Melissa Daly

Benchmarking of dynamic simulation predictions in two software platforms using an upper limb musculoskeletal model

Several opensource or commercially available software platforms are widely used to develop dynamic simulations of movement. While computational approaches are conceptually similar across platforms, technical differences in implementation may influence output. We present a new upper limb dynamic model as a tool to evaluate potential differences in predictive behavior between platforms. We evaluated to what extent differences in technical implementations in popular simulation software environments result in differences in kinematic predictions for single and multijoint movements using EMG- and optimization-based approaches for deriving control signals. We illustrate the benchmarking comparison using SIMM–Dynamics Pipeline–SD/Fast and OpenSim platforms. The most substantial divergence results from differences in muscle model and actuator paths. This model is a valuable resource and is available for download by other researchers. The model, data, and simulation results presented here can be used by future researchers to benchmark other software platforms and software upgrades for these two platforms.

Characterizing upper limb muscle volume and strength in older adults: A comparison with young adults

Aging is associated with the loss of muscle volume (MV) and force leading to difficulties with activities of daily living. However, the relationship between upper limb MV and joint strength has not been characterized for older adults. Quantifying this relationship may help our understanding of the functional declines of the upper limb that older adults experience. Our objective was to assess the relationship between upper limb MV and maximal isometric joint moment-generating capacity (IJM) in a single cohort of healthy older adults (age ≥ 65 years) for 6 major functional groups (32 muscles). MV was determined from MRI for 18 participants (75.1±4.3 years). IJM at the shoulder (abduction/adduction), elbow (flexion/extension), and wrist (flexion/extension) was measured. MV and IJM measurements were compared to previous reports for young adults (28.6±4.5 years). On average older adults had 16.5% less total upper limb MV compared to young adults. Additionally, older adult wrist extensors composed a significantly increased percentage of upper limb MV. Older adult IJM was reduced across all joints, with significant differences for shoulder abductors (p<0.0001), adductors (p=0.01), and wrist flexors (p<0.0001). Young adults were strongest at the shoulder, which was not the case for older adults. In older adults, 40.6% of the variation in IJM was accounted for by MV changes (p≤0.027), compared to 81.0% in young adults. We conclude that for older adults, MV and IJM are, on average, reduced but the significant linear relationship between MV and IJM is maintained. These results suggest that older adult MV and IJM cannot be simply scaled from young adults.

Computer Simulation of Nerve Transfer Strategies for Restoring Shoulder Function After Adult C5 and C6 Root Avulsion Injuries

PURPOSE Functional ability after nerve transfer for upper brachial plexus injuries relies on both the function and magnitude of force recovery of targeted muscles. Following nerve transfers targeting either the axillary nerve, suprascapular nerve, or both, it is unclear whether functional ability is restored in the face of limited muscle force recovery. METHODS We used a computer model to simulate flexing the elbow while maintaining a functional shoulder posture for 3 nerve transfer scenarios. We assessed the minimum restored force capacity necessary to perform the task, the associated compensations by neighboring muscles, and the effect of altered muscle coordination on movement effort. RESULTS The minimum force restored by the axillary, suprascapular, and combined nerve transfers that was required for the model to simulate the desired movement was 25%, 40%, and 15% of the unimpaired muscle force capacity, respectively. When the deltoid was paralyzed, the infraspinatus and subscapularis muscles generated higher shoulder abduction moments to compensate for deltoid weakness. For all scenarios, movement effort increased as restored force capacity decreased. CONCLUSIONS Combined axillary and suprascapular nerve transfer required the least restored force capacity to perform the desired elbow flexion task, whereas single suprascapular nerve transfer required the most restored force capacity to perform the same task. Although compensation mechanisms allowed all scenarios to perform the desired movement despite weakened shoulder muscles, compensation increased movement effort. Dynamic simulations allowed independent evaluation of the effect of restored force capacity on functional outcome in a way that is not possible experimentally. CLINICAL RELEVANCE Simultaneous nerve transfer to suprascapular and axillary nerves yields the best simulated biomechanical outcome for lower magnitudes of muscle force recovery in this computer model. Axillary nerve transfer performs nearly as well as the combined transfer, whereas suprascapular nerve transfer is more sensitive to the magnitude of reinnervation and is therefore avoided.

Dynamic Simulation of Upper Limb Movement in Two Software Platforms

There are several opensource or commercially available software platforms widely used for the development of dynamic simulations of movement. While computational approaches to calculating the dynamics of a musculoskeletal model are conceptually similar across platforms, differences in implementation may influence simulation output. To understand predictions made using simulation, it is important to understand differences that may result from the choice of model or platform. Our aims were to 1) develop a musculoskeletal model of the upper limb suitable for dynamic simulation and 2) evaluate the influence of the choice between SIMM-SD/Fast and OpenSim simulation platforms on gravity- and EMG-driven simulations of movement.Copyright

A Method to Discriminate Pulmonary Contusion Severity Through Analysis of Hounsfield Unit Frequency

This study presents a novel approach for the quantification and classification of pulmonary contusion (PC). PC is a common thoracic injury, affecting up to 25% of patients sustaining blunt chest trauma. [1] Contusion volume at the time of hospitalization has been shown to be an independent predictor for the development of Acute Respiratory Distress Syndrome (ARDS), with the risk of ARDS increasing sharply with PC in excess of 20% by volume. [1] Despite the frequency of the injury and strong positive correlation between contusion volume and outcome, there are relatively few contusion quantification methods in the current literature. One such study utilized chest x-ray film to score PC according the amount of lung appearing to be damaged. [2] The study concluded that despite the limitations in using chest x-rays, a PC scoring system may be of value in determining the need for ventilator assistance and predicting outcome. A potentially more accurate approach to quantifying the severity of PC is through the use of computed tomography (CT) chest scans. CT is the preferred modality for obtaining volumetric pulmonary contusion data since the complete three-dimensional lung anatomy is captured. In this work a semi-automated approach is used to analyze PC in an isolated model of lung contusion in the rat. [3, 4] The CT-based approach enables the PC to be precisely quantified as the lesion progresses in time. The technique distinguishes the severity of the contusion by analyzing the composition of bands in the Hounsfield Unit (HU) range of lung image masks.Copyright