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WeR5 - Human likeliness as a benchmarker for wearable robotics

EasyChair Preprint no. 132

2 pagesDate: May 15, 2018


In recent years benchmarking has become an increasingly important topic for the wearable robotic community. One of the key abilities used during the benchmarking of wearable robots is motion ability. Successful motion ability is achieved once the wearable robot is capable of achieving human-like motion while integrating user controlled volitional movements. This requires an in-depth understanding of the mechanisms underlying commonly observed gait impairments. Only then, a wearable robot can allow the user to make the movements he or she desires while providing support where needed. In this conference contribution we present results of research into the mechanisms underlying gait impairments. We take individuals with a transtibial amputation as an example of unilaterally impaired individuals. These results illustrate how an increased understanding of the gait pattern can assist in the development and evaluation of wearable robots.

Keyphrases: Benschmarking, gait impairments, Motion ability, wearable robots

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Erik Prinsen and Jaap Buurke},
  title = {WeR5 - Human likeliness as a benchmarker for wearable robotics},
  howpublished = {EasyChair Preprint no. 132},
  doi = {10.29007/81l1},
  year = {EasyChair, 2018}}
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