Hardware Podcasts

184. Bionics Help Amputees Take Big Strides Forward

The Next Byte Podcast · 23 Jul 2024 · 22m

What this episode covers

Hosts Daniel and Forbode discuss research from MIT’s Extreme Bionics Lab, led by Professor Hugh Herr and postdoc Hung Yun Song, on a new surgical technique called Agonist-Antagonist Myoneural Interface (AMI). The AMI surgery reconnects opposing muscle groups in the residual limb to restore neural feedback, allowing amputees to control robotic prosthetics with their own nervous system. The hosts highlight clinical trials showing that AMI patients achieved natural gait, obstacle navigation, and walking speeds comparable to non-amputees, significantly improving quality of life and reducing phantom pain.

Most relevant to

early-stage companies

Topics

Mentioned

Companies
MIT, Brigham and Women's Hospital, Extreme Bionics Lab, Wevolver
Also
Hugh Herr, Hung Yun Song

Related episodes from other shows

Other shows on the same ground, closest first.

  • Robot Talk · 51m

    Episode 90: Robotically Augmented People - Robot Talk Live

    Milia Hasbani of Imperial College London, Benjamin Metcalfe of the University of Bath, and Dani Clode of Cambridge University discuss robotic prosthetics and human augmentation. Hasbani explains her active prosthetic arm research using EMG and computer vision to select grasp types, while Metcalfe details a hybrid exoskeleton combining robotic support with functional electrical stimulation for rehabilitation. Clode presents her 'Third Thumb' and the Alternative Limb Project, exploring neuroplasticity, embodiment, and the ethical implications of augmenting able bodies.

    Medical & health devicesSensors & measurement in products
    10 chapters

  • Embedded.fm · 1h 12m

    187: Self-Driving Arm (Repeat)

    Patrick Pilarski, a Canada Research Chair in Machine Intelligence for Rehabilitation at the University of Alberta, discusses the development of smart prosthetic limbs that use machine learning to restore function for amputees. He explains how reinforcement learning allows prosthetics to learn from trial-and-error or by observing a user's healthy limb, addressing the challenge of mapping limited biological signals to complex robotic movements. Pilarski highlights the shift from traditional myoelectric controls to systems that predict user intent and context, such as using cameras to identify objects like soup or doorknobs to automate grip patterns.

    Embedded firmwareAI & machine learning
    7 chapters

  • Embedded.fm · 1h 12m

    187: Self-Driving Arm

    Patrick Pilarski, a Canada Research Chair at the University of Alberta, discusses his work on smart prosthetic limbs that use machine intelligence to bridge the gap between limited biological signals and complex robotic actuators. He explains how reinforcement learning allows prostheses to learn from trial and error in real-time, using techniques like 'prosthetic falconry' where a robotic limb learns by observing a user's healthy biological arm. Pilarski highlights the shift from simple myoelectric controls to systems that predict user intent and context, such as using cameras to identify objects like soup or doorknobs to pre-shape grips. He also outlines accessible tools for engineers, including Weka, OpenIA Gym, and Robotis Dynamixel servos, to get started with reinforcement learning robotics.

    Embedded firmwareRobotics & autonomy
    8 chapters

  • The Robot Report Podcast · 1h 03m

    Jeremiah Robison from Cionic creates bionic clothing to help patients walk better

    Jeremiah Robison, founder and CEO of Psionic, explains how his daughter’s cerebral palsy diagnosis inspired the creation of the Psionic Neurosleeve, a bionic garment that uses functional electrical stimulation (FES) and surface EMG sensors to augment walking for patients with mobility impairments. Robison details the engineering challenges of replacing bulky exoskeleton motors with a non-invasive, wearable system that reads neural intent and delivers real-time stimulation to four major leg muscle groups. He discusses the company's journey from garage-based prototyping to receiving FDA clearance and selling out its initial founders program, highlighting the therapeutic benefits of reinforcing neural pathways rather than just providing passive assistance.

    Medical & health devicesPrototyping & iteration
    7 chapters

  • EE Times Current · 45m

    Bio-Inspired Networks to Interface with Nervous System

    Dr. Elisa Donati of the Institute of Neuroinformatics in Zurich discusses using neuromorphic circuits to create closed-loop interfaces with the peripheral nervous system for prosthetics and drug delivery. She explains her design of analog mixed-signal chips based on Hodgkin-Huxley models to mimic biological neurons, aiming to bypass digital spike encoding for more natural communication. Professor Ralph Etienne-Cummings of Johns Hopkins University joins to discuss the history of central pattern generators (CPGs) in robotics, the challenges of long-term nerve interface stability, and the complexity of encoding sensory feedback like pain.

    Analog & power electronicsMicrocontrollers & dev platforms
    7 chapters

The summary, chapters and topics are generated from the episode’s audio by this directory, not written by The Next Byte Podcast. The episode itself belongs to its publisher.