Feedback enhances brainwave control of a novel hand-exoskeleton

EPFL scientists are developing a lightweight and portable hand exoskeleton that can be controlled with brainwaves. The device enhances performance of brain-machine interfaces and can restore functional grasps for the physically impaired. An extremely lightweight and portable hand exoskeleton may one day help the physically impaired with daily living. These are the hopes of EPFL …

Three NCCR Robotics Spin Offs selected in the IMD Start-up Competition 2017/2018

Feeltronix, Fotokite and TWIICE have been selected in this competition. For more info, visit IMD webpage. The Feeltronix breakthrough technology platform stretches the mechanical limits of electronics and provides solutions for robust and ultra-compliant rubber-based systems. Applications include smart bands for the next generation of wearables in sports, healthcare, AR/VR and fashion. Fotokite is a spin-off from ETHZürich’s Flying Machine Arena with patented technology that fundamentally solves …

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A Brain-Controlled Exoskeleton with Cascaded Event-Related Desynchronization Classifiers

  • Authors: Lee, Kyuhwa; Liu, Dong; Perroud, Laetitia; Chavarriaga, Ricardo; Millán, José del R.

This paper describes a brain-machine interface for the online control of a powered lower-limb exoskeleton based on electroencephalogram (EEG) signals recorded over the user’s sensorimotor cortical areas. We train a binary decoder that can distinguish two different mental states, which is applied in a cascaded manner to efficiently control the exoskeleton in three different directions: walk front, turn left and turn right. This is realized by first classifying the user’s intention to walk front or change the direction. If the user decides to change the direction, a subsequent classification is performed to decide turn left or right. The user’s mental command is conditionally executed considering the possibility of obstacle collision. All five subjects were able to successfully complete the 3-way navigation task using brain signals while mounted in the exoskeleton. We observed on average 10.2% decrease in overall task completion time compared to the baseline protocol.

Posted on: August 31, 2016