Real-time closed-loop control of cognitive load in neurological patients during robot-assisted gait training

Alexander Koenig*, Domen Novak, Ximena Omlin, Michael Pulfer, Eric Perreault, Lukas Zimmerli, Matjaz Mihelj, Robert Riener

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

64 Scopus citations

Abstract

Cognitively challenging training sessions during robot-assisted gait training after stroke were shown to be key requirements for the success of rehabilitation. Despite a broad variability of cognitive impairments amongst the stroke population, current rehabilitation environments do not adapt to the cognitive capabilities of the patient, as cognitive load cannot be objectively assessed in real-time. We provided healthy subjects and stroke patients with a virtual task during robot-assisted gait training, which allowed modulating cognitive load by adapting the difficulty level of the task. We quantified the cognitive load of stroke patients by using psychophysiological measurements and performance data. In open-loop experiments with healthy subjects and stroke patients, we obtained training data for a linear, adaptive classifier that estimated the current cognitive load of patients in real-time. We verified our classification results via questionnaires and obtained 88% correct classification in healthy subjects and 75% in patients. Using the pre-trained, adaptive classifier, we closed the cognitive control loop around healthy subjects and stroke patients by automatically adapting the difficulty level of the virtual task in real-time such that patients were neither cognitively overloaded nor under-challenged.

Original languageEnglish (US)
Article number5977262
Pages (from-to)453-464
Number of pages12
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume19
Issue number4
DOIs
StatePublished - Aug 2011

Keywords

  • Bio cooperative control
  • Lokomat
  • cognitive control
  • psychophysiology
  • stroke rehabilitation

ASJC Scopus subject areas

  • Internal Medicine
  • Neuroscience(all)
  • Biomedical Engineering

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