| Literature DB >> 32634096 |
David Pinto-Fernandez, Diego Torricelli, Maria Del Carmen Sanchez-Villamanan, Felix Aller, Katja Mombaur, Roberto Conti, Nicola Vitiello, Juan C Moreno, Jose Luis Pons.
Abstract
Benchmarks have long been used to verify and compare the readiness level of different technologies in many application domains. In the field of wearable robots, the lack of a recognized benchmarking methodology is one important impediment that may hamper the efficient translation of research prototypes into actual products. At the same time, an exponentially growing number of research studies are addressing the problem of quantifying the performance of robotic exoskeletons, resulting in a rich and highly heterogeneous picture of methods, variables and protocols. This review aims to organize this information, and identify the most promising performance indicators that can be converted into practical benchmarks. We focus our analysis on lower limb functions, including a wide spectrum of motor skills and performance indicators. We found that, in general, the evaluation of lower limb exoskeletons is still largely focused on straight walking, with poor coverage of most of the basic motor skills that make up the activities of daily life. Our analysis also reveals a clear bias towards generic kinematics and kinetic indicators, in spite of the metrics of human-robot interaction. Based on these results, we identify and discuss a number of promising research directions that may help the community to attain a comprehensive benchmarking methodology for robot-assisted locomotion more efficiently.Entities:
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Year: 2020 PMID: 32634096 DOI: 10.1109/TNSRE.2020.2989481
Source DB: PubMed Journal: IEEE Trans Neural Syst Rehabil Eng ISSN: 1534-4320 Impact factor: 3.802