Francisco J. Valero-Cuevas, Ph.D.
NCMRR Symposium. January 4, 2001
I. Introduction
- Motivation
- Hand disabilities often result in a disproportionate reduction in our ability to interact with the physical world and each other.
- The complexity of the hand makes it difficult to characterize the biomechanical consequences of hand disabilities and rehabilitation strategies.
- Anatomy of forefinger
- Utility of hand models
- By describing individual anatomical structures and the interactions among them, computer models can predict the biomechanical consequences of hand disabilities and rehabilitation strategies.
- Because of the complexity of the hand, most models are of individual digits, not of whole hands.
- Research paradigm for modeling of the hand/digits
- Restoring pinch function
- Brief overview of hand models
- Because of the versatility of the hand, a biomechanical model that encompasses all aspects of hand function is not yet available (and is perhaps not feasible).
- Instead, models focus on specific aspects of hand/finger function such as motion and force production for prehension.
- Non-clinically oriented models
- 2D motion of single fingers:
Leijnse et al ('92-'97): The effect of tendon excursion on finger motion.
Harding et al ('93): Motion of the fingers during piano playing.
- 3D motion of multiple fingers:
Buchholz & Armstrong ('92): Wrapping grasps around objects.
- 2D force production of single fingers:
Lee and Rim ('91 & '92): maximal grip force.
- 3D force production of multiple fingers:
Chao et al ('76 & '78): Joint and finger forces.
- Clinically oriented models
- An, Chao, Linscheid, Cooney et al at Mayo Clinic ('79-'85): 3D Joint and finger forces in the normal and abnormal hand.
- Spoor ('83): 2D force production in the paretic finger.
- Thompson, Giurintano, Hollister, Brand, Buford et al ('88-'95): 3D finger and thumb models for tendon transfers and muscle forces.
- To become part of clinical practice:
- Modeling of the hand must:
Have the necessary level of anatomical detail (e.g., complete musculature).
Consider the neuromuscular aspects of control.
Include experimental validation.
- Modeling Challenges
II. Three clinical research questions being pursued using mechanics-based models
First question
What biomechanical disability can be expected following paralysis of specific muscles?
How should musculotendons be re-routed to maximize post-operative fingertip force?
How does the CNS dynamically control the redundant musculature of the digits?
- Forefinger model case study
- 3D model Includes all 7 muscles & adjustable extensor mechanism
- Segments and joints Moment arms Extensor mechanism
- Model predictions
- Measured fingertip force
- Simultaneous fine-wire EMG recordings
- The model can predict the coordination patterns measured 3D force production
- How to validate this prediction of weakness in pinch?
- Developed hybrid cadaveric/optimization model to avoid the uncertainty in the anatomical assumptions made in classical computer models.
- Apply known tensions to each tendon, measure output at fingertip Maximal predicted force
- First finding
- Somewhat counter-intuitively, the paralysis of extensor muscles of the forefinger weakens pinch force.
- Thus, biomechanical modeling contributes to our understanding of the complex causes of disability.
Second question
What biomechanical disability can be expected following paralysis of specific muscles?
How should musculotendons be re-routed to maximize post-operative fingertip force?
How does the CNS dynamically control the redundant musculature of the digits?
Biomechanical consequences of ulnar palsy and its treatment with tendon transfers - Second finding
- Shifting by a few millimeters the insertion point of tendons transferred to prevent claw deformity in low ulnar palsy is predicted to greatly enhance fingertip forces.
- Thus, biomechanical modeling can be used to improve the effectiveness of treatment strategies.
Third question
What biomechanical disability can be expected following paralysis of specific muscles?
How should musculotendons be re-routed to maximize post-operative fingertip force?
How does the CNS dynamically control the redundant musculature of the digits?
- When producing sub-maximal forces:
How do we select and implement coordination patterns from a large pool of valid alternatives in real-time? Hypothesis: the coordination pattern for the largest expected force is scaled to produce lower forces.
- Modeling muscle redundancy
- Predicted coordination patterns capable of producing 50% of maximal palmar force
- Coordination patterns used for maximal and sub-maximal force
- Coordination patterns used for different fingertip force magnitudes
- Third finding
- The CNS seems to simplify the control of redundant musculature by scaling whole muscle coordination patterns.
- Thus, we can design surgeries to produce large forces knowing that the CNS can use a similar coordination pattern to produce post-operative forces of high and low magnitude.
III. Current research directions
- To create a computer model to simulate dynamic interactions among multiple digits.
- To design, compare and validate alternative surgical treatments and rehabilitation strategies.
- To develop methods to evaluate hand function.
- To understand the control of manipulation.
IV. Future work: Modeling unaffected and disabled manipulation ability
V. Conclusion
- Mechanics-based modeling can be combined with neurophysiological and clinical principles to effectively describe the biomechanical consequences of hand disabilities and rehabilitation strategies.
Thank you