30 research outputs found

    Adaptive Controllers for Assistive Robotic Devices

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    Lower extremity assistive robotic devices, such as exoskeletons and prostheses, have the potential to improve mobility for millions of individuals, both healthy and disabled. These devices are designed to work in conjunction with the user to enhance or replace lost functionality of a limb. Given the large variability in walking dynamics from person to person, it is still an open research question of how to optimally control such devices to maximize their benefit for each individual user. In this context, it is becoming more and more evident that there exists no "one size fits all" solution, but that each device needs to be tuned on a subject-specific basis to best account for each user's unique gait characteristics. However, the controllers that run in the background of these devices to dictate when and what type of actuation to deliver often have up to a hundred different parameters that can be tuned on a subject-specific basis. To hand tune each parameter can be an extremely tedious and time consuming process. Additionally, current tuning practices often rely on subjective measures to inform the fitting process. To address the current obstacles associated with device control and tuning, I have developed novel tools that overcome some of these issues through the design of control architectures that autonomously adapt to the user based upon real-time physiological measures. This approach frames the tuning process of a device as a real-time optimization and allows for the device to co-adapt with the wearer during use. As an outcome of these approaches, I have been able to investigate what qualities of a device controller are beneficial to users through the analysis of whole body kinematics, dynamics, and energetics. The framework of my research has been broken down into four major projects. First, I investigated how current standards of processing and analyzing physiological measures could be improved upon. Specifically, I focused on how to analyze non-steady-state measures of metabolic work rate in real time and how the noise content of theses measures can inform confidence analyses. Second, I applied the techniques I developed for analyzing non-steady-state measures of metabolic work rate to conduct a real-time optimization of powered bilateral ankle exoskeletons. For this study I employed a gradient descent optimization to tune and optimize an actuation timing parameter of these simple exoskeletons on a subject-specific basis. Third, I investigated how users may use an adaptive controller where they had a more direct impact on the adaptation via their own muscle recruitment. In this study, I designed and tested an adaptive gain proportional myoelectric controller with healthy subjects walking in bilateral ankle exoskeletons. Through this work I showed that subjects adapted to using increased levels of total ankle power compared to unpowered walking in the devices. As a result, subjects decreased power at their hip and were able to achieve large decreases in their metabolic work rate compared to unpowered walking. Fourth, I compared how subjects may use a controller driven by neural signals differently than one driven by mechanically intrinsic signals. The results of this project suggest that control based on neural signals may be better suited for therapeutic rehabilitation than control based on mechanically intrinsic signals. Together, these four projects have drastically improved upon subject-specific control of assistive devices in both a research and clinical setting.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144029/1/jrkoller_1.pd

    Physical Diagnosis and Rehabilitation Technologies

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    The book focuses on the diagnosis, evaluation, and assistance of gait disorders; all the papers have been contributed by research groups related to assistive robotics, instrumentations, and augmentative devices

    Development of a 2-DoF Ankle Exoskeleton

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    Application of wearable sensors in actuation and control of powered ankle exoskeletons: a Comprehensive Review

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    Powered ankle exoskeletons (PAEs) are robotic devices developed for gait assistance, rehabilitation, and augmentation. To fulfil their purposes, PAEs vastly rely heavily on their sensor systems. Human–machine interface sensors collect the biomechanical signals from the human user to inform the higher level of the control hierarchy about the user’s locomotion intention and requirement, whereas machine–machine interface sensors monitor the output of the actuation unit to ensure precise tracking of the high-level control commands via the low-level control scheme. The current article aims to provide a comprehensive review of how wearable sensor technology has contributed to the actuation and control of the PAEs developed over the past two decades. The control schemes and actuation principles employed in the reviewed PAEs, as well as their interaction with the integrated sensor systems, are investigated in this review. Further, the role of wearable sensors in overcoming the main challenges in developing fully autonomous portable PAEs is discussed. Finally, a brief discussion on how the recent technology advancements in wearable sensors, including environment—machine interface sensors, could promote the future generation of fully autonomous portable PAEs is provided

    Modular soft pneumatic actuator system design for compliance matching

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    The future of robotics is personal. Never before has technology been as pervasive as it is today, with advanced mobile electronics hardware and multi-level network connectivity pushing âsmartâ devices deeper into our daily lives through home automation systems, virtual assistants, and wearable activity monitoring. As the suite of personal technology around us continues to grow in this way, augmenting and offloading the burden of routine activities of daily living, the notion that this trend will extend to robotics seems inevitable. Transitioning robots from their current principal domain of industrial factory settings to domestic, workplace, or public environments is not simply a matter of relocation or reprogramming, however. The key differences between âtraditionalâ types of robots and those which would best serve personal, proximal, human interactive applications demand a new approach to their design. Chief among these are requirements for safety, adaptability, reliability, reconfigurability, and to a more practical extent, usability. These properties frame the context and objectives of my thesis work, which seeks to provide solutions and answers to not only how these features might be achieved in personal robotic systems, but as well what benefits they can afford. I approach the investigation of these questions from a perspective of compliance matching of hardware systems to their applications, by providing methods to achieve mechanical attributes complimentary to their environment and end-use. These features are fundamental to the burgeoning field of Soft Robotics, wherein flexible, compliant materials are used as the basis for the structure, actuation, sensing, and control of complete robotic systems. Combined with pressurized air as a power source, soft pneumatic actuator (SPA) based systems offers new and novel methods of exploiting the intrinsic compliance of soft material components in robotic systems. While this strategy seems to answer many of the needs for human-safe robotic applications, it also brings new questions and challenges: What are the needs and applications personal robots may best serve? Are soft pneumatic actuators capable of these tasks, or âusefulâ work output and performance? How can SPA based systems be applied to provide complex functionality needed for operation in diverse, real-world environments? What are the theoretical and practical challenges in implementing scalable, multiple degrees of freedom systems, and how can they be overcome? I present solutions to these problems in my thesis work, elucidated through scientific design, testing and evaluation of robotic prototypes which leverage and demonstrate three key features: 1) Intrinsic compliance: provided by passive elastic and flexible component material properties, 2) Extrinsic compliance: rendered through high number of independent, controllable degrees of freedom, and 3) Complementary design: exhibited by modular, plug and play architectures which combine both attributes to achieve compliant systems. Through these core projects and others listed below I have been engaged in soft robotic technology, its application, and solutions to the challenges which are critical to providing a path forward within the soft robotics field, as well as for the future of personal robotics as a whole toward creating a better society

    Design and evaluation of a passive hydraulic simulator for biceps spasticity

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    This thesis presents the design framework for a passive (unpowered) clinical training simulator using purely mechanical components to help improve the accuracy and reliability of clinical assessment. In the scope of this thesis, a prototype simulator was developed to replicate a common abnormal muscle behavior, biceps spasticity, at different levels of severities. Spasticity is often found in patients with stroke, spinal cord injuries, and other neurological disorders causing abnormal motor activity. The current assessment of spasticity is via in-person evaluation using qualitative clinical scales, and the accuracy and reliability of this method heavily depend on assessors’ previous training and clinical experience. However, the current training methods cannot provide students sufficient amount of practice, resulting in lack of proficiency and missing clear understanding of spasticity behavior. The motivation of this project is to develop a self-contained, unpowered simulator to complement the current clinical assessment training. The design process started by characterizing the main behavioral features of the spasticity and selecting the appropriate mechanical design features that provides haptic feedback comparable to a spastic biceps muscle. The prototype was further validated by a two-stage evaluation process. The first part of evaluation involved examining the performance of individual mechanical design features and their combined performance through bench-top experiments. In the second part of evaluation, clinicians were invited to assess the replicated spasticity behavior and to compare the simulation with their previous experience interacting with actual patients. The bench-top performance and clinical feedback help design iteration and provide insights into the future development of the training simulator. Preliminary results suggested the feasibility of using the simulator as a training tool to teach spasticity assessment in a classroom setting
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