Motion capture of all degrees of freedom of the hand collected during performance of daily living activities remains challenging. Instrumented gloves are an attractive option because of their higher ease of use. However, subject-specific calibration of gloves is lengthy and has limitations for individuals with disabilities. Here, a calibration procedure is presented, consisting in the recording of just a simple hand position so as to allow capture of the kinematics of 16 hand joints during daily life activities even in case of severe injured hands. 'across-subject gains' were obtained by averaging the gains obtained from a detailed subject-specific calibration involving 44 registrations that was repeated three times on multiple days to 6 subjects. In additional 4 subjects, joint angles that resulted from applying the 'across-subject calibration' or the subject-specific calibration were compared. Global errors associated with the 'across-subject calibration' relative to the detailed, subjectspecific protocol were small (bias: 0.49º; precision: 4.45º) and comparable to those that resulted from repeating the detailed protocol with the same subject on multiple days (0.36º; 3.50º). Furthermore, in one subject, performance of the 'across-subject calibration' was directly compared to another fast calibration method, expressed relative to a videogrammetric protocol as a gold-standard, yielding better results.

Baseball pitching imposes a dangerous valgus load on the elbow that puts the joint at severe risk for injury. The goal of this study was to develop a musculoskeletal modeling approach to enable evaluation of muscle-tendon contributions to mitigating elbow injury risk in pitching. We implemented a forward dynamic simulation framework that used a scaled biomechanical model to reproduce a pitching motion recorded from a high school pitcher. The medial elbow muscles generated substantial, protective, varus elbow moments in our simulations. For our subject, the triceps generated large varus moments at the time of peak valgus loading; varus moments generated by the flexor digitorum superficialis were larger, but occurred later in the motion. Increasing muscle-tendon force output, either by augmenting parameters associated with strength and power or by increasing activation levels, decreased the load on the ulnar collateral ligament. Published methods have not previously quantified the biomechanics of elbow muscles during pitching. This simulation study represents a critical advancement in the study of baseball pitching and highlights the utility of simulation techniques in the study of this difficult problem.

The carpometacarpal (CMC) joints of the hand facilitate motion of the metacarpals and are critical for functional tasks, especially tasks involving precision grasping. Despite their importance, only limited data describing metacarpal kinematics exist. In this short communication, we quantified in vivo metacarpal kinematics from a single subject and used these data to develop the kinematic functions necessary to add rotational degrees of freedom at the CMC joints to a biomechanical model of the hand. Computed tomography (CT) was used to capture three-dimensional rotations of the metacarpal bones of the ring and little fingers of the subject in seven different static postures, chosen to position the fourth and fifth metacarpals throughout a functional range of motion. The CT images were manually segmented, yielding digital surface representations of the metacarpals in each posture. From the surfaces, principal axes of rotation were defined by calculating orthonormal bases of the surface vertices. The three-dimensional rotations of the fourth and fifth metacarpals were quantified in each posture about their principal axes, relative to a designated reference posture. For both metacarpals, ranges of rotations were computed about the principal axes across all seven postures. From the processed data, single axes and angles were calculated that were equivalent to the three dimensional ranges of motion. Finally, kinematic functions were defined that enabled modeling of the formation of a metacarpal arch by movement of the fourth and fifth CMC joints as one degree of freedom, coupled to a single generalized coordinate.

There has been a marked increase in the use of hand motion capture protocols in the past 20 yr. However, their absolute accuracies and precisions remain unclear. The purpose of this technical brief was to present a method for evaluating the accuracy and precision of the joint angles determined by a hand motion capture protocol using simultaneously collected static computed tomography (CT) images. The method consists of: (i) recording seven functional postures using both the motion capture protocol and a CT scanner; (ii) obtaining principal axes of the bones in each method; (iii) calculating the flexion angle at each joint for each method as the roll angle of the composite, sequential, roll-pitchyaw rotations relating the orientation of the distal bone to the proximal bone; and (iv) comparing corresponding joint angle measurements. For demonstration, we applied the method to a Cyberglove protocol. Accuracy and precision of the instrumentedglove protocol were calculated as the mean and standard deviation, respectively, of the differences between the angles determined from the Cyberglove output and the CT images across the seven postures. Implementation in one subject highlighted substantial errors, especially for the distal joints of the fingers. This technical note both clearly demonstrates the need for future work and introduces a solid, technical approach with the potential to improve the current state of such assessments in our field.