This thesis presents the development and implementation of a machine learning prediction model for concurrently aggregating interval linear step distance predictions before future foot placement. Specifically, on-body inertial measurement units consisting of accelerometers, gyroscopes, and magnetometers, through integrated development by Xsens, are used for measuring human walking behavior in real-time. The data collection process involves measuring activity from two subject participants who travel an intended course consisting of flat, stair, and sloped walking elements. This work discusses the formulation of the ensemble machine learning prediction algorithm, real-time application design considerations, feature extraction and selection, and experimental testing under which this system performed several different test case conditions. It was found that the system was able to predict the linear step distances for 47.2% of 1060 steps within 7.6cm accuracy, 67.5% of 1060 steps within 15.2cm accuracy, and 75.8% of 1060 steps within 23cm. For separated flat walking, it was found that 93% of the 1060 steps have less than 25% error, and 75% of the 1060 steps have less than 10% error which is an improvement over the commingled data set. Future applications and work to expand upon from this system are discussed for improving the results discovered from this work. / Master of Science

Residual gait abnormalities are common following lower limb injury and/or stroke and can have several negative impacts on an individual’s life. Without continuous treatment and follow up, individuals can be prone to chronic pain as abnormal gait may lead to non-physiological loading of the musculoskeletal system. The current industry gold standard for diagnosing abnormal gait requires specialty equipment that is generally only available at designated gait facilities. Due to the inaccessibility and high cost associated with these facilities, a wearable SmartSole device to continuously detect abnormal gait was proposed. A previous iteration of the SmartSole was unable to properly detect abnormal gait and also experienced fracturing throughout the 3D printed body. In this present study, sensor placement and material selection were reconsidered to address these limitations. The objective of this study was to determine if a redesigned SmartSole could identify events of abnormal gait through validation and verification testing against the industry standard force plates. In total, 14 participants were selected for gait studies, 7 with pronounced gait abnormalities (e.g. limps), and 7 with physiological gait. Parameters of interest included stance time, gait cycle time, and the ratio of the force magnitudes recorded during heel strike and toe off. Results indicated that the SmartSole was effective at determining overall event timings within the gait cycle, as both stance and cycle time had strong, positive correlations (left stance: r = 0.761, right stance: r = 0.560, left cycle: r = 0.688) with the force plates, with the exception of right foot cycle time. The sole was not effective at measuring actual values of events during gait as there were weak correlations with the force plates. Furthermore, when comparing parameters of interest between the injured and non-injured sides for test participants with gait abnormalities, neither the SmartSole nor the force plates were able to detect significant differences. The inability of the sole to accurately collect force magnitudes or to detect abnormal gait leads to the conclusion that additional sensors may need to be implemented. Future iterations may consider placement of additional sensors to allow for a “fuller picture” and the inclusion of other types of sensors for improved, continuous tracking of gait abnormalities.

Yes / The school environment is an ideal setting for promoting physical activity (PA). Wearable activity trackers (wearables) have previously been implemented, in research, as intervention tools within the school-environment. However, the large-scale use and acceptance of wearables, in schools, is unknown. This study distributed a cross-sectional survey to school staff to investigate the prevalence of child and adolescent wearable use in schools, including when and how they are used, and school staff's willingness to use them in the future (as implemented by school staff). This survey consisted of between 13 and 22 items, including closed-ended and open-ended questions. Closed-ended responses were displayed descriptively (wearable prevalence and characteristics), and open-ended qualitative responses were categorised using descriptive content analysis (how wearables are used). 1087 school staff provided valid responses. Of those, 896 (82.4%) had never used a wearable as a teaching or support tool for their students, and 120 (11%) currently used- and 71 (6.5%) had previously used- a wearable as a teaching or support tool for their students. When wearables were used, school staff implemented their use regularly and during physical education lessons or throughout the entire school day. Wearables were used to monitor or increase student's PA levels, or for student and staff educational purposes (e.g., academic learning, movement breaks). Most school staff were willing to use a wearable as a teaching or support tool to promote student's PA, and/or learning about PA, in the future. This study is the first study to explore the widescale use and acceptance of children and adolescents using wearables in the school-setting. Findings may inform the development of future school-based interventions and public health initiatives for physical activity promotion, using wearables. / This study is funded as part of a PhD studentship by the Born in Bradford study. The Born in Bradford study receives core infrastructure funding from the Wellcome Trust (WT101597MA) and the National Institute for Health Research (NIHR), under its NIHR ARC Yorkshire and Humber (NIHR200166) and Clinical Research Network (CRN) research delivery support. For this piece of work, funding from the Sport England’s Local Delivery Pilot awarded Born in Bradford funding for this PhD studentship. S.A.C is supported by the NIHR Leicester Biomedical Research Centre—Lifestyle theme.

Wearable computers and e-textiles are becoming increasingly widespread in today's society. Motion capture is one of the many potential applications for on-body electronic systems. Previous work has been performed at Virginia Tech's E-textiles Laboratory to design a framework for a self-contained loose fit motion capture system. This system gathers information from sensors distributed throughout the body on a "smart" garment. This thesis presents the hardware and software components of the framework, along with improvements made to it. This thesis also presents an analysis of both the on-body and off-body network communication to determine how many sensors can be supported on the garment at a given time. Finally, this thesis presents a method for determining the accuracy of the smart garment and shows how it compares against a commercially available motion capture system. / Master of Science

Since the 1960s, research into the medical applications of wearable robots has been fueled by a growing need for assistive technologies that can help individuals impacted by musculoskeletal disorders such as sarcopenia independently manage common activities of daily living while maintaining their natural physical capacities. While contemporary research has demonstrated promising developments, the usefulness of exoskeletons in everyday settings remains limited due to design factors that include the limited practicality of existing battery technologies, the need for actuators exhibiting a high output torque-to-weight ratio, a need for modular designs that are minimally disruptive to wearers, and the need for control systems that can actively work in sync with a user. To explore potential solutions to some of these limiting factors, a novel ankle exoskeleton prototype supporting ankle plantarflexion during gait was developed under a design approach that seeks to optimize actuator performance. The actuation system featured in this prototype consists of a custom dual-action linear actuator that can provide mechanical assistance to both ankles via a single BLDC motor and an underlying Bowden cable system. The metric ball screw and BLDC motor implemented in the linear actuator were selectively chosen to minimize the motor torque and current required to assist wearers impacted by a degree of muscle weakness under an assistance-as-needed design paradigm. The prototype additionally features an array of force sensing resistors for tracking gait progression and exploring potential user-based control strategies for synchronizing the exoskeleton actuator with a wearer's gait. Performance analysis for this prototype was conducted with the goal of quantifying the exoskeleton's force output, actuator settling time, and the control system's ability to track gait and identify key events in the gait cycle. The preliminary findings of this experimental analysis support the viability of the actuator's dual-action concept and gait progression tracking system as a starting ground for future developments that build on a similar design optimization approach. / Master of Science / Healthy aging and good physical health are characterized in part by one's ability to self-manage a core set of daily living tasks, one of the most prominent of which is gait. Relative to existing assistive technologies such as wheelchairs, exoskeletons provide the unique benefit of providing active mechanical support while encouraging users to rely on their natural physical capabilities. While recent technological developments in the field of wearable robots show promise, the viability of exoskeletons in an everyday setting remains constrained in part by three underlying design factors: the limited practicality of existing battery technologies, a need for actuators that can satisfactorily balance a high force output with weight, and a need for control strategies that can properly synchronize wearable robots with users. The ankle exoskeleton prototype introduced in this thesis is a portable, energetically autonomous wearable device that supports ankle plantarflexion during the push-off stages of the gait cycle. The design for this prototype seeks to optimize actuator performance and features a novel dual-action linear actuator that provides walking support to both ankles using a single DC motor. The exoskeleton additionally features an array of contact sensors that track the user's progression throughout the gait cycle and allow for the examination of potential control strategies for synchronizing the actuator with the wearer's gait. Performance analysis conducted for this prototype quantifies the exoskeleton's force output, approximates the actuator's settling time between steps, and assesses the control system's ability to track gait and synchronize with a wearer. The findings from these performance evaluation experiments support the viability of the actuator's dual-action concept and gait progression tracker as a foundation for future developments that build on a similar design optimization approach.

This degree work delved into the intersections of fashion and art, specifically focusing on creating wearable knitted sculptures. For this, the presented project considered the idea of designing spatially, without a human body as a reference, by shaping knitted forms inside a scaffolding. The exploration began with an in-depth investigation of knitting to identify different form expressions through merging and manipulating traditional knitting techniques such as plain, transfer, and partial knitting. Three knitted wearable sculptures were developed based on the knitting experiments by creating stripes on the knitting in a fully fashioned way. Further on, these wearable sculptures underwent various steps of development, such as sculpting, draping, and surface modification.

abstract: Wearable robotics has gained huge popularity in recent years due to its wide applications in rehabilitation, military, and industrial fields. The weakness of the skeletal muscles in the aging population and neurological injuries such as stroke and spinal cord injuries seriously limit the abilities of these individuals to perform daily activities. Therefore, there is an increasing attention in the development of wearable robots to assist the elderly and patients with disabilities for motion assistance and rehabilitation. In military and industrial sectors, wearable robots can increase the productivity of workers and soldiers. It is important for the wearable robots to maintain smooth interaction with the user while evolving in complex environments with minimum effort from the user. Therefore, the recognition of the user's activities such as walking or jogging in real time becomes essential to provide appropriate assistance based on the activity. This dissertation proposes two real-time human activity recognition algorithms intelligent fuzzy inference (IFI) algorithm and Amplitude omega ($A \omega$) algorithm to identify the human activities, i.e., stationary and locomotion activities. The IFI algorithm uses knee angle and ground contact forces (GCFs) measurements from four inertial measurement units (IMUs) and a pair of smart shoes. Whereas, the $A \omega$ algorithm is based on thigh angle measurements from a single IMU. This dissertation also attempts to address the problem of online tuning of virtual impedance for an assistive robot based on real-time gait and activity measurement data to personalize the assistance for different users. An automatic impedance tuning (AIT) approach is presented for a knee assistive device (KAD) in which the IFI algorithm is used for real-time activity measurements. This dissertation also proposes an adaptive oscillator method known as amplitude omega adaptive oscillator ($A\omega AO$) method for HeSA (hip exoskeleton for superior augmentation) to provide bilateral hip assistance during human locomotion activities. The $A \omega$ algorithm is integrated into the adaptive oscillator method to make the approach robust for different locomotion activities. Experiments are performed on healthy subjects to validate the efficacy of the human activities recognition algorithms and control strategies proposed in this dissertation. Both the activity recognition algorithms exhibited higher classification accuracy with less update time. The results of AIT demonstrated that the KAD assistive torque was smoother and EMG signal of Vastus Medialis is reduced, compared to constant impedance and finite state machine approaches. The $A\omega AO$ method showed real-time learning of the locomotion activities signals for three healthy subjects while wearing HeSA. To understand the influence of the assistive devices on the inherent dynamic gait stability of the human, stability analysis is performed. For this, the stability metrics derived from dynamical systems theory are used to evaluate unilateral knee assistance applied to the healthy participants. / Dissertation/Thesis / Doctoral Dissertation Aerospace Engineering 2018

Wearable systems continue to gain new markets by addressing improved performance and lower size, weight and cost. Both civilian and military markets have incorporated wearable technologies to enhance and facilitate user's tasks and activities. A wearable system is a heterogeneous system composed of diverse electronic modules: data processing, input and output modules. The system is constructed to be body-borne and therefore, several constraints are put on wearable systems regarding wearability (size, weight, placement, etc.) and robustness rendering the task of designing wearable systems challenging. In this thesis, an overview of wearable systems was given by discussing definition, technology challenges, market analysis and design methodologies. Main research targeted at network architectures and robustness to environmental stresses and electromagnetic interference (EMI). The network architecture designated the data communication on the intermodule level - topology and infrastructure. A deeper analysis of wearable requirements on the network architecture was made and a new architecture is proposed based on DC power line communication network (DC-PLC). In addition, wired data communication was compared to wireless data communication by introducing statistical communication model and looking at multiple design attributes: power efficiency, scalability, and wearability. The included papers focused on wearable systems related issues including analysis of present situation, environmental and electrical robustness studies, theoretical and computer aided modelling, and experimental testing to demonstrate new wearable architectural concepts. A roadmap was given by examining the past and predicting the future of wearable systems in terms of technology, market, and architecture. However, the roadmap was updated within this thesis to include new market growth figures that proved to be far less than was predicted in 2004. User and application environmental requirements to be applied on future wearable systems were identified. A procedure is presented to address EMI and evaluated solutions in wearable application through modelling and simulation. Environmental robustness and wearability of wearable systems in general, and washability and conductive textile in particular are investigated. A measurement-based methodology to model electrical properties of conductive textile when subjected to washing was given. Employing a wired data communication network was found to be more appropriate for wearable systems than wireless networks when prioritizing power efficiency. The wearability and scalability of the wired networks was enhanced through conductive textile and DC-PLC, respectively. A basic wearable application was built to demonstrate the suitability of DC-PLC communication with conductive textile as infrastructure. The conductive textile based on metal filament showed better mechanical robustness than metal plated conductive textile. A more advanced wearable demonstrator, where DC-PLC network was implemented using transceivers, further strengthened the proposed wearable architecture. Based on the overview, the theoretical, modelling and experimental work, a possible approach of designing wearable systems that met several contradicting requirements was given.

Textile forms of wearable technology offer the potential for users to interact with electronic devices in a whole new manner. However, the operation of a wearable system can result in non-traditional on-body interactions (including gestural commands) that users may not be comfortable with performing in a public setting. Understanding the societal perceptions of gesture-based interactions will ultimately impact how readily a new form of mobile technology will be adopted within society. The goal of this research is to assess the social acceptability of a user's interaction with an electronic textile wearable interface. Two means of interaction were studied: the first was to assess the most acceptable input method for the interface (tapping, sliding, circular rotation); and the second assessment was to measure the social acceptability of a user interacting with the detachable textile interface at different locations on the body. The study recruited participants who strictly identified themselves as being of American nationality so as to gain insight into the culture-specific perceptions of interacting with a wearable form of technology.

While much attention has been paid to the usability of desktop computers, mobile com- puters are quickly becoming the dominant platform. Because mobile computers may be used in nearly any situation--including while the user is actually in motion, or performing other tasks--interfaces designed for stationary use may be inappropriate, and alternative interfaces should be considered. In this dissertation I consider the idea of microinteractions--interactions with a device that take less than four seconds to initiate and complete. Microinteractions are desirable because they may minimize interruption; that is, they allow for a tiny burst of interaction with a device so that the user can quickly return to the task at hand. My research concentrates on methods for applying microinteractions through wrist- based interaction. I consider two modalities for this interaction: touchscreens and motion- based gestures. In the case of touchscreens, I consider the interface implications of making touchscreen watches usable with the finger, instead of the usual stylus, and investigate users' performance with a round touchscreen. For gesture-based interaction, I present a tool, MAGIC, for designing gesture-based interactive system, and detail the evaluation of the tool.