Human Hand Biomechanics and Bioinspiration

James Tigue, PhD Candidate

Human Hand Biomechanical Modeling

The goal of this research is to develop an all-inclusive musculoskeletal model for the human hand.  The complexities of the human hand interconnected tendon system make computational biomechanical simulation via popular platforms like OpenSim difficult. Using bond graph modeling techniques, a dynamic model of the human index finger and a Graphical User Interface for simulation were developed. The use of a bond graph framework results in an intuitive approach at dynamic equation derivation and allows for easy transitions between domains of biomechanics: muscle/tendon translation, joint rotation, cartesian motion, and interaction forces.

(a) The EM described as  Winslow’s rhombus with additional LUM. (b) Model of EM using interconnected translational springs in the interconnected Winslow’s rhombus configuration. Intermediate masses are included at intersections of springs to elevate differential algebraic loops. (c) The bond graph representation of EM model using capacitive elements (springs) and intermediate inertial elements.

Utah’s Anatomically-correct Robotic Testbed (UART)

Robots provide a unique platform for experimentation. Not only can we be inspired by biological systems to design and build Bio-inspired robots, but robots with a high degree of biological accuracy can provide insights for biology, Robotics-inspired biology. In order to study the human hand, Utah’s Anatomically-correct Robotic Testbed (UART) is actively being developed. Not only does the robotic hand facilitate investigations for biological design and control, but it provides a way to conduct rigorous testing that either cadavers or live human subjects are not capable of. The robotic testbeds can also highlight the limitations of models, like kinematic assumptions or representations of friction.












UART finger version 1 vs UART Hand Design


Hand Tendon Reconstructive Surgery

One interesting application of human hand biomechanics is hand tendon reconstructive surgery. The goal of this surgery is to restore functionality after trauma or neurological complications. One specific surgery is the flexor tendon repair surgery. One complication that can happen during this surgery is tendon shortening. Whether the shortening is due to tendon damage or delay in surgical intervention this shortening can result in flexion deformities and loss of range of motion. Current clinical understanding is limited to post-recovery observation which is clouded by issues of recovery. New methods for the direct investigation of tendon shortening’s effect are needed. Another surgery is FDS-opponensplasty. This surgery seeks to restore the thumb opposition motion after nerve damage by doing a tendon transfer from the FDS of the ring finger to the thumb. The routing of the tendon is typically based on trial and error, computational and robotic platforms could be used to investigate different routing paths or provide quantitative evidence for current methods.

We have received funding from the NIH: National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIH Award No. R21AR076269) to investigate the applications of the computational model and the robotic testbed on hand tendon reconstructive surgeries.

The specific aims of this proposal are:

  1. Expand the robotic testbed and model to include the thumb tendon system.
  2. Simulate reconstructive tendon surgery outcomes using the UART hand and computational model
  3. Conduct cadaver experimental validation and simulation of surgical outcomes

Current simulation of FDP tendon repair surgery and tendon shortening at BioRob 2020:

BioRob 2020 Conference Paper, Poster, and Presentation


  • J. A. Tigue, W. B. Rockwell, K. B. Foreman, S.A. Mascaro, 2020, “Simulating Tendon Shortening During Flexor Tendon Repair Surgery Using A Biomechanical Model and Robotic Testbed,” in 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob).
  • Tigue, J. King, R. Mascaro, S., 2020, Simultaneous Kinematic and Contact Force Modeling of a Human Finger Tendon System Using Bond Graphs and Robotic Validation,” ASME Journal of Dynamic Systems, Measurement, and Control, vol 147, no 3.
  • J. A. Tigue, S. A. Mascaro, 2019, “Calibration and Validation of Dynamic Model for Simulating Robotic Finger Kinematics and Contact Forces,” in Proceedings of the ASME 2019 Dynamic Systems and Control Conference.
  • J. A. Tigue, S. Harris, C. Anjewierden, and S. A. Mascaro, 2017, “Validation of Fingertip Force and Finger Pose in the UART Finger and Bond Graph Tendon Model During Surface Contact,” in Proceedings of the ASME 2017 Dynamic Systems and Control Conference.

Super Coiled Polymer (SCP) Actuators

Brady Foard, Undergraduate

The goal of this project is to develop super-coiled polymer (SCP) actuators into artificial robotic muscles. First, a methodology for manufacturing copper-wound monofilament SCPs was developed and investigated the manufacturing parameters in terms of muscle strain, contraction time, and efficiency. Currently, a water-cooled system is being developed to provide active expansion and decrease cooling times to allow for faster control.


  • Matthew E. Padgett and Stephen A. Mascaro “Investigation of manufacturing parameters for copper-wound super-coiled polymer actuators”, Proc. SPIE 10966, Electroactive Polymer Actuators and Devices (EAPAD) XXI, 109660R (13 March 2019);

Past Projects


Optimal Control of Actuator Arrays with Electric and Thermofluidic Inputs

Mohammadreza Mollaei,

The objective of this research is to characterize the performance of an array of Shape Memory Alloy (SMA) actuators with multiple energy domain inputs. The SMA actuators will be embedded in a vascular network that can provide both electric and thermofluidic energy. The vascular system delivers and removes thermal energy from compact muscle like actuators, allowing them to be integrated into large DOF systems. This research is anticipated to advance the capabilities of a variety of robotic systems such as prosthetics, exoskeletons, haptic devices and biomimicing robots. Specifically, we propose two distinct objectives: 1) to characterize and optimize the performance of a single wet SMA actuator using electric and thermofluidic inputs, 2) to characterize and optimize the performance of these wet SMA actuators in bundles/arrays where different combinations of actuators in the array can be addressed with different inputs in order to maximize a combination of speed and energy consumption. We plan to accomplish this through several research tasks including thermomechanical and computational fluid dynamic modeling of wet SMA actuators, and analysis of intelligent algorithms for optimal multi-input control of actuator arrays. This research sponsored by an NSF Grant.