Mapping Together Kinetic and Kinematic Abilities of the Hand

Quantifying Hand Strength and Isometric Pinch Individuation Using a Flexible Pressure Sensor Grid

Modulating force between the thumb and another digit, or isometric pinch individuation, is critical for daily tasks and can be impaired due to central or peripheral nervous system injury. Because surgical and rehabilitative efforts often focus on regaining this dexterous ability, we need to be able to consistently quantify pinch individuation across time and facilities. Currently, a standardized metric for such an assessment does not exist. Therefore, we tested whether we could use a commercially available flexible pressure sensor grid (Tekscan F-Socket [Tekscan Inc., Norwood, MA, USA]) to repeatedly measure isometric pinch individuation and maximum voluntary contraction (MVC) in twenty right-handed healthy volunteers at two visits. We developed a novel equation informed by the prior literature to calculate isometric individuation scores that quantified percentage of force on the grid generated by the indicated digit. MVC intra-class correlation coefficients (ICCs) for the left and right hands were 0.86 (p < 0.0001) and 0.88 (p < 0.0001), respectively, suggesting MVC measurements were consistent over time. However, individuation score ICCs, were poorer (left index ICC 0.41, p = 0.28; right index ICC -0.02, p = 0.51), indicating that this protocol did not provide a sufficiently repeatable individuation assessment. These data support the need to develop novel platforms specifically for repeatable and objective isometric hand dexterity assessments.

Simulating finger-tip force using two common contact models: Hunt-Crossley and elastic foundation

Musculoskeletal models of the hand rarely include fingerpad contact mechanics, thereby limiting our ability to simulate and examine hand-object interactions. The objective of this study was to evaluate whether two common contact models (Hunt-Crossley and Elastic Foundation) can accurately represent the fingerpad. Two musculoskeletal models of the index finger were created by adding fingerpad contact geometry using either the Hunt-Crossley or Elastic Foundation contact models. Key contact parameters (target force, contact area, and stiffness) were then systematically varied through 432 forward dynamic simulations to examine how these parameters influenced estimation of finger-tip forces. Across all simulations, variation in target force, contact area, and stiffness parameters impacted the computation time required to complete the simulations and the accuracy of the predicted finger-tip force. Computation time was over three times longer in simulations with high versus low values of contact area and stiffness in both contact models. For both contact models, larger contact area and stiffness values resulted in simulations that more closely predicted target force. However, across all simulations, the Hunt-Crossley model produced a greater proportion of accurate finger-tip force simulations than the Elastic Foundation model, suggesting that the Hunt-Crossley contact model may be preferable for modeling the fingerpad. Overall, our study demonstrates how the Hunt-Crossley and Elastic Foundation contact models behave in low-force biomechanical scenarios, such as those experienced during hand-object manipulation, and provides a foundation for incorporating contact mechanics into musculoskeletal models of the hand.