Normal movement execution requires proper coupling of motor and sensory activation. An increasing body of literature supports the idea that incorporation of sensory stimulation into motor rehabilitation practices increases its effectiveness. Paired associative stimulation (PAS) studies, in which afferent and efferent pathways are activated in tandem, have brought attention to the importance of well-timed stimulation rather than non-associative (i.e., open-loop) activation. In patients with tetraplegia resulting from spinal cord injury (SCI), varying degrees of upper limb function may remain and could be harnessed for rehabilitation. Incorporating associative sensory stimulation coupled with self-paced motor training would be a means for supplementing sensory deficits and improving functional outcomes. In a motor rehabilitation setting, it seems plausible that sensory feedback stimulation in response to volitional movement execution (to the extent possible), which is not utilized in most PAS protocols, would produce greater benefits. This capability is developed and tested in the present study by implementing a brain-computer interface (BCI) to apply sensory stimulation synchronized with movement execution through the detection of movement intent in real time from electroencephalography (EEG). The results demonstrate that accurate sensory stimulation application in response to movement intent is feasible in SCI patients with chronic motor deficit and often precedes the onset of movement, which is deemed optimal by PAS investigations that do not involve a volitional movement task.

Since aggressive cancers are frequently hypermetabolic with angiogenic vessels, quantification of blood flow (BF) can be vital for cancer diagnosis. Our laboratory has developed a noncontact diffuse correlation tomography (ncDCT) system for 3-D imaging of BF distribution in deep tissues (up to centimeters). The ncDCT system employs two sets of optical lenses to project source and detector fibers respectively onto the tissue surface, and applies finite element framework to model light transportation in complex tissue geometries. This thesis reports our first step to adapt the ncDCT system for 3-D imaging of BF contrasts in human breast tumors. A commercial 3-D camera was used to obtain breast surface geometry which was then converted to a solid volume mesh. An ncDCT probe scanned over a region of interest on the breast mesh surface and the measured boundary data were used for 3-D image reconstruction of BF distribution. This technique was tested with computer simulations and in 28 patients with breast tumors. Results from computer simulations suggest that relatively high accuracy can be achieved when the entire tumor was within the sensitive region of diffuse light. Image reconstruction with a priori knowledge of the tumor volume and location can significantly improve the accuracy in recovery of tumor BF contrasts. In vivo ncDCT imaging results from the majority of breast tumors showed higher BF contrasts in the tumor regions compared to the surrounding tissues. Reconstructed tumor depths and dimensions matched ultrasound imaging results when the tumors were within the sensitive region of light propagation. The results demonstrate that ncDCT system has the potential to image BF distributions in soft and vulnerable tissues without distorting tissue hemodynamics. In addition to this primary study, detector fibers with different modes (i.e., single-mode, few-mode, multimode) for photon collection were experimentally explored to improve the signal-to-noise ratio of diffuse correlation spectroscopy flow-oximeter measurements.

Systemic inflammation involves a complex array of cytokines that can result in organ dysfunction. Mortality remains high despite the vast amount of research conducted to find an effective biomarker. The cause of systemic inflammation can be broad and non-specific; therefore, this research investigates using transendothelial electrical resistance (TEER) measurements to better define systemic inflammatory response syndrome (SIRS)/sepsis within a patient. Results show a difference in TEER measurements between healthy individuals and SIRS-rated patients. This research also displays correlations between TEER measurements and biomarkers currently studied with systemic inflammation (tumor necrosis factor-α, C- reactive protein, procalcitonin). Furthermore, this research also presents the groundwork for developing a microfluidic cell-based biosensor using low temperature co-fired ceramic materials. An LTCC TEER-based microfluidic device has the potential to aid in a more effective treatment strategy for patients and potentially save lives.

The knee joint plays an essential role in the human musculoskeletal system. It has evolved to withstand extreme loading conditions, while providing almost frictionless joint movement. However, its performance may be disrupted by disease, anatomical deformities, soft tissue imbalance or injury. Knee disorders are often puzzling, and accurate diagnosis may be challenging. Current evaluation approach is usually limited to a detailed interview with the patient, careful physical examination and radiographic imaging. The X-ray screening may reveal bone degeneration, but does not carry sufficient information of the soft tissue conditions. More advanced imaging tools such as MRI or CT are available, but expensive, time consuming and can be used only under static conditions. Moreover, due to limited resolution the radiographic techniques cannot reveal early stage arthritis. The arthroscopy is often the only reliable option, however due to its semi-invasive nature, it cannot be considered as a practical diagnostic tool. Therefore, the motivation for this work was to combine three scientific methods to provide a comprehensive, non-invasive evaluation tool bringing insight into the in vivo, dynamic conditions of the knee joint and articular cartilage degeneration. Electromyography and inverse dynamics were employed to independently determine the forces present in several muscles spanning the knee joint. Though both methods have certain limitations, the current work demonstrates how the use of these two methods concurrently enhances the biomechanical analysis of the knee joint conditions, especially the performance of the extensor mechanism. The kinetic analysis was performed for 12 TKA, 4 healthy individuals in advanced age and 4 young subjects. Several differences in the knee biomechanics were found between the three groups, identifying age-related and post-operative decrease in the extensor mechanism efficiency, explaining the increased effort of performing everyday activities experienced by the elderly and TKA subjects. The concept of using accelerometers to assess the cartilage degeneration has been proven based on a group of 23 subjects with non-symptomatic knees and 52 patients suffering from knee arthritis. Very high success (96.2%) of pattern classification obtained in this work clearly demonstrates that vibroarthrography is a promising, non-invasive and low-cost technique offering screening capabilities.

The purpose of this study was to evaluate the incidence of corrosion and fretting in 48 retrieved titanium-6aluminum-4vanadium and/or cobalt-chromium-molybdenum modular total hip prosthesis with respect to alloy material microstructure and design parameters. The results revealed vastly different performance results for the wide array of microstructures examined. Severe corrosion/fretting was seen in 100% of as-cast, 24% of low carbon wrought, 9% of high carbon wrought and 5% of solution heat treated cobalt-chrome. Severe corrosion/fretting was observed in 60% of Ti-6Al-4V components. Design features which allow for fluid entry and stagnation, amplification of contact pressure and/or increased micromotion were also shown to play a role. 75% of prosthesis with high femoral head-trunnion offset exhibited poor performance compared to 15% with a low offset. Large femoral heads (>32mm) did not exhibit poor corrosion or fretting. Implantation time was not sufficient to cause poor performance; 54% of prosthesis with greater than 10 years in-vivo demonstrated none or mild corrosion/fretting.

Near infrared spectroscopy (NIRS) is an emerging non-invasive optical neuro imaging technique that monitors the hemodynamic response to brain activation with ms-scale temporal resolution and sub-cm spatial resolution. The overall goal of my dissertation was to develop and apply NIRS towards investigation of neurological response to language, joint attention and planning and execution of motor skills in healthy adults. Language studies were performed to investigate the hemodynamic response, synchrony and dominance feature of the frontal and fronto-temporal cortex of healthy adults in response to language reception and expression. The mathematical model developed based on granger causality explicated the directional flow of information during the processing of language stimuli by the fronto-temporal cortex. Joint attention and planning/ execution of motor skill studies were performed to investigate the hemodynamic response, synchrony and dominance feature of the frontal cortex of healthy adults and in children (5-8 years old) with autism (for joint attention studies) and individuals with cerebral palsy (for planning/execution of motor skills studies). The joint attention studies on healthy adults showed differences in activation as well as intensity and phase dependent connectivity in the frontal cortex during joint attention in comparison to rest. The joint attention studies on typically developing children showed differences in frontal cortical activation in comparison to that in children with autism. The planning and execution of motor skills studies on healthy adults and individuals with cerebral palsy (CP) showed difference in the frontal cortical dominance, that is, bilateral and ipsilateral dominance, respectively. The planning and execution of motor skills studies also demonstrated the plastic and learning behavior of brain wherein correlation was found between the relative change in total hemoglobin in the frontal cortex and the kinematics of the activity performed by the participants. Thus, during my dissertation the NIRS neuroimaging technique was successfully implemented to investigate the neurological response of language, joint attention and planning and execution of motor skills in healthy adults as well as preliminarily on children with autism and individuals with cerebral palsy. These NIRS studies have long-term potential for the design of early stage interventions in children with autism and customized rehabilitation in individuals with cerebral palsy.

Intraoperative neurophysiologic monitoring is an integral part of spinal surgeries and involves the recording of somatosensory evoked potentials (SSEP). However, clinical application of IONM still requires anywhere between 200 to 2000 trials to obtain an SSEP signal, which is excessive and introduces a significant delay during surgery to detect a possible neurological damage. The aim of this study is to develop a means to obtain the SSEP using a much less, twelve number of recordings. The preliminary step involved was to distinguish the SSEP with the ongoing brain activity. We first establish that the brain activity is indeed quasi-stationary whereas an SSEP is expected to be identical every time a trial is recorded. An algorithm was developed using Chebychev time windowing for preconditioning of SSEP trials to retain the morphological characteristics of somatosensory evoked potentials (SSEP). This preconditioning was followed by the application of a principal component analysis (PCA)-based algorithm utilizing quasi-stationarity of EEG on 12 preconditioned trials. A unique Walsh transform operation was then used to identify the position of the SSEP event. An alarm is raised when there is a 10% time in latency deviation and/or 50% peak-to-peak amplitude deviation, as per the clinical requirements. The algorithm shows consistency in the results in monitoring SSEP in up to 6-hour surgical procedures even under this significantly reduced number of trials. In this study, the analysis was performed on the data recorded in 29 patients undergoing surgery during which the posterior tibial nerve was stimulated and SSEP response was recorded from scalp. This method is shown empirically to be more clinically viable than present day approaches. In all 29 cases, the algorithm takes 4sec to extract an SSEP signal, as compared to conventional methods, which take several minutes. The monitoring process using the algorithm was successful and proved conclusive under the clinical constraints throughout the different surgical procedures with an accuracy of 91.5%. Higher accuracy and faster execution time, observed in the present study, in determining the SSEP signals provide a much improved and effective neurophysiological monitoring process.

This thesis presents the design for a novel haptic interface for large-format touchscreens. Techniques such as electrovibration, ultrasonic vibration, and external braked devices have been developed by other researchers to deliver haptic feedback to touchscreen users. However, these methods do not address the need for spatial constraints that only restrict user motion in the direction of the constraint. This technology gap contributes to the lack of haptic technology available for touchscreen-based upper-limb rehabilitation, despite the prevalent use of haptics in other forms of robotic rehabilitation. The goal of this thesis is to display kinesthetic haptic constraints to the touchscreen user in the form of boundaries and paths, which assist or challenge the user in interacting with the touchscreen. The presented prototype accomplishes this by steering a single wheel in contact with the display while remaining driven by the user. It employs a novel embedded force sensor, which it uses to measure the interaction force between the user and the touchscreen. The haptic response of the device is controlled using this force data to characterize user intent. The prototype can operate in a simulated free mode as well as simulate rigid and compliant obstacles and path constraints. A data architecture has been created to allow the prototype to be used as a peripheral add-on device which reacts to haptic environments created and modified on the touchscreen. The long-term goal of this work is to create a haptic system that enables a touchscreen-based rehabilitation platform for people with upper limb impairments.

This thesis presents an activity mode intent recognition approach for safe, robust and reliable control of powered backbone exoskeleton. The thesis presents the background and a concept for a powered backbone exoskeleton that would work in parallel with a user. The necessary prerequisites for the thesis are presented, including the collection and processing of surface electromyography signals and inertial sensor data to recognize the user’s activity. The development of activity mode intent recognizer was described based on decision tree classification in order to leverage its computational efficiency. The intent recognizer is a high-level supervisory controller that belongs to a three-level control structure for a powered backbone exoskeleton. The recognizer uses surface electromyography and inertial signals as the input and CART (classification and regression tree) as the classifier. The experimental results indicate that the recognizer can extract the user’s intent with minimal delay. The approach achieves a low recognition error rate and a user-unperceived latency by using sliding overlapped analysis window. The approach shows great potential for future implementation on a prototype backbone exoskeleton.

Walkers provided stability to the elderly but cannot assist a person from sitting to standing. The objective of this project is to present the design and analysis of a lift assist walker. This report discusses the design and analysis of a collapsible lift assist walker capable of lifting a patient up to 250 lbs. from seated to standing in under 10 seconds. The designed walker utilized a two stage scissor mechanism with a gas spring assisted embedded linear actuator.