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Team sports frequently use inertial measurement units (IMU) fixed at the scapulae for the quantification of athlete performance. Similar IMU are used in clinical settings for gait analysis and jump testing but are located at the center of mass (COM). For clinical methods of jump and gait analysis to be translated to sports related IMU, an investigation of the validity of measure from the scapulae should be assessed. The objective of the current study was to translate clinical methods of gait analysis and jump assessment to commercially available trunk-mounted accelerometers. The current study created a gait program to analyze and compile the gait data. Following completion of the gait program, the IMU (STATSports APEX) was investigated for validity against ankle accelerometers. Once the validity was determined, an application study evaluated the relevance of collecting gait data during a NCAA D1 Women's Soccer season. Similarly, the trunk-mounted accelerometer was validated against force plates to assess countermovement jump height. The final study assessed how both jump height and gait variables changed due to game-related decline in performance. This study provides evidence that trunk-mounted accelerometers are a valid tool for assessing temporal gait variables (ICCRight = 0.95 and ICCLeft = 0.96), CMJ height (ICCJH = 0.90) and flight time (ICCFT = 0.88). A longitudinal analysis of gait showed that StepL, StrideL, kleg, and postural variables changed regularly in pre-post comparisons of performance. Postural variables had more changes towards the end of the season. Root mean squares (RMS) of accelerations and angular velocities had the highest correlations to High Speed Running (HSR). Fractal step and stride length (StepLα and StrideLα) had the strongest correlation to Total Distance (Rstep = -0.29 and Rstride = -0.29), or Tot Dist. When comparing gait and CMJ analyses to detect game-related changes in performance, CMJ was more descriptive of fatigue. In a proof-of-concept study, pre-post changes in CMJ immediately before and after a game had a moderate negative correlation (R = -0.57) to Tot Dist. When the protocol changed to assess the differences between the days before and after the game, the correlation weakened to R = -0.27. Spatiotemporal and spring mass variables did not change, whereas postural variables appeared to improve. The current study has provided evidence that running gait could be used as an athlete monitoring technique, however more data needs to be collected to understand how running gait variables change with team-sports related fatigue. / Doctor of Philosophy / Trunk-mounted accelerometers have become widely popular in team sports such as soccer. Prior to their use in team sports, accelerometers were used in clinical settings to assess gait, and in some cases jump performance. Different from the trunk-mounted accelerometers, the clinical accelerometers were fixed on the lower back to approximate the position of the center of mass. Consequently, the methods to assess gait and jump performance using an accelerometer assume that the accelerometer is fixed on the lower back. For these methods to be translated to trunk-mounted accelerometers, the validity of the methods needs to be established. This paper investigated the validity of trunk-mounted accelerometers in evaluating gait and countermovement jump height. A season-long assessment of gait provided insight into the utility of monitoring gait in team sports athletes. Lastly, a comparison of gait to countermovement jump analyses helped to elucidate what the changes in gait indicate, and how team staff may effectively utilize that information. The trunk-mounted accelerometer (STATSports APEX) was valid in estimating gait and jump variables. The seasonal analysis showed that gait variables changed frequently throughout the season. The main variables affected described the step and stride length of the individual, the stiffness of the leg, and variables representing the variability in trunk movements associated with running. The variability in trunk movements were more perturbed towards the end of the season when players may be beginning to tire from continuous training and competition. In the final study, the jump analysis proved to be more representative of the player's state of fatigue than gait. The gait variables appeared to improve after exhaustive exercise. The apparent improvement in gait variables could indicate that the players recovered quickly from the exhaustive exercise, or that gait variables respond in a more complex fashion than jump variables. More data needs to be collected on how gait changes due to game-related fatigue in soccer players to better understand its effect on neuromuscular performance.

Quantitative approaches to directly measure infant movement have not utilized miniature electronics technology, nor been used effectively in evaluating neurological dysfunctions' affect on movement. This thesis presents a new quantitative technique for measuring infant general movements (GMs) using micro-electromechanical accelerometers, while discussing future improvements for this technology and possible benefits to present methods of diagnosing cerebral palsy. For decades, GMs have interested neurologists because characteristics can indicate neurological dysfunctions. Motions over the entire body that show fluency, variation, and complexity characterize normal GMs. Analyzing these movements can accurately predict neurological dysfunction - cerebral palsy, in particular. This research describes a technique to make consistent, quantitative measurements of GMs using accelerometers on infant limbs. Signal processing techniques can find patterns, later determined characteristic of neurological dysfunctions. Such analyses complement the current technique of video footage review. Additionally, data could be reanalyzed using updated signal processing algorithms. An accurate collection of data allows physicians to quickly review an infant's entire history of motion studies. Physical information can be inferred from the data. Correlation techniques have compared motions from different limbs to examine coordination. Evidence suggests this may help indicate dysfunction. High-speed data acquisition enables the study of high-frequency motions, possibly undetectable with the human eye. This research has successfully recorded acceleration and video during GMs from four limbs on multiple infants. Signal processing techniques have been applied to create various graphical representations. The direct measurement of movement makes this work unique, enabling a graphical analysis tool for physicians based on physical performance. / Master of Science

The growth of the automobile Industry in the past 50 years is radical. The development of chassis control systems have grown drastically due to the demand for safer, faster and more comfortable vehicles. For example, the invention of Anti-lock Braking System (ABS) has resulted in saving more than a million lives since its adaptation while also allowing the vehicles to commute faster. As we move into the autonomous vehicles era, demand for additional information about tire-road interaction to improve the performance of the onboard chassis control systems, is high. This is due to the fact that the interaction between the tire and the road surface determines the stability boundary limits of the vehicles. In this research, a real-time system to classify the road surface into five major categories was developed. The five surfaces include Dry Asphalt, Wet Asphalt, Snow, and Ice and dry Concrete. tri-axial accelerometers were placed on the inner liner of the tires. An advanced signal processing technique was utilized along with a machine learning model to classify the road surfaces. The instrumented Volkswagen Jetta with intelligent tires was retrofitted with new instrumentation for collecting data and evaluating the performance of the developed real-time system. A comprehensive study on road surface classification was performed in order to determine the features of the classification algorithm. Performance of the real-time system is discussed in details and compared with offline results. / Master of Science / The automobile industry has been improving road transportation safety over the past 50 years. While we enter the autonomous vehicles era, the safety of the vehicle is of primary concern. In order to get the autonomous vehicles to production, we will have to improve the on board vehicle control systems to adapt to all surfaces. Gaining more accurate information about the tire and road interaction will help in improving the control systems. Tires have always been considered a passive element of the vehicle. However, more recently, the idea of “tire as a sensor” has surfaced and has become one of the major research thrusts in tire as well as vehicle companies. The intelligent tire research at the Center for Tire Research (CenTiRe) begun in 2010 and has been going strong. In this work, we have developed a classification algorithm to classify the road surfaces in real-time based on acceleration measured inside the tire. The information regarding the road surface would be highly beneficial for the developing new control strategies, automate service vehicles and aid surface prediction in autonomous vehicles.

General movements (GMs) are the spontaneous gross motor movements involving the whole body. GMs progressively develop as an infant ages. Several recent research studies involving the qualitative assessment of the GMs in infants have validated that GMs, or the lack of, are an accurate way diagnosing a neurological dysfunction in the early stages of infancy. One study has shown that definitely abnormal movements occurring between 10-20 weeks post-term accurately predicted cerebral palsy in infants with an accuracy of 85 to 98 percent [1]. The qualitative method of assessing an infant's GMs is an accurate way of predicting a neurological dysfunction, however, requires the review of hours of video footage by a trained physician. This process is not only time consuming and costly but is subjective in the sense that the results cannot be easily transferred among different institutions. It is also difficult to conduct longitudinal studies without first reviewing the entire history of video footage of the infant's GMs. Improvements can be made to the qualitative GMs assessment method by utilizing recent advances in technology that "can make data collection and analysis more efficient, without compromising competency" [2]. In particular, preliminary research has shown that data collected from"wired" micro-electrical-mechanical systems (MEMS) accelerometers attached to the wrist and ankles of an infant is a feasible way of collecting and characterizing the motion patterns that infants display during GMs [3]. The work presented in this thesis is directed towards improving the past research that used "wired" accelerometers to acquire acceleration signals from the limbs of infants. This thesis describes the process of transitioning the "wired" accelerometers to the wireless level, designing a user-friendly interface to graphically interpret the acceleration data, and assessing the designed system through clinical trials on normal and at-risk infants using the design system. / Master of Science