4 research outputs found

    Electromyography for teleoperated tasks in weightlessness

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    The cooperation between robots and astronauts will become a core element of future space missions. This is accompanied by the demand for suitable input devices. An interface based on electromyography (EMG) represents a small, light and wearable device to generate a continuous 3D control signal from voluntarily muscle activation of the operator's arm. We analyzed the influence of microgravity on task performance during a 2D task on a screen. Six subjects performed aiming and tracking tasks in parabolic flights. Three different levels of fixation -- fixed feet using foot straps, semi-free by using a foot rail, and free-floating feet -- were tested to investigate how much user fixation is required to operate via the interface. The user study showed that weightlessness affects the usage of the interface only to a small extent. Success rates between 89% and 96% were reached within all conditions during microgravity. A significant effect between 0G and 1G could not be identified for the test series of fixed and semi-free feet, while free-floating feet showed significantly worse results in fine and gross motion times in 0G compared to ground tests (with success rates of 92% for 0G and 99% for 1G). Further adaptation to the altered proprioception may be needed here. Hence, foot rails as already mounted in the ISS would be sufficient to use the interface in weightlessness. Low impact of microgravity, high success rates, and an easy handling of the system, indicates a high potential of an EMG-based interface for teleoperation in space

    A New Labeling Approach for Proportional Electromyographic Control

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    Different control strategies are available for human machine interfaces based on electromyography (EMG) to map voluntary muscle signals to control signals of a remote controlled device. Complex systems such as robots or multi-fingered hands require a natural commanding, which can be realized with proportional and simultaneous control schemes. Machine learning approaches and methods based on regression are often used to realize the desired functionality. Training procedures often include the tracking of visual stimuli on a screen or additional sensors, such as cameras or force sensors, to create labels for decoder calibration. In certain scenarios, where ground truth, such as additional sensor data, can not be measured, e.g., with people suffering from physical disabilities, these methods come with the challenge of generating appropriate labels. We introduce a new approach that uses the EMG-feature stream recorded during a simple training procedure to generate continuous labels. The method avoids synchronization mismatches in the labels and has no need for additional sensor data. Furthermore, we investigated the influence of the transient phase of the muscle contraction when using the new labeling approach. For this purpose, we performed a user study involving 10 subjects performing online 2D goal-reaching and tracking tasks on a screen. In total, five different labeling methods were tested, including three variations of the new approach as well as methods based on binary labels, which served as a baseline. Results of the evaluation showed that the introduced labeling approach in combination with the transient phase leads to a proportional command that is more accurate than using only binary labels. In summary, this work presents a new labeling approach for proportional EMG control without the need of a complex training procedure or additional sensors

    Voltage-dependent gating of KCNH potassium channels lacking a covalent link between voltage-sensing and pore domains

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    Voltage-gated channels open paths for ion permeation upon changes in membrane potential, but how voltage changes are coupled to gating is not entirely understood. Two modules can be recognized in voltage-gated potassium channels, one responsible for voltage sensing (transmembrane segments S1 to S4), the other for permeation (S5 and S6). It is generally assumed that the conversion of a conformational change in the voltage sensor into channel gating occurs through the intracellular S4–S5 linker that provides physical continuity between the two regions. Using the pathophysiologically relevant KCNH family, we show that truncated proteins interrupted at, or lacking the S4–S5 linker produce voltage-gated channels in a heterologous model that recapitulate both the voltage-sensing and permeation properties of the complete protein. These observations indicate that voltage sensing by the S4 segment is transduced to the channel gate in the absence of physical continuity between the modules

    EDAN - An EMG-controlled Daily Assistant To Help People With Physical Disabilities

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    Injuries, accidents, strokes, and other diseases can significantly degrade the capabilities to perform even the most simple activities in daily life. A large share of these cases involves neuromuscular diseases, which lead to severely reduced muscle function. However, even though affected people are no longer able to move their limbs, residual muscle function can still be existent. Previous work has shown that this residual muscular activity can suffice to apply an EMG-based user interface. In this paper, we introduce DLR's robotic wheelchair EDAN (EMG-controlled Daily Assistant), which is equipped with a torque-controlled, eight degree-of-freedom light-weight arm and a dexterous, five-fingered robotic hand. Using electromyography, muscular activity of the user is measured,processed and utilized to control both the wheelchair and the robotic manipulator. This EMG-based interface is enhanced with shared control functionality to allow for efficient and safe physical interaction with the environment
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