Lower limb amputations pose significant challenges for patients, with over 150,000 cases annually in the U.S., leading to a high demand for effective prosthetics. However, only 43% of lower limb prosthetic users report satisfaction, primarily due to issues with socket fit, which is critical for comfort, stability, and preventing injury. This study presents a deployable sensing system for potentially real-time monitoring of prosthetic socket fit by using pressure sensors and convolutional neural networks (CNNs) to analyze the pressure distribution within the socket. A novel CNN architecture, utilizing both dilated and strided convolutions, is proposed to effectively capture spatial-temporal patterns in multivariate timeseries data, which is processed as an image. The system was designed for edge deployment on the Sony Spresense microcontroller, maintaining a small model size while achieving high accuracy. Results show that the CNN models, particularly those optimized with the stochastic gradient descent (SGD), demonstrated robustness and high transferability. This system provides a cost-effective, portable solution to improve prosthetic fit, enhancing patient care and preventing gait-related injuries.

Physical activity plays a crucial role in maintaining overall health and reducing the risk of various chronic diseases. Step counting has emerged as a popular method for assessing physical activity levels, given its simplicity and ease of use. However, accurately measuring step counts in free-living environments presents significant challenges, with most activity trackers exhibiting a percent error above 20%. This study aims to address these challenges by creating a machine learning algorithm that leverages activity labels to improve step count accuracy in real-world conditions. Two approaches to balancing data were used: one employed a simpler oversampling technique, while the other adopted a more nuanced approach involving the removal of outliers. Models 1 and 2 were trained on each of these uniquely balanced datasets. Model 1 performed much better than Model 2 on testing datasets, but both achieved better than 20% error on new datasets, indicating their potential for more accurate step counting in real-world conditions. Despite challenges such as data imbalance, the study demonstrated the viability of using activity labels to enhance step counting accuracy. Future research should focus on addressing data imbalances and exploring more advanced machine learning techniques for more reliable activity monitoring.

In the human control of motor vehicles, there are situations regularly encountered wherein the vehicle operator becomes drowsy and fatigued due to the influence of long work days, long driving hours, or low amounts of sleep. Although various methods are currently proposed to detect drowsiness in the operator, they are either obtrusive, expensive, or otherwise impractical. The method of drowsy driving detection through the collection of Steering Wheel Movement (SWM) signals has become an important measure as it lends itself to accurate, effective, and cost-effective drowsiness detection. In this dissertation, novel technologies for drowsiness detection using Inertial Measurement Units (IMUs) are investigated and described. IMUs are an umbrella group of kinetic sensors (including accelerometers and gyroscopes) which transduce physical motions into data. Driving performances were recorded using IMUs as the primary sensors, and the resulting data were used by artificial intelligence algorithms, specifically Support Vector Machines (SVMs) to determine whether or not the individual was still fit to operate a motor vehicle. Results demonstrated high accuracy of the method in classifying drowsiness. It was also shown that the use of a smartphone-based approach to IMU monitoring of drowsiness will result in the initiation of feedback mechanisms upon a positive detection of drowsiness. These feedback mechanisms are intended to notify the driver of their drowsy state, and to dissuade further driving which could lead to crashes and/or fatalities. The novel methods not only demonstrated the ability to qualitatively determine a drivers drowsy state, but they were also low-cost, easy to implement, and unobtrusive to drivers. The efficacy, ease of use, and ease of access to these methods could potentially eliminate many barriers to the implementation of the technologies. Ultimately, it is hoped that these findings will help enhance traveler safety and prevent deaths and injuries to users.

Advanced biomaterials and sophisticated processing technologies aim to fabricate tissue-engineering scaffolds that can predictably interact within a biological environment at a cellular level. Sterilization of such scaffolds is at the core of patient safety and is an important regulatory issue that needs to be addressed prior to clinical translation. In addition, it is crucial that meticulously engineered micro- and nano- structures are preserved after sterilization. Conventional sterilization methods involving heat, steam and radiation are not compatible with engineered polymeric systems because of scaffold degradation and loss of architecture. Using electrospun scaffolds made from polycaprolactone (PCL), a low melting polymer, and employing spores of Bacillus atrophaeus as biological indicators, we compared ethylene oxide, autoclaving and 80% ethanol to a known chemical sterilant, peracetic acid (PAA), for their ability to sterilize as well as their effects on scaffold properties. PAA diluted in 20% ethanol to 1000 ppm or above, sterilized electrospun scaffolds in 15 min at room temperature while maintaining nano-architecture and mechanical properties. Scaffolds treated with PAA at 5000 ppm were rendered hydrophilic, with contact angles reduced to zero degrees. Therefore, PAA can provide economical, rapid and effective sterilization of heat-sensitive polymeric electrospun scaffolds used in tissue-engineering.

Heart failure is expected to ail over 8 million people in America by 2030 leaving many in need of cardiac replacement. To accommodate this large volume of people, ventricular assist devices (VADs) are necessary to provide mechanical circulatory support. Current VADs exhibit issues such as thrombosis and hemolysis caused by large local pressure drops and turbulent flow within the pump. Multiple disk centrifugal pumps (MDCPs) use shearing and centrifugal forces to produce laminar flow patterns and eliminate large pressure drops within the pump which greatly reduce risks that are in current VADs. The MDCP has a shaft drive system (SDS) that causes leakage between the motor and housing that when implanted can cause blood loss, infection, thrombosis and hemolysis. To eliminate these adverse effects, a magnetic external motor-driven system (MEMDS) was implemented. An efficiency study was performed to examine the efficacy of the MEMDS by comparing the hydraulic work of the MDCP to the power required to run the pump. This was done by measuring inlet and outlet pressures, outlet flow rate and input current at various input voltages and resistances. The results showed the MDCP could produce physiologic flow characteristics with a flow rate of 4.90 L/min and outlet pressure of 61.33 mmHg at an impeller speed of 989.79 rpm. Other VADs generate flow rates around 5 L/min at rotational speeds of 2400 rpm for centrifugal pumps and 12000 rpm for axial pumps. When compared to the SDS, the MEMDS exhibited similar efficiencies of 3.89% and 3.50% respectively. This study shows promise in the advancement of MDCP.

Hip resurfacing arthroplasty has changed the treatment of end stage arthritis without severe deformity for young, active adults. Presently, there are varying clinical approaches to implant design selection and cementation techniques. The purpose of this project is to determine what amount of reamer-femoral component offset allows for the best cement penetration into the femoral head. Rapid prototyped femoral component models were produced with reamer femoral component offsets of 0.0 mm, 0.5 mm, and 1.0 mm. After implantation onto models of reamed femoral heads made from high-density open-cell reticulated carbon foam, cement penetration was assessed from cross-sections of the foam-implant unit. Increased offset was found to decrease the extent of cement over penetration from the dome and chamfer. Increased offset also yielded optimal cement penetration as measured from the walls. Finally, increased offset was found to increase the height of cement mantle formation while maintaining complete seating of all implants.

Off-label use of traditional Oropharyngeal Airway (OPA) as a bite-block, and the subsequential procedure of force exertion of the device by physician has caused many cases of patient’s teeth damage and monetary loss, as the patient’s incisors were damaged while clenching on the OPA during an adverse scenario called “Emergency Clenching”. To remedy this harmful situation, Bardo OPA was developed by Dr. Theodore Burdumy. The Bardo airway has unique design to transfer the clenching force from incisor to the molar. However, the Bardo OPA is one-sized, and cannot fit most of the patients like the commonly-used OPAs, such as the Berman and Gudel OPA, which have a spectrum of sizes to ensure fit. In this project, a Computer Assisted Design (CAD) simulation platform was developed to simulate the scenario where OPA is placed in a patient’s oral cavity. CAD – related technique and tools, such as 3D scanner (ScanStudio HD), RapidWorks, SolidWorks and Mimics were utilized to create the models used to construct the platform. The purpose of this platform is to generate data to support the development of additional sizes and other modification to improve the current design of the Bardo OPA. MRI sets of nine (9) patients were obtained and converted into STL mesh models. Berman and Guedel OPA were used as the standard for comparison against the Bardo OPA. It was found that the Bardo OPA was able to fit into all sample patients’ models, while these models were fitted with Berman and Guedel OPA of 70-90mm (Small to medium adult) sizes. It can only be concluded that the Bardo is compatible with these OPA sizes and there was not enough evidence to show the need for additional sizes. Nevertheless, some functional features of the Bardo OPA were found potentially harmful to the patients or ineffective. Three approaches were suggested to improve the design of the Bardo to achieve better safety and efficacy.

The goal of this research was to develop a system of individualized medicine that could be applied to dermal wounds serving as a wound dressing and synthetic extracellular matrix while delivering stem cells to the wound bed. First, fabrication parameters for electrospinning polymer fibers were determined. This involved evaluating fiber morphology with respect to polymer selection and solution concentration. Next, construct fabrication was examined to produce an integrated void space, or cargo area, suitable to maintain stem cells. In vitro studies to ensure stem cell viability and phenotype were conducted, and results supported the notion that cells could be administered to the wound site through construct pre-seeding. Lastly, in vivostudies were conducted to evaluate the construct as an applied biomaterial and as a cellular delivery device. Wound closure and quality were assessed, and neo-vascularization quantified. This project will provide insight into the tissue engineering field regarding cell-based therapies and dermal wound healing.

One countermeasure to cardiovascular spaceflight deconditioning being tested is the application of intermittent artificial gravity provided by centripetal acceleration of a human via centrifuge. However, artificial gravity protocols have not been optimized for the cardiovascular system, or any other physiological system for that matter. Before artificial gravity protocols can be optimized for the cardiovascular system, cardiovascular responses to the variables of artificial gravity need to be quantified. The research presented in this document is intended to determine how the artificial gravity variables, radius (gravity gradient) and lower limb exercise, affect cardiovascular responses during centrifugation. Net fluid (blood) shifts between body segments (thorax, abdomen, upper leg, lower leg) will be analyzed to assess the cardiovascular responses to these variables of artificial gravity, as well as to begin to understand potential mechanism(s) underlying the beneficial orthostatic tolerance response resulting from artificial gravity training. Methods: Twelve healthy males experienced the following centrifuge protocols. Protocol A: After 10 minutes of supine control, the subjects were exposed to rotational 1 Gz at radius of rotation 8.36 ft (2.54 m) for 2 minutes followed by 20 minutes alternating between 1 and 1.25 Gz. Protocol B: Same as A, but lower limb exercise (70% V02max) preceded ramps to 1.25 Gz. Protocol C: Same as A but radius of rotation 27.36 ft (8.33 m). Results: While long radius without exercise presented an increased challenge for the cardiovascular system compared to short radius without exercise, it is likely at the expense of more blood “pooling” in the abdominal region. Whereas short radius with exercise provided a significant response compared to short radius without exercise. More fluid loss occurred from the thorax and with the increased fluid loss from the thorax blood did not “pool” in the abdominal region but instead was essentially “mobilized” to the upper and lower leg. The exercise fluid shift profile presented in this document is applicable to not only artificial gravity protocol design but also proposes a mechanistic reason as to why certain artificial gravity protocols are more effective than others in increasing orthostatic tolerance.

This study combines noninvasive hybrid diffuse optical spectroscopies [near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS)] with occlusive calibration for continuous measurement of absolute blood flow (BF), tissue blood oxygenation (StO2), and oxygen consumption rate (VO2) in exercising skeletal muscle. Subjects performed rhythmic dynamic handgrip exercise, while an optical probe connected to a hybrid NIRS/DCS flow-oximeter directly monitored oxy-, deoxy-, and total hemoglobin concentrations ([HbO2], [Hb], and [tHb]), StO2, relative BF (rBF), and relative VO2 (rVO2) in the forearm flexor muscles. Absolute baseline BF and VO2 were obtained through venous and arterial occlusions, respectively, and used to calibrate continuous relative parameters. Previously known problems with muscle fiber motion artifact in optical measurements were mitigated with a novel dynamometer-based gating algorithm. Nine healthy young subjects were measured and results validated against previous literature findings. Ten older subjects with fibromyalgia and thirteen age-matched healthy controls were then successfully measured to observe differences in hemodynamic and metabolic response to exercise. This study demonstrates a novel application of NIRS/DCS technology to simultaneously evaluate quantitative hemodynamic and metabolic parameters in exercising skeletal muscle. This method has broad application to research and clinical assessment of disease (e.g. peripheral vascular disease, fibromyalgia), treatment evaluation, and sports medicine.