction of intrinsic muscles limited the fingertip forces and lead to lower peak resultant forces in the wEM model. Rather than maximizing peak resultant forces, it appears that the extensor mechanism is a sophisticated tool for increasing maximum fingertip forces over a broad range of postures and force directions - making the finger more versatile during grasping.
Collapse
Affiliation(s)
- A Synek
- Institute of Lightweight Design and Structural Biomechanics, Vienna University of Technology, Getreidemarkt 9, 1060 Vienna, Austria.
| | - D H Pahr
- Institute of Lightweight Design and Structural Biomechanics, Vienna University of Technology, Getreidemarkt 9, 1060 Vienna, Austria
| |
Collapse
|
11
|
Mirakhorlo M, Visser JMA, Goislard de Monsabert BAAX, van der Helm FCT, Maas H, Veeger HEJ. Anatomical parameters for musculoskeletal modeling of the hand and wrist. Int Biomech 2016. [DOI: 10.1080/23335432.2016.1191373] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
Affiliation(s)
- Mojtaba Mirakhorlo
- Faculty of Behavioral and Movement Sciences, Move Research Institute, VU University, Amsterdam, The Netherlands
| | - Judith M. A. Visser
- Faculty of Health, Nutrition and Sport, The Hague University of Applied Sciences, The Hague, The Netherlands
| | | | - F. C. T. van der Helm
- Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands
| | - H. Maas
- Faculty of Behavioral and Movement Sciences, Move Research Institute, VU University, Amsterdam, The Netherlands
| | - H. E. J. Veeger
- Faculty of Behavioral and Movement Sciences, Move Research Institute, VU University, Amsterdam, The Netherlands
- Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands
| |
Collapse
|