File:On-the-Applicability-of-Brain-Reading-for-Predictive-Human-Machine-Interfaces-in-Robotics-pone.0081732.s003.ogv

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On-the-Applicability-of-Brain-Reading-for-Predictive-Human-Machine-Interfaces-in-Robotics-pone.0081732.s003.ogv ‎(Ogg multiplexed audio/video file, Theora/Vorbis, length 4 min 51 s, 426 × 320 pixels, 635 kbps overall, file size: 22.04 MB)

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English: Online adaptation of the exoskeleton by eBR in the teleoperation scenario. It is shown how the exoskeleton's control is adapted by eBR to ease the lock out from a rest position. Online prediction values and the point in time at which sensors that are integrated in the exoskeleton detect the movement onset are visualized in an inserted diagram. Video and online prediction values for BR as well as movement onsets are synchronized in time. The video shows that too early or false movement predictions by BR are irrelevant for the control of the system. Only correct movement predictions ease the handling of the exoskeleton by the operator.
Date
Source Video S3 from Kirchner E, Kim S, Straube S, Seeland A, Wohrle H, Krell M, Tabie M, Fahle M (2013). "On the Applicability of Brain Reading for Predictive Human-Machine Interfaces in Robotics". PLOS ONE. DOI:10.1371/journal.pone.0081732. PMID 24358125. PMC: 3864841.
Author Kirchner E, Kim S, Straube S, Seeland A, Wohrle H, Krell M, Tabie M, Fahle M
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This file was transferred to Wikimedia Commons from PubMed Central by way of the Open Access Media Importer.
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Date/TimeThumbnailDimensionsUserComment
current07:47, 24 December 20134 min 51 s, 426 × 320 (22.04 MB)Open Access Media Importer Bot (talk | contribs)Automatically uploaded media file from Open Access source. Please report problems or suggestions here.

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Format Bitrate Download Status Encode time
VP9 240P 232 kbps Completed 21:26, 5 September 2018 3 min 18 s
Streaming 240p (VP9) 161 kbps Completed 17:50, 6 February 2024 2.0 s
WebM 360P 680 kbps Completed 03:20, 2 December 2023 43 s
Streaming 144p (MJPEG) 832 kbps Completed 05:29, 17 November 2023 6.0 s
Stereo (Opus) 68 kbps Completed 05:29, 17 November 2023 5.0 s
Stereo (MP3) 128 kbps Completed 05:29, 17 November 2023 6.0 s

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