Subject-specific musculoskeletal models of the lower limbs for the prediction of skeletal loads during motion

The determination of skeletal loading conditions in vivo and their relationship to the health of bone tissues, remain an open question. Computational modeling of the musculoskeletal system is the only practicable method providing a valuable approach to muscle and joint loading analyses, although crucial shortcomings limit the translation process of computational methods into the orthopedic and neurological practice. A growing attention focused on subject-specific modeling, particularly when pathological musculoskeletal conditions need to be studied. Nevertheless, subject-specific data cannot be always collected in the research and clinical practice, and there is a lack of efficient methods and frameworks for building models and incorporating them in simulations of motion. The overall aim of the present PhD thesis was to introduce improvements to the state-of-the-art musculoskeletal modeling for the prediction of physiological muscle and joint loads during motion. A threefold goal was articulated as follows: (i) develop state-of-the art subject-specific models and analyze skeletal load predictions; (ii) analyze the sensitivity of model predictions to relevant musculotendon model parameters and kinematic uncertainties; (iii) design an efficient software framework simplifying the effort-intensive phases of subject-specific modeling pre-processing. The first goal underlined the relevance of subject-specific musculoskeletal modeling to determine physiological skeletal loads during gait, corroborating the choice of full subject-specific modeling for the analyses of pathological conditions. The second goal characterized the sensitivity of skeletal load predictions to major musculotendon parameters and kinematic uncertainties, and robust probabilistic methods were applied for methodological and clinical purposes. The last goal created an efficient software framework for subject-specific modeling and simulation, which is practical, user friendly and effort effective. Future research development aims at the implementation of more accurate models describing lower-limb joint mechanics and musculotendon paths, and the assessment of an overall scenario of the crucial model parameters affecting the skeletal load predictions through probabilistic modeling.

"Influence of lower-limb joint models on subject-specific musculoskeletal model predictions during gait" ( "modelli muscoloscheletrici personalizzati dell'arto inferiore: Analisi dell'effetto della modellazione dei giunti sulla predizione dei carichi agenti sul sistema scheletrico durante il cammino").

The aim of the present thesis was to investigate the influence of lower-limb joint models on musculoskeletal model predictions during gait. We started our analysis by using a baseline model, i.e., the state-of-the-art lower-limb model (spherical joint at the hip and hinge joints at the knee and ankle) created from MRI of a healthy subject in the Medical Technology Laboratory of the Rizzoli Orthopaedic Institute. We varied the models of knee and ankle joints, including: knee- and ankle joints with mean instantaneous axis of rotation, universal joint at the ankle, scaled-generic-derived planar knee, subject-specific planar knee model, subject-specific planar ankle model, spherical knee, spherical ankle. The joint model combinations corresponding to 10 musculoskeletal models were implemented into a typical inverse dynamics problem, including inverse kinematics, inverse dynamics, static optimization and joint reaction analysis algorithms solved using the OpenSim software to calculate joint angles, joint moments, muscle forces and activations, joint reaction forces during 5 walking trials. The predicted muscle activations were qualitatively compared to experimental EMG, to evaluate the accuracy of model predictions. Planar joint at the knee, universal joint at the ankle and spherical joints at the knee and at the ankle produced appreciable variations in model predictions during gait trials. The planar knee joint model reduced the discrepancy between the predicted activation of the Rectus Femoris and the EMG (with respect to the baseline model), and the reduced peak knee reaction force was considered more accurate. The use of the universal joint, with the introduction of the subtalar joint, worsened the muscle activation agreement with the EMG, and increased ankle and knee reaction forces were predicted. The spherical joints, in particular at the knee, worsened the muscle activation agreement with the EMG. A substantial increase of joint reaction forces at all joints was predicted despite of the good agreement in joint kinematics with those of the baseline model. The introduction of the universal joint had a negative effect on the model predictions. The cause of this discrepancy is likely to be found in the definition of the subtalar joint and thus, in the particular subject’s anthropometry, used to create the model and define the joint pose. We concluded that the implementation of complex joint models do not have marked effects on the joint reaction forces during gait. Computed results were similar in magnitude and in pattern to those reported in literature. Nonetheless, the introduction of planar joint model at the knee had positive effect upon the predictions, while the use of spherical joint at the knee and/or at the ankle is absolutely unadvisable, because it predicted unrealistic joint reaction forces.

Intra-subject variability in attention-deficit hyperactivity disorder

BACKGROUND: This study is based on a comprehensive survey of the neuropsychological attention-deficit hyperactivity disorder (ADHD) literature and presents the first psychometric analyses of different parameters of intra-subject variability (ISV) in patients with ADHD compared to healthy controls, using the Continuous Performance Test, a Go-NoGo task, a Stop Signal Task, as well as N-back tasks. METHODS: Data of 57 patients with ADHD and 53 age- and gender-matched controls were available for statistical analysis. Different parameters were used to describe central tendency (arithmetic mean, median), dispersion (standard deviation, coefficient of variation, consecutive variance), and shape (skewness, excess) of reaction time distributions, as well as errors (commissions and omissions). RESULTS: Group comparisons revealed by far the strongest effect sizes for measures of dispersion, followed by measures of central tendency, and by commission errors. Statistical control of ISV reduced group differences in the other measures substantially. One (patients) or two (controls) principal components explained up to 67% of the inter-individual differences in intra-individual variability. CONCLUSIONS: Results suggest that, across a variety of neuropsychological tests, measures of ISV contribute best to group discrimination, with limited incremental validity of measures of central tendency and errors. Furthermore, increased ISV might be a unitary construct in ADHD.

Repeated measurements of learned irrelevance by a novel within-subject paradigm in humans

Learned irrelevance (LIrr) refers to the retardation of classical conditioning following preexposure of the to-be-associated stimuli. Healthy volunteers have been tested on three occasions with a new LIrr paradigm avoiding methodological problems which afflict traditional paradigms. A significant LIrr effect was demonstrated on each occasion. Thus, the new paradigm enables repeated measurements of LIrr and might be useful in evaluating long-term effects of medication in psychiatric disorders exhibiting aberrant LIrr.