ArticleFrontiers in neuroscience2017
Benchmarking Brain-Computer Interfaces Outside the Laboratory: The Cybathlon 2016.
Article in Frontiers in neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users.PLoS biology · 2018Trial
- Competing at the Cybathlon championship for people with disabilities: long-term motor imagery brain-computer interface training of a cybathlete who has tetraplegia.Journal of neuroengineering and rehabilitation · 2022Article
- TWIICE One powered exoskeleton: effect of design improvements on usability in daily life as measured by the performance in the CYBATHLON race.Journal of neuroengineering and rehabilitation · 2022Article
- A survey on the influence of CYBATHLON on the development and acceptance of advanced assistive technologies.Journal of neuroengineering and rehabilitation · 2022Article
- A Transfer Learning Algorithm to Reduce Brain-Computer Interface Calibration Time for Long-Term Users.Frontiers in neuroergonomics · 2022Article
- Intention Detection Strategies for Robotic Upper-Limb Orthoses: A Scoping Review Considering Usability, Daily Life Application, and User Evaluation.Frontiers in neurorobotics · 2022Article
- Characterizing reproducibility of cerebral hemodynamic responses when applying short-channel regression in functional near-infrared spectroscopy.Neurophotonics · 2022Article
- Editorial: Long Term User Training and Preparation to Succeed in a Closed-Loop BCI Competition.Frontiers in human neuroscience · 2022Article
- Leaf-inspired homeostatic cellulose biosensors.Science advances · 2021Article
- Design Considerations for Long Term Non-invasive Brain Computer Interface Training With Tetraplegic CYBATHLON Pilot.Frontiers in human neuroscience · 2021Article
- Long-Term Mutual Training for the CYBATHLON BCI Race With a Tetraplegic Pilot: A Case Study on Inter-Session Transfer and Intra-Session Adaptation.Frontiers in human neuroscience · 2021Article
- Long-Term BCI Training of a Tetraplegic User: Adaptive Riemannian Classifiers and User Training.Frontiers in human neuroscience · 2021Article
- Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review.Frontiers in neurorobotics · 2020Review
- Histogram of Gradient Orientations of Signal Plots Applied to P300 Detection.Frontiers in computational neuroscience · 2019Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper presents a new approach to benchmarking brain-computer interfaces (BCIs) outside the lab. A computer game was created that mimics a real-world application of assistive BCIs, with the main outcome metric being the time needed to complete the game. This approach was used at the Cybathlon 2016, a competition for people with disabilities who use assistive technology to achieve tasks. The paper summarizes the technical challenges of BCIs, describes the design of the benchmarking game, then describes the rules for acceptable hardware, software and inclusion of human pilots in the BCI competition at the Cybathlon. The 11 participating teams, their approaches, and their results at the Cybathlon are presented. Though the benchmarking procedure has some limitations (for instance, we were unable to identify any factors that clearly contribute to BCI performance), it can be successfully used to analyze BCI performance in realistic, less structured conditions. In the future, the parameters of the benchmarking game could be modified to better mimic different applications (e.g., the need to use some commands more frequently than others). Furthermore, the Cybathlon has the potential to showcase such devices to the general public.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.