<p>Increased muscle stiffness helps prevent excessive movement that can lead to ligament and soft-tissue damage. There is empirical evidence suggesting that muscles are important in preventing injuries caused by excessive translational movements. Very little is known, however, on how our muscles provide translational stiffness. This thesis uses complementary theoretical (Chapters 2 and 3) and experimental (Chapter 4) techniques to address how muscles provide translational joint stiffness.</p> <p>In Chapters 2 and 3, we used an elastic energy approach to successfully derive equations that quantify muscular contributions to joint stiffness. From the equations, we were able to determine how the geometric orientation and mechanical properties of an individual muscle allows it to provide translational stiffness. In Chapter 4, using the techniques developed in the previous chapters, we test the notion that the nervous system is responsive to translational loading.</p> <p>From these works, several important discoveries were found. We are the first to find that muscles with large squared projections (alignment) over a degree-of-freedom are well suited to provide translational stiffness. Further, by explicitly describing the interactions between the translational and rotational stiffnesses we found that ignoring these interactions resulted in an overestimation of principal stiffnesses. This has large implication for stability analyses, where such overestimations could suggest that an unsafe task is actually safe. Experimentally, we found that the nervous system is responsive to translational loading. This was accomplished through increased activity of muscle well suited to provide translational stiffness.</p> <p>Collectively, the works presented provide much needed knowledge on the role muscle play in stabilizing and protecting our joints. This thesis provides a strong foundation for continued joint stiffness, stability, and impedance research.</p> / Doctor of Science (PhD)

No description available.

A combination of surface electromyography (EMG) and pattern recognition algorithms have led to improvements in the functionality of upper limb prosthetics. This method of control relies on user's ability to repeatedly generate consistent muscle contractions. Research in EMG based control of prosthesis has mainly utilized adult subjects who have fully developed neuromuscular control. Little is known about children's ability to generate consistent EMG signals necessary to control artificial limbs with multiple degrees of freedom. To address this gap, two experiments were designed to validate and benchmark an experimental protocol that quantifies the ability to coordinate forearm muscle contractions in able-bodied children across adolescent ages. Able-bodied, healthy adults (n = 8) and children (n = 9) participated in the first experiment that aimed to measure the subject's ability to produce distinguishable EMG signals. Each subject performed 8 repetitions of 16 different hand/wrist movements. We quantify the number of movement types that can be classified by Support Vector Machine with > 90% accuracy. Additional adults (n=8) and children (n=12) were recruited for the second experiment which measured the subjects' ability to control the position of a virtual cursor on a 1-DoF slide using proportional EMG control under three different gain levels. We demonstrated that children had a smaller number of highly independent movements than adults did, due to higher variability. Furthermore, we found that children had higher failure rates and slower average target acquisitions due to increased time-to-target and follow-up correction time. We also found significant correlation between forearm circumference/age and performance. The results of this study provide novel insights into the technical and empirical basis to better understand neuromuscular development in pediatric upper-limb amputees.

Objective – 1) To determine whether a graft of fascia lata and part of the patellar ligament, used in an extracapsular fashion from the tibial crest to the femorofabellar ligament, would eliminate abnormal cranial drawer motion in the cranial cruciate ligament (CrCL) deficient stifle 2) To determine if two new tibial suture anchor points would enhance biomechanical function of the lateral fabellar-tibial suture (FTS). Study Design – Experimental. Animals – 28 canine cadaver hind limbs. Methods – Stifles were mounted in a jig that allowed tibial rotation during loading and were tested between loads of â 65 to 80 N in caudal and cranial drawer respectively. Stifles were tested with the CrCL intact followed by one of four stabilization techniques after CrCL transection: lateral graft technique (LGT) and three FTS with different tibial anchor points. Results – Differences in cranial drawer motion (displacement) and stiffness between the LGT and standard FTS were not significant in two data sets, when compared to the intact CrCL. The FTS with the anchor point in the tibial crest showed the least displacement of all stabilization methods. Differences in stiffness were not significant between the stabilization techniques. Conclusions – Stability provided by the LGT is comparable to that of the standard FTS for the CrCL-deficient stifle in the cadaver. Altering the tibial anchor points for the FTS did not improve stiffness or result in a further decrease in cranial drawer motion. Clinical Relevance – The LGT could be used for the treatment of acute and chronic CrCL ruptures in the dog. A clinical study is recommended. / Master of Science

Aortic aneurysm is a complex disease manifesting in a localized dilation of the aorta developing over years and carries with it a significant chance of rupture resulting in death. As only surgical methods are currently available for treatment, there is a need to understand the underlying mechanisms of the disease and how they develop and lead to expansion and rupture. Thus, the study of the formation and progression of aneurysm has also focused on quantifying any changes observed in fiber realignment and altered mechanical properties leading to vascular disease. Animal models of aneurismal disease can be useful for studying alterations during disease development (e.g., in the tissue's mechanical response). Recent efforts have been aimed at determining both the biomechanical alterations that occur with aneurysm formation and their potential for rupture. However, previous animal model work is lacking quantitative descriptions of how biomechanical response and vessel remodeling change with time and lead to the diseased state. Thus, there is a need for determining an appropriate animal model for aneurysm and developing an adequate method for quantifying and determining disease progression through alterations in biomechanical response.

Pharmaceutical aerosols provide a number of advantages for treating respiratory diseases that include targeting high doses directly to the lungs and reducing exposure of other organs to the medication, which improve effectiveness and minimize side effects. However, difficulties associated with aerosolized drug delivery to the lungs include drug losses in delivery devices and in the extrathoracic region of human upper airways. Intersubject variability of extrathoracic and thoracic drug deposition is a key issue as well and should be minimized. Improvements to respiratory drug delivery efficiency have been recently proposed by Dr. P. Worth Longest and Dr. Michael Hindle through the use controlled condensational growth methods, which include enhanced condensational growth (ECG) and excipient enhanced growth (EEG). These methods reduce inhaled drug loss through the introduction of an aerosol with an initial submicrometer aerodynamic diameter, which then experiences condensational growth to increase droplet size and enhance thoracic deposition. Tracheobronchial and nasal human airway computational models were developed for this study to assess drug delivery using conventional and EEG methods. Computational versions of these models are used to assess drug delivery and variability with computational fluid dynamics (CFD) simulations, which are validated with experimental data where possible. Using CFD, steady state delivery of albuterol sulfate (AS) during high flow therapy (HFT) through a nasal cannula was characterized with four nasal models developed for this study, with results indicating an increase in average delivered dose from 24.0% with a conventional method to 82.2% with the EEG technique and an initially sized 0.9 µm aerosol, with a corresponding decrease in the coefficient of variation from 15% to 3%. Transient CFD simulations of nebulized AS administration through a mask during noninvasive positive pressure ventilation (NPPV) were performed and validated with experimental data, which resulted in 40.5% delivered dose with the EEG method as compared with 19.5% for a conventional method and a common inhalation profile. Using two newly created face-nose-mouth-throat models, dry powder delivery of ciprofloxacin during NPPV was assessed for the first time with steady state CFD predictions, which showed an increase in average delivered lung dose through a new mask design of 78.2% for the EEG method as compared with 36.2% for conventional delivery, while corresponding differences in delivered dose between the two models were reduced from 45.4% to 12.8% with EEG. In conclusion, results of this study demonstrate (i) the use of highly realistic in silico and in vitro models to predict the lung delivery of inhaled pharmaceutical aerosols, (ii) indicate that the EEG approach can reduce variability in nose-to-lung aerosol delivery through a nasal cannula by a factor of five, and (iii) introduce new high efficiency methods for administering aerosols during NPPV, which represents an area of current clinical need.

by Fu Siu Ngor. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 117-124). / abstract --- p.I / acknowledgments --- p.III / contents --- p.V / list of figures --- p.VII / list of tables --- p.VIII / Chapter chapter 1: --- introduction / Chapter 1.1 --- Dance and jump --- p.1 / Chapter 1.2 --- Research objectives --- p.4 / Chapter 1.3 --- Research hypothesis --- p.5 / Chapter 1.4 --- Definition of terms --- p.7 / Chapter chapter 2 : --- dance injuries / Chapter 2.1 --- Epidemiology of dance injuries --- p.12 / Chapter 2.2 --- Etiology of dance injuries --- p.19 / Chapter 2.3 --- Implication to this study --- p.30 / Chapter chapter 3 : --- biomechanical studies on landing from vertical jumps / Chapter 3.1 --- Biomechanics on landing from vertical jumps --- p.31 / Chapter 3.2 --- Biomechanical studies on ballet jumps --- p.46 / Chapter 3.3 --- Kinetics and kinematics studies on jumping sports --- p.49 / Chapter 3.4 --- Implication to this study --- p.57 / Chapter CHAPTER 4 : --- MATERIAL AND METHOD / Chapter 4.1 --- Study design --- p.58 / Chapter 4.2 --- Subject and sampling method --- p.58 / Chapter 4.3 --- Instrumentation --- p.60 / Chapter 4.4 --- Method --- p.70 / Chapter CHAPTER 5 : --- RESULTS / Chapter 5.1 --- Demographic characteristics --- p.79 / Chapter 5.2 --- "kinetic and kinematics changes on landing with ""pull-up""" --- p.82 / Chapter 5.3 --- "kinetics and kinematics changes on landing with and without ""pull-up""" --- p.92 / Chapter CHAPTER 6 : --- DISCUSSION / Chapter 6.1 --- Kinetic changes --- p.96 / Chapter 6.2 --- Kinematics changes --- p.102 / Chapter 6.3 --- Correlation between kinetics and kinematics --- p.105 / Chapter 6.4 --- "Effects of'pull-up""" --- p.107 / Chapter 6.5 --- Limitation of the study --- p.108 / Chapter 6.6 --- Suggestion for future studies --- p.110 / Chapter 6.7 --- Implication of this study --- p.112 / Chapter CHAPTER 7 : --- CONCLUSIONS --- p.115 / REFERENCES --- p.117-124 / APPENDIX 1 : Demographic characteristics --- p.i / APPENDIX 2 : Kinetic data --- p.v / APPENDIX 3 : Kinematics data --- p.x / APPENDIX 4 : Summary of kinetic and kinematics results --- p.xiv / APPENDIX 5 : Statistical results --- p.xv

Mathematical musculoskeletal modeling and simulation provide a means for proactive injury prevention. To be effective, these models must physiologically replicate shoulder function. Although several muscle force prediction (MFP) shoulder models exist, few have attempted to integrate the force contributions of ligaments, especially the glenohumeral ligaments. The purpose of the current study was to integrate seven shoulder ligaments into an existing computational shoulder model, and analyze both individual ligament characteristics and the influence on the model outputs. Using data from the literature, seven shoulder ligaments were integrated into the model: the costoclavicular, conoid, trapezoid, coracohumeral, superior glenohumeral, middle glenohumeral, and inferior glenohumeral. 10 subjects performed isometric exertions in 56 posture-force combinations. Upper body posture and hand force collected were used as inputs for three different model versions; No-Ligaments (NL) included, Glenohumeral-Ligaments (GH) included, and All-Ligaments (AL) included. Electromyographic (EMG) signals from 11 muscle sites were used for comparison with model MFPs. The primary analysis focused on the differences between the GH and NL versions. Normalized EMG amplitudes were plotted against normalized MFPs from both models. Ligament effects on model outputs were measured by comparing changes in correlation between EMG and MFP, changes in slopes regression lines relating EMG to MFP, and the frequency of zero-force prediction by the model. Paired Student’s t-tests were used to measure significant differences. Results showed significant correlations (Pearson product) between EMG amplitude and MFP in the lower trapezius and infraspinatus muscles (p<0.01). No significant differences were found in r-values for these muscles between the NL and GH model. Slopes of regression lines decreased when GH ligaments were added, while the change in zero-force predictions varied by muscle. This study highlights the sensitivity of musculoskeletal models to the inclusion of ligament forces. Though correlations did not change, decreases in slope indicate increased force prediction by the GH model. Though zero-force predictions for some muscles increased, the results from those that decreased suggest muscles are active in postures where they were originally believed to be inactive. This finding suggests that inclusion of GH ligaments into our model may help predict antagonist muscle activity. However, further research is required.

Mathematical musculoskeletal modeling and simulation provide a means for proactive injury prevention. To be effective, these models must physiologically replicate shoulder function. Although several muscle force prediction (MFP) shoulder models exist, few have attempted to integrate the force contributions of ligaments, especially the glenohumeral ligaments. The purpose of the current study was to integrate seven shoulder ligaments into an existing computational shoulder model, and analyze both individual ligament characteristics and the influence on the model outputs. Using data from the literature, seven shoulder ligaments were integrated into the model: the costoclavicular, conoid, trapezoid, coracohumeral, superior glenohumeral, middle glenohumeral, and inferior glenohumeral. 10 subjects performed isometric exertions in 56 posture-force combinations. Upper body posture and hand force collected were used as inputs for three different model versions; No-Ligaments (NL) included, Glenohumeral-Ligaments (GH) included, and All-Ligaments (AL) included. Electromyographic (EMG) signals from 11 muscle sites were used for comparison with model MFPs. The primary analysis focused on the differences between the GH and NL versions. Normalized EMG amplitudes were plotted against normalized MFPs from both models. Ligament effects on model outputs were measured by comparing changes in correlation between EMG and MFP, changes in slopes regression lines relating EMG to MFP, and the frequency of zero-force prediction by the model. Paired Student’s t-tests were used to measure significant differences. Results showed significant correlations (Pearson product) between EMG amplitude and MFP in the lower trapezius and infraspinatus muscles (p<0.01). No significant differences were found in r-values for these muscles between the NL and GH model. Slopes of regression lines decreased when GH ligaments were added, while the change in zero-force predictions varied by muscle. This study highlights the sensitivity of musculoskeletal models to the inclusion of ligament forces. Though correlations did not change, decreases in slope indicate increased force prediction by the GH model. Though zero-force predictions for some muscles increased, the results from those that decreased suggest muscles are active in postures where they were originally believed to be inactive. This finding suggests that inclusion of GH ligaments into our model may help predict antagonist muscle activity. However, further research is required.

A biomechanical model of the human tongue was constructed, based upon a detailed anatomical study of an actual cadaver. Data from the Visible Human Project were segmented to create a volumetric representation of the tongue and its constituent muscles. The volumetric representation was converted to a smooth NURBS-bounded solid model--for compatibility with meshing algorithms--by lofting between splines, the vertices of which were defined by the coordinates of a smoothed triangular mesh representation. Using a hyperelastic constitutive model that allowed for the addition of active stress, the model deforms in response to user-specified muscle activation patterns. A series of meshes was created to perform a mesh validation study; in the validation tests performed, a 245,223-element mesh was found to be sufficient to model tongue behavior.Systematic samples of the behavior of the model were collected. Principal component analyses were performed on the samples to discover low-dimensional representations of tongue postures. Statistical models (linear regression models and neural networks) were fit to predict tongue posture from muscle activation, and vice versa. In all tests, it was found that a relatively small sample of tongue postures can be used to successfully generalize to larger data sets.Finally, a variety of specific tests were performed, based on claims and predictions found in previous literature. Of these, the claims of the muscular hydrostat theory of tongue movement were best supported. Simulations were also run that simulated lingual hemiplegia. It was found that substantially different muscular activation patterns were required to achieve equivalent postures in a hemiplegic tongue, relative to a normal tongue.