Person:
Young, Aaron

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    Biomechanics of locomotion during ground translation perturbations
    (Georgia Institute of Technology, 2023-02-23) Leestma, Jennifer K. ; Golyski, Pawel R. ; Smith, Courtney R. ; Sawicki, Gregory S. ; Young, Aaron
    The purpose of this data set is to enable the investigation of human balance and recovery strategies during perturbed walking. We performed a study where participants walked while being exposed to ground translation perturbations. We varied the magnitude, direction, and onset time of these perturbations while collecting various biomechanical outcome metrics.
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    Multi-Context, User-Independent, Real-Time Intent Recognition for Powered Lower-Limb Prostheses
    (Georgia Institute of Technology, 2023) Bhakta, Krishan ; Maldonado-Contreras, Jairo ; Camargo, Jonathan ; Zhou, Sixu ; Compton, William ; Herrin, Kinsey R. ; Young, Aaron
    Community ambulation is a critical component in maintaining a healthy lifestyle but has numerous task demands that can be challenging for individuals with limb loss. In wearable robotics, specifically powered prostheses, a need exists to provide intuitive and seamless assistance to the user. We developed a user-independent and multi-context, intent recognition system that was deployed in real-time to an open-source knee and ankle powered prosthesis (OSL). The intent recognition system predicted user intent and environment attributes using embedded sensing and control. Eleven individuals with transfemoral amputation were recruited for this study, in which 7 individuals were used for real-time validation. Here, we proposed a hierarchical control framework in which the intelligent prosthesis would first predict locomotion mode and subsequently estimate an environmental variable (i.e., walking speed or slope). Two main conclusions were found: 1) the user-independent (IND) performance across mode, speed, and slope was not statistically different from user-dependent (DEP) models in real-time, even though the offline performance of the IND system was worse 2) IND walking speed estimates showed ~0.09 m/s average error and slope estimates showed ~0.95 deg average error, which provided acceptable performance for modulating ankle and knee assistance across multi-context scenarios. Our study suggests that intelligent controllers can generalize to individuals and can perform well in real-time. In addition, we made our training dataset and the developed machine learning models publicly available to an open-source repository. This approach provides novel prosthesis users with autonomous and task-dependent functionality across real-world walking tasks.
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    A Human Lower-Limb Biomechanics and Wearable Sensors Dataset During Cyclic and Non-Cyclic Activities
    (Georgia Institute of Technology, 2023) Scherpereel, Keaton ; Molinaro, Dean ; Inan, Omer ; Shepherd, Maxwell ; Young, Aaron
    Tasks of daily living are often sporadic, highly variable, and asymmetric. Analyzing these real-world non-cyclic activities is integral for expanding the applicability of exoskeletons, protheses, wearable sensing, and activity classification to real life, and could provide new insights into human biomechanics. Yet, currently available biomechanics datasets focus on either highly consistent, continuous, and symmetric activities, such as walking and running, or only a single specific non-cyclic task. To capture a more holistic picture of lower limb movements in everyday life, we collected data from 12 participants performing 20 non-cyclic activities (e.g. sit-to-stand, jumping, squatting, lunging, cutting) as well as 11 cyclic activities (e.g. walking, running) while kinematics (motion capture and IMUs), kinetics (force plates), and EMG were collected. This dataset provides normative biomechanics for a highly diverse range of activities and common tasks from a consistent set of participants and sensors.
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    Data-Driven Control Strategies for Wearable Lower-Limb Robotic Systems
    (Georgia Institute of Technology, 2022-08-24) Young, Aaron
    IRIM hosts each semester a symposium to feature presentations from faculty and presentations of research that has been funded by our IRIM seed grant program in the last year. The symposium is a chance for faculty to meet new PhD students on campus, as well as a chance to get a better idea of what IRIM colleagues are up to these days. The goal of the symposium is to spark new ideas, new collaborations, and even new friends!
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    Career Options in Robotics: Academia vs Industry
    (Georgia Institute of Technology, 2021-02-17) Collins, Thomas R. ; Coogan, Samuel ; Dellaert, Frank ; Mazumdar, Anirban ; Parikh, Anup ; Young, Aaron
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    Star Wars: The Rise of Robots and Intelligent Machines
    (Georgia Institute of Technology, 2020-09-30) Gombolay, Matthew ; Mazumdar, Ellen Y. C. ; Yaszek, Lisa ; Young, Aaron
    A long time ago, in a galaxy far far away, a space opera movie captured the imaginations of roboticists, researchers, and writers from around the world. Over the last 43 years, Star Wars has had an immense impact on our collective perception of robotics. It has introduced some of the most beloved droids as well as one of the most feared cyborgs in science fiction. In this panel, we will discuss how the Star Wars movies have influenced the design of robots and intelligent machines, including prosthetics, cybernetics, and artificial intelligence. We will show examples of how George Lucas portrayed good and evil in different types of technology and how he depicted human-robot teaming. These illustrations have driven how we design and interact with technology to this day. Whether you love or love-to-hate the movies, these are the droids discussions that you are looking for!
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    Cost of Transport, the Correct Metric for Mobile Systems?
    (Georgia Institute of Technology, 2020-09-16) Mazumdar, Anirban ; Rouse, Elliott ; Sawicki, Gregory W. ; Young, Aaron ; Zhao, Ye
    Energetic cost of locomotion is often the gold standard measures used in autonomous robotic walking for efficiency as well as humans augmented with lower limb wearable robotics. The panel will discuss the relative benefits as well as critical disadvantages to the field’s obsession on energy cost for optimizing robotic systems and controls. Applications to clinical robotics for impaired populations, autonomous biped robotics, and wearable robotics for human augmentation will be discussed. The panel will also discuss potential alternative measures beyond energy cost to assess locomotion systems such as those associated with stability and agility.