The challenge of measuring physiological parameters during motor imagery engagement in patients after a stroke
IntroductionIt is suggested that eye movement recordings could be used as an objective evaluation method of motor imagery (MI) engagement. Our investigation aimed to evaluate MI engagement in patients after stroke (PaS) compared with physical execution (PE) of a clinically relevant unilateral upper...
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Frontiers Media S.A.
2023-07-01
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| Series: | Frontiers in Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2023.1225440/full |
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| author | Szabina Gäumann Efe Anil Aksöz Frank Behrendt Frank Behrendt Jasmin Wandel Letizia Cappelletti Annika Krug Daniel Mörder Annika Bill Katrin Parmar Katrin Parmar Hans Ulrich Gerth Hans Ulrich Gerth Leo H. Bonati Leo H. Bonati Leo H. Bonati Corina Schuster-Amft Corina Schuster-Amft Corina Schuster-Amft |
| author_facet | Szabina Gäumann Efe Anil Aksöz Frank Behrendt Frank Behrendt Jasmin Wandel Letizia Cappelletti Annika Krug Daniel Mörder Annika Bill Katrin Parmar Katrin Parmar Hans Ulrich Gerth Hans Ulrich Gerth Leo H. Bonati Leo H. Bonati Leo H. Bonati Corina Schuster-Amft Corina Schuster-Amft Corina Schuster-Amft |
| author_sort | Szabina Gäumann |
| collection | DOAJ |
| description | IntroductionIt is suggested that eye movement recordings could be used as an objective evaluation method of motor imagery (MI) engagement. Our investigation aimed to evaluate MI engagement in patients after stroke (PaS) compared with physical execution (PE) of a clinically relevant unilateral upper limb movement task of the patients' affected body side.MethodsIn total, 21 PaS fulfilled the MI ability evaluation [Kinaesthetic and Visual Imagery Questionnaire (KVIQ-10), body rotation task (BRT), and mental chronometry task (MC)]. During the experiment, PaS moved a cup to distinct fields while wearing smart eyeglasses (SE) with electrooculography electrodes integrated into the nose pads and electrodes for conventional electrooculography (EOG). To verify MI engagement, heart rate (HR) and oxygen saturation (SpO2) were recorded, simultaneously with electroencephalography (EEG). Eye movements were recorded during MI, PE, and rest in two measurement sessions to compare the SE performance between conditions and SE's psychometric properties.ResultsMI and PE correlation of SE signals varied between r = 0.12 and r = 0.76. Validity (cross-correlation with EOG signals) was calculated for MI (r = 0.53) and PE (r = 0.57). The SE showed moderate test–retest reliability (intraclass correlation coefficient) with r = 0.51 (95% CI 0.26–0.80) for MI and with r = 0.53 (95% CI 0.29 – 0.76) for PE. Event-related desynchronization and event-related synchronization changes of EEG showed a large variability. HR and SpO2 recordings showed similar values during MI and PE. The linear mixed model to examine HR and SpO2 between conditions (MI, PE, rest) revealed a significant difference in HR between rest and MI, and between rest and PE but not for SpO2. A Pearson correlation between MI ability assessments (KVIQ, BRT, MC) and physiological parameters showed no association between MI ability and HR and SpO2.ConclusionThe objective assessment of MI engagement in PaS remains challenging in clinical settings. However, HR was confirmed as a reliable parameter to assess MI engagement in PaS. Eye movements measured with the SE during MI did not resemble those during PE, which is presumably due to the demanding task. A re-evaluation with task adaptation is suggested. |
| first_indexed | 2024-03-12T20:57:40Z |
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| language | English |
| last_indexed | 2024-03-12T20:57:40Z |
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| series | Frontiers in Neuroscience |
| spelling | doaj.art-078adc29031b41ebb684bec39656e6102023-07-31T13:15:54ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2023-07-011710.3389/fnins.2023.12254401225440The challenge of measuring physiological parameters during motor imagery engagement in patients after a strokeSzabina Gäumann0Efe Anil Aksöz1Frank Behrendt2Frank Behrendt3Jasmin Wandel4Letizia Cappelletti5Annika Krug6Daniel Mörder7Annika Bill8Katrin Parmar9Katrin Parmar10Hans Ulrich Gerth11Hans Ulrich Gerth12Leo H. Bonati13Leo H. Bonati14Leo H. Bonati15Corina Schuster-Amft16Corina Schuster-Amft17Corina Schuster-Amft18Department of Research, Reha Rheinfelden, Rheinfelden, SwitzerlandSchool of Engineering and Information Technology, Bern University of Applied Sciences, Biel, SwitzerlandDepartment of Research, Reha Rheinfelden, Rheinfelden, SwitzerlandSchool of Engineering and Information Technology, Bern University of Applied Sciences, Biel, SwitzerlandInstitute for Optimisation and Data Analysis, Bern University of Applied Sciences, Burgdorf, SwitzerlandDepartment of Health Professions, Bern University of Applied Science, Bern, SwitzerlandInstitute for Physiotherapy, School of Health Professions, Zurich University of Applied Sciences, Winterthur, SwitzerlandDepartment of Sport Science, Faculty of Humanities, University of Konstanz, Konstanz, GermanyInstitute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich, SwitzerlandDepartment of Research, Reha Rheinfelden, Rheinfelden, SwitzerlandDepartment of Neurology, University Hospital Basel, Basel, SwitzerlandDepartment of Research, Reha Rheinfelden, Rheinfelden, SwitzerlandDepartment of Medicine, University Hospital Münster, Münster, GermanyDepartment of Research, Reha Rheinfelden, Rheinfelden, SwitzerlandDepartment of Neurology, University Hospital Basel, Basel, Switzerland0Department of Clinical Research, University of Basel, Basel, SwitzerlandDepartment of Research, Reha Rheinfelden, Rheinfelden, SwitzerlandSchool of Engineering and Information Technology, Bern University of Applied Sciences, Biel, Switzerland1Department of Sport, Physical Activity, and Health, University of Basel, Basel, SwitzerlandIntroductionIt is suggested that eye movement recordings could be used as an objective evaluation method of motor imagery (MI) engagement. Our investigation aimed to evaluate MI engagement in patients after stroke (PaS) compared with physical execution (PE) of a clinically relevant unilateral upper limb movement task of the patients' affected body side.MethodsIn total, 21 PaS fulfilled the MI ability evaluation [Kinaesthetic and Visual Imagery Questionnaire (KVIQ-10), body rotation task (BRT), and mental chronometry task (MC)]. During the experiment, PaS moved a cup to distinct fields while wearing smart eyeglasses (SE) with electrooculography electrodes integrated into the nose pads and electrodes for conventional electrooculography (EOG). To verify MI engagement, heart rate (HR) and oxygen saturation (SpO2) were recorded, simultaneously with electroencephalography (EEG). Eye movements were recorded during MI, PE, and rest in two measurement sessions to compare the SE performance between conditions and SE's psychometric properties.ResultsMI and PE correlation of SE signals varied between r = 0.12 and r = 0.76. Validity (cross-correlation with EOG signals) was calculated for MI (r = 0.53) and PE (r = 0.57). The SE showed moderate test–retest reliability (intraclass correlation coefficient) with r = 0.51 (95% CI 0.26–0.80) for MI and with r = 0.53 (95% CI 0.29 – 0.76) for PE. Event-related desynchronization and event-related synchronization changes of EEG showed a large variability. HR and SpO2 recordings showed similar values during MI and PE. The linear mixed model to examine HR and SpO2 between conditions (MI, PE, rest) revealed a significant difference in HR between rest and MI, and between rest and PE but not for SpO2. A Pearson correlation between MI ability assessments (KVIQ, BRT, MC) and physiological parameters showed no association between MI ability and HR and SpO2.ConclusionThe objective assessment of MI engagement in PaS remains challenging in clinical settings. However, HR was confirmed as a reliable parameter to assess MI engagement in PaS. Eye movements measured with the SE during MI did not resemble those during PE, which is presumably due to the demanding task. A re-evaluation with task adaptation is suggested.https://www.frontiersin.org/articles/10.3389/fnins.2023.1225440/fullmotor imagerystrokeelectrooculographyvaliditytest–retest reliabilitysmart eyeglasses |
| spellingShingle | Szabina Gäumann Efe Anil Aksöz Frank Behrendt Frank Behrendt Jasmin Wandel Letizia Cappelletti Annika Krug Daniel Mörder Annika Bill Katrin Parmar Katrin Parmar Hans Ulrich Gerth Hans Ulrich Gerth Leo H. Bonati Leo H. Bonati Leo H. Bonati Corina Schuster-Amft Corina Schuster-Amft Corina Schuster-Amft The challenge of measuring physiological parameters during motor imagery engagement in patients after a stroke Frontiers in Neuroscience motor imagery stroke electrooculography validity test–retest reliability smart eyeglasses |
| title | The challenge of measuring physiological parameters during motor imagery engagement in patients after a stroke |
| title_full | The challenge of measuring physiological parameters during motor imagery engagement in patients after a stroke |
| title_fullStr | The challenge of measuring physiological parameters during motor imagery engagement in patients after a stroke |
| title_full_unstemmed | The challenge of measuring physiological parameters during motor imagery engagement in patients after a stroke |
| title_short | The challenge of measuring physiological parameters during motor imagery engagement in patients after a stroke |
| title_sort | challenge of measuring physiological parameters during motor imagery engagement in patients after a stroke |
| topic | motor imagery stroke electrooculography validity test–retest reliability smart eyeglasses |
| url | https://www.frontiersin.org/articles/10.3389/fnins.2023.1225440/full |
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