Regenstein Foundation Center for Bionic Medicine

  • Regenstein Foundation Center for Bionic Medicine

    Our vision is to develop, evaluate, and translate transformative technology to advance human ability
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    COVID-19 Sensor Project

    Learn more about our project to develop a wearable device that continuously tracks key symptoms of COVID-19
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    Our open-source, artificially intelligent bionic leg is now available to the scientific community

    Watch Dr. Kuiken's 2011 TED Talk

    Our Projects

    Take a look at a few of the projects we work on everyday.

    Evaluation of a Lightweight Powered Leg
    PROJECT TYPE: Biomedical Engineering

    Research Project

    Low-Cost Arm System
    PROJECT TYPE: Arms & Hands

    Research Project

    Wearable Airbag Technology to Reduce Injuries from Falls
    PROJECT TYPE: Stroke, Parkinson's Disease

    Research Project

    Targeted Reinnervation for Transradial Amputation
    PROJECT TYPE: Amputation, Arms & Hands

    Research Project

    Open Source Bionic Leg
    PROJECT TYPE: Biomedical Engineering, Mechanical Engineering, Legs, Amputation

    Research Project

    TEAMM
    PROJECT TYPE: Arms & Hands, Amputation, Legs

    Research Project

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    Research Studies

    Join our current research by becoming a participant.

    Woman with left arm amputation above the elbow looking at smartphone in right hand

    Intuitively-controlled Virtual Reality to Treat Phantom Limb Pain

    The purpose of this study is to investigate the effect of two different forms of virtual reality training as a treatment for phantom limb pain.

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    Prosthetic Gait

    Understanding how Powered Componentry Impacts Prosthetic Gait with a Transfemoral Prosthesis

    The objective of this study is to understand how using a new powered prosthetic knee and/or ankle affects how people walk with a prosthesis.

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    Limb Loss Study

    Outcomes Testing with Myoelectric Upper Limb Prosthesis Users

    This study is exploring what factors may impact function using a prosthesis.

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    Selected Publications

    Implications of EMG channel count: enhancing pattern recognition online prosthetic testing.

    INTRODUCTION: Myoelectric pattern recognition systems have shown promising control of upper limb powered prostheses and are now commercially available. These pattern recognition systems typically record from up to 8 muscle sites, whereas other control systems use two-site control. While previous offline studies have shown 8 or fewer sites to be optimal, real-time control was not evaluated. METHODS: Six individuals with no limb absence and four individuals with a transradial amputation…

    Feasibility of snapshot testing using wearable sensors to detect cardiorespiratory illness (COVID infection in India)

    Detecting the symptoms of Parkinson's disease with non-standard video.

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    Interested in joining us?

    Contact Our Lab