Passive Brain-Computer Interfaces for Robot-Assisted Rehabilitation

Autor:	Benjamin Beyeler, Robert Riener, Ximena Omlin, Domen Novak
Rok vydání:	2014
Předmět:	Rehabilitation medicine.diagnostic_test Computer science business.industry medicine.medical_treatment Work (physics) Workload Robotics Electroencephalography Task (project management) Psychophysiology Human–computer interaction medicine Artificial intelligence business Brain–computer interface
Zdroj:	SpringerBriefs in Electrical and Computer Engineering ISBN: 9783319099781 Brain-Computer Interface Research (3)
DOI:	10.1007/978-3-319-09979-8_7
Popis:	Stroke patients must exercise intensely with rehabilitation robots to achieve satisfactory rehabilitation outcome, but ensuring appropriate exercise difficulty is a challenging task. Brain-computer interfaces would be suitable for such difficulty adaptations since they capture both conscious and subconscious aspects of workload, but have seen little use in rehabilitation. This chapter reviews previous work on passive brain–computer interfaces and highlights the practical challenges of applying the technology to motor rehabilitation. Preliminary results of a study on workload estimation in a rehabilitation robot with healthy subjects are then presented. Adaptive stepwise regression is used to estimate different types of workload from electroencephalography signals recorded at different sites. Results show that electroencephalography can achieve more accurate workload estimation than autonomic nervous system responses and that adaptive estimation methods can further improve accuracy. However, the number of electrode sites needs to be reduced and issues such as motion artefacts must be resolved before passive brain-computer interfaces can be used in motor rehabilitation.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c027b1b6be5aa0c86dae32e54a724686 https://doi.org/10.1007/978-3-319-09979-8_7 Zobrazit plný text záznamu