Performance Evaluation of Lower Limb Exoskeletons: A Systematic Review

David Pinto-Fernandez, Diego Torricelli*, Maria Del Carmen Sanchez-Villamanan, Felix Aller, Katja Mombaur, Roberto Conti, Nicola Vitiello, Juan C. Moreno, Jose Luis Pons

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

148 Scopus citations

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.

Original languageEnglish (US)
Article number9103122
Pages (from-to)1573-1583
Number of pages11
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume28
Issue number7
DOIs
StatePublished - Jul 2020

Funding

Manuscript received May 31, 2019; revised November 21, 2019; accepted January 3, 2020. Date of publication May 28, 2020; date of current version July 8, 2020. This work was supported in part by the H2020 Project EUROBENCH under Grant 779963, and in part by the COST Action under Grant CA16116. (David Pinto-Fernandez and Diego Torricelli contributed equally to this work.) (Corresponding author: Diego Torricelli.) David Pinto-Fernandez, Diego Torricelli, Maria del Carmen Sanchez-Villamanan, and Juan C. Moreno are with the Neural Rehabilitation Group, Cajal Institute, Spanish Research Council, 28002 Madrid, Spain (e-mail: [email protected]).

Keywords

  • Benchmarking
  • assessment
  • locomotion
  • orthoses
  • posture
  • walking
  • wearable robots

ASJC Scopus subject areas

  • Internal Medicine
  • General Neuroscience
  • Biomedical Engineering
  • Rehabilitation

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