Injuries and death associated with fall incidences pose a significant burden to society, both in terms of human suffering and economic losses. The main aim of this dissertation is to study approaches that can reduce the risk of falls. One major subset of falls is falls due to neurodegenerative disorders such as Parkinson’s disease (PD). Freezing of gait (FOG) is a major cause of falls in this population. Therefore, a new FOG detection method using wavelet transform technique employing optimal sampling window size, update time, and sensor placements for identification of FOG events is created and validated in this dissertation. Another approach to reduce the risk of falls in PD patients is to correctly diagnose PD motor subtypes. PD can be further divided into two subtypes based on clinical features: tremor dominant (TD), and postural instability and gait difficulty (PIGD). PIGD subtype can place PD patients at a higher risk for falls compared to TD patients and, they have worse postural control in comparison to TD patients. Accordingly, correctly diagnosing subtypes can help caregivers to initiate early amenable interventions to reduce the risk of falls in PIGD patients. As such, a method using the standing center-of-pressure time series data has been developed to identify PD motor subtypes in this dissertation. Finally, an intervention method to improve dynamic stability was tested and validated. Unexpected perturbation-based training (PBT) is an intervention method which has shown promising results in regard to improving balance and reducing falls. Although PBT has shown promising results, the efficacy of such interventions is not well understood and evaluated. In other words, there is paucity of data revealing the effects of PBT on improving dynamic stability of walking and flexible gait adaptability. Therefore, the effects

of three types of perturbation methods on improving dynamics stability was assessed. Treadmill delivered translational perturbations training improved dynamic stability, and adaptability of locomotor system in resisting perturbations while walking.

Human walking is a complex and rhythmical activity that comprises of the brain, nerves and muscles. Neuromuscular disorder (NMD) is a broad term that refers to conditions that affect the proper use of muscles and nervous system, thus also impairing the walking or gait cycle of an individual. The improper gait cycle might be attributed to the lack of force produced at the toe-off stage. This project addresses if it is possible to create an OpenSim model to find the ideal time and force magnitude needed of an assistive force ankle device to improve gait patterns in individuals with NMD.

Individuals fluent in sign language who have at least one deaf parent are considered native signers while those with non-signing, hearing parents are non-native signers. Musculoskeletal pain from repetitive motion is more common from non-natives than natives. The goal of this study was twofold: 1) to examine differences in upper extremity (UE) biomechanical measures between natives and non-natives and 2) upon creating a composite measure of injury-risk unique to signers, to compare differences in scores between natives and non-natives. Non-natives were hypothesized to have less favorable biomechanical measures and composite injury-risk scores compared to natives. Dynamometry was used for measurement of strength, electromyography for ‘micro’ rest breaks and muscle tension, optical motion capture for ballistic signing, non-neutral joint angle and work envelope, a numeric pain rating scale for pain, and the modified Strain Index (SI) as a composite measure of injury-risk. There were no differences in UE strength (all p≥0.22). Natives had more rest (natives 76.38%; non-natives 26.86%; p=0.002) and less muscle tension (natives 11.53%; non-natives 48.60%; p=0.008) for non-dominant upper trapezius across the first minute of the trial. For ballistic signing, no differences were found in resultant linear segment acceleration when producing the sign for ‘again’ (natives 27.59m/s2; non-natives 21.91m/s2; p=0.20). For non-neutral joint angle, natives had more wrist flexion-extension motion when producing the sign for ‘principal’ (natives 54.93°; non-natives 46.23°; p=0.04). Work envelope demonstrated the greatest significance when determining injury-risk. Natives had a marginally greater work envelope along the z-axis (inferior-superior) across the first minute of the trial (natives 35.80cm; non-natives 30.84cm; p=0.051). Natives (30%) presented with a lower pain prevalence than non-natives (40%); however, there was no significant difference in the modified SI scores (natives 4.70 points; non-natives 3.06 points; p=0.144) and no association between presence of pain with the modified SI score (r=0.087; p=0.680). This work offers a comprehensive analysis of all the previously identified UE biomechanics unique to signers and helped to inform a composite measure of injury-risk. Use of the modified SI demonstrates promise, although its lack of association with pain does confirm that injury-risk encompasses other variables in addition to a signer’s biomechanics.

Muscular weakness is a common manifestation for Stroke survivors and for patients with Anterior Cruciate Ligament reconstruction leading to reduced functional independence, especially mobility. Several rigid orthotic devices are being designed to assist mobility. However, limitations in majority of these devices are: 1) that they are constrained only to level walking applications, 2) are mostly bulky and rigid lacking user comfort. For these reasons, rehabilitation using soft-robotics can serve as a powerful modality in gait assistance and potentially accelerate functional recovery. The characteristics of soft robotic exosuit is that it’s more flexible, delivers high power to weight ratio, and conforms with the user’s body structure making it a suitable choice. This work explores the implementation of an existing soft robotic exosuit in assisting knee joint mechanism during stair ascent for patients with muscular weakness. The exosuit assists by compensating the lack of joint moment and minimizing the load on the affected limb. It consists of two I-cross-section soft pneumatic actuators encased within a sleeve along with insole sensor shoes and control electronics. The exosuit actuators were mechanically characterized at different angles, in accordance to knee flexion in stair gait, to enable the generation of the desired joint moments. A linear relation between the actuator stiffness and internal pressure as a function of the knee angle was obtained. Results from this characterization along with the insole sensor outputs were used to provide assistance to the knee joint. Analysis of stair gait with and without the exosuit ‘active’ was performed, using surface electromyography (sEMG) sensors, for two healthy participants at a slow walking speed. Preliminary user testing with the exosuit presented a promising 16% reduction in average muscular activity of Vastus Lateralis muscle and a 3.6% reduction on Gluteus Maximus muscle during the stance phase and unrestrained motion during the swing phase of ascent thereby demonstrating the applicability of the soft-inflatable exosuit in rehabilitation.

As life expectancy continually rises, many age-related conditions such as deteriorated gait and decreased stability begin to play a larger role in affecting the quality of life for all individuals. Medical expenses associated with falls in the elderly population surpassed $50 Billion in 2015 alone. Understanding fall risk and developing robust metrics and methods of assessment has become more important than ever. While traditional fall risk has looked at classical gait parameters, dynamic stability has gained traction as a more accurate representation of stability during active movement and daily activities. This project seeks to determine the effects on the internal perturbation of gait velocity on dynamic stability represented by the Maximal Lyapunov Exponent (MLE) of multiple acceleration vectors, as well as the efficacy of varying methodology used to assess dynamic stability. Data from 15 healthy, college aged individuals was collected. Significant differences were shown between certain gait velocity trials for one analysis of the three methods explored, while overall trends suggested potential differences between gait velocities with other methodologies warranting further investigation.

Presented below is the design and fabrication of prosthetic components consisting of an attachment, tactile sensing, and actuator systems with Fused Filament Fabrication (FFF) technique. The attachment system is a thermoplastic osseointegrated upper limb prosthesis for average adult trans-humeral amputation with mechanical properties greater than upper limb skeletal bone. The prosthetic designed has: a one-step surgical process, large cavities for bone tissue ingrowth, uses a material that has an elastic modulus less than skeletal bone, and can be fabricated on one system.

FFF osseointegration screw is an improvement upon the current two-part osseointegrated prosthetics that are composed of a fixture and abutment. The current prosthetic design requires two invasive surgeries for implantation and are made of titanium, which has an elastic modulus greater than bone. An elastic modulus greater than bone causes stress shielding and overtime can cause loosening of the prosthetic.

The tactile sensor is a thermoplastic piezo-resistive sensor for daily activities for a prosthetic’s feedback system. The tactile sensor is manufactured from a low elastic modulus composite comprising of a compressible thermoplastic elastomer and conductive carbon. Carbon is in graphite form and added in high filler ratios. The printed sensors were compared to sensors that were fabricated in a gravity mold to highlight the difference in FFF sensors to molded sensors. The 3D printed tactile sensor has a thickness and feel similar to human skin, has a simple fabrication technique, can detect forces needed for daily activities, and can be manufactured in to user specific geometries.

Lastly, a biomimicking skeletal muscle actuator for prosthetics was developed. The actuator developed is manufactured with Fuse Filament Fabrication using a shape memory polymer composite that has non-linear contractile and passive forces, contractile forces and strains comparable to mammalian skeletal muscle, reaction time under one second, low operating temperature, and has a low mass, volume, and material costs. The actuator improves upon current prosthetic actuators that provide rigid, linear force with high weight, cost, and noise.

Gait training therapies are methods for improving the walking stability of individuals who have difficulty walking, whether it is due to injury or neuromuscular conditions. Perturbation training that causes individuals to correct their balance and actively improve their stability could potentially lead to longer term benefits for those with unstable gait. Subjects had the medial lateral movement of their center of mass measured through motion-tracking software (D-Flow 3 and Vicon Nexus 2.2). Perturbation training completed with the GRAIL treadmill randomly triggered medial-lateral sway perturbations of 3 cm a total of fifteen times throughout a five minute training period. Data collected to compare baseline, post-training, and one week follow-up dynamic stabilities were recorded over three minutes without any perturbations. There were no statistically significant differences when comparing the results of all subjects at each instance of data collection with each other. Thus, the perturbation training had no significant impact on the dynamic stability of gait. Major limitations that lend to the inconclusive nature of this study include a small sample size, no repetitions, and only one round of training. Further work can be done to better assess the potential impacts of perturbation training on walking stability for therapeutic use.

Military personnel are affected by muscle fatigue during the various missions and training regimens for their work. Muscle fatigue is caused by the overuse and lack of nutrients to muscles. When a soldier is fatigued, they are unable to perform at their maximum potential and are also more susceptible to injury. For military personnel to save time and money as well as become more efficient within the missions they deploy soldiers, muscle fatigue should be predicted. Predicting fatigue will allow for a reduced rate of negative exercise-related impacts. This means that soldiers will be able to avoid potential life threatening situations they encounter due to the muscle fatigue. The newest technology in wearable devices includes clothing that incorporates heart rate monitors, breathing rate and breathing depth sensors, and a database that converts this information into the amount of calories burned during a workout. Fatigue can be tracked and predicted in the military using wearable clothing with activity sensors, preventing further injury to the soldiers and optimizing performance output at all times. For military personnel, the ability to predict fatigue using this technology would be beneficial to the soldiers and the military as a whole.

The past decade has seen a drastic increase in collaboration between Computer Science (CS) and Molecular Biology (MB). Current foci in CS such as deep learning require very large amounts of data, and MB research can often be rapidly advanced by analysis and models from CS. One of the places where CS could aid MB is during analysis of sequences to find binding sites, prediction of folding patterns of proteins. Maintenance and replication of stem-like cells is possible for long terms as well as differentiation of these cells into various tissue types. These behaviors are possible by controlling the expression of specific genes. These genes then cascade into a network effect by either promoting or repressing downstream gene expression. The expression level of all gene transcripts within a single cell can be analyzed using single cell RNA sequencing (scRNA-seq). A significant portion of noise in scRNA-seq data are results of extrinsic factors and could only be removed by customized scRNA-seq analysis pipeline. scRNA-seq experiments utilize next-gen sequencing to measure genome scale gene expression levels with single cell resolution.

Almost every step during analysis and quantification requires the use of an often empirically determined threshold, which makes quantification of noise less accurate. In addition, each research group often develops their own data analysis pipeline making it impossible to compare data from different groups. To remedy this problem a streamlined and standardized scRNA-seq data analysis and normalization protocol was designed and developed. After analyzing multiple experiments we identified the possible pipeline stages, and tools needed. Our pipeline is capable of handling data with adapters and barcodes, which was not the case with pipelines from some experiments. Our pipeline can be used to analyze single experiment scRNA-seq data and also to compare scRNA-seq data across experiments. Various processes like data gathering, file conversion, and data merging were automated in the pipeline. The main focus was to standardize and normalize single-cell RNA-seq data to minimize technical noise introduced by disparate platforms.