Monitoring patients during neurorehabilitation following central or peripheral nervous system injury: Dynamic difficulty adaptation

Herbert Jelinek, David Cornforth, Alexander Koenig, Robert Riener, Chandan Karmakar, Mohammad Hasan Imam, Ahsan H. Khandoker, Marimuthu Palaniswami, Mario Minichiello

Research output: Book chapter/Published conference paperChapter (peer-reviewed)peer-review

3 Citations (Scopus)

Abstract

Brain injuries including stroke often require extensive cognitive and physical rehabilitation.Active mental engagement and a positive emotional state are prerequisites for optimal learning in the rehabilitation of stroke patients. Stroke often affects aspects of gait requiring balance and gait therapy using robot-assisted devices. Ideal cognitive and physical training conditions are an important prerequisite to obtain optimal robot-assisted therapeutic outcomes. Key factors for successful therapy include design of the rehabilitation task, attention to stress, and the psychological state of patients during robot-assisted gait therapy. Although the latter is difficult to gauge in real time, patient stress or anxiety can be inferred from heart rate variability (HRV). This chapter examines the design of robot assisted therapy and the effect on HRV of increasing task difficulty.
Original languageEnglish
Title of host publicationECG time series variability analysis
Subtitle of host publicationEngineering and medicine
EditorsHerbert Jelinek, David Cornforth, Ahsan Khandoker
Place of PublicationFlorida, US
PublisherCRC Press
Chapter12
Pages281-296
Number of pages16
Edition1st
ISBN (Print)9781482243475
Publication statusPublished - 2018

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