Refine
Document Type
- Article (18)
- Doctoral Thesis (5)
Has Fulltext
- yes (23)
Is part of the Bibliography
- no (23)
Keywords
- stroke (23) (remove)
Institute
Publisher
- Frontiers Media S.A. (12)
- MDPI (2)
- BMJ Publishing Group (1)
- Oxford University Press (1)
- SAGE Publications (1)
- Wiley (1)
Es gibt Hinweise darauf, dass das Kleinhirn an affektiven und kognitiven Verarbeitungsprozessen und an Arbeitsgedächtnisleistungen beteiligt ist. In dieser Arbeit wurden 8 Patienten mit Kleinhirninsulten (Durchschnittsalter 61,25 Jahre), die in der neurologischen Klinik der Universitätsmedizin Greifswald behandelt wurden und 7 Patienten mit peripher neurologischen Erkrankungen (Durchschnittsalter 56,71 Jahre), bei denen eine Kleinhirnläsion ausgeschlossen worden war, untersucht. Zur Beurteilung veränderter neuronaler Aktivitäten wurde eine 129-Kanal-Elektroenzephalographie-Studie (EEG) verwendet und mithilfe der Interpretation ereigniskorrelierter Potentiale (EKP) verschiedene affektive und kognitive Verarbeitungsprozesse analysiert. In der Teilstudie 1 wurde die frühe Verarbeitung visuell-affektiver Stimuli, in der Teilstudie 2 affektive und kognitive Verarbeitungsprozesse während der Präsentation visueller Stimuli, in der Teilstudie 3 affektive und kognitive Verarbeitungsprozesse während der Präsentation visueller und akustischer Stimuli und in der Teilstudie 4 die späte Verarbeitung visuell-affektiver Stimuli untersucht. Zur Untersuchung der affektiven Verarbeitungsprozesse wurden Bilder verschiedenen emotionalen Inhaltes (angenehm, neutral, unangenehm) und Erregungsstufe (schwach bis stark erregend) aus dem Katalog des International Affective Picture System (IAPS) verwendet. Es wurden Bilder in schneller 333ms (Teilstudien 1 bis 3) oder in langsamer Abfolge von 1000ms (Teilstudie 4) präsentiert. Zur Untersuchung kognitiver Verarbeitungsprozesse wurden die IAPS-Bilder bearbeitet. Für die Teilstudie 2 wurden sie mit Linien (horizontal/vertikal) überlagert und für die Teilstudie 3 mit Tönen (hoch/tief) synchronisiert. Linien und Töne unterschieden sich in ihrer Wahrscheinlichkeit des Auftretens, wobei die seltenen Reize als Zielreize dienten, welche von den Probanden mitgezählt werden mussten. Es wurden durch dieses Studiendesign folgende ereigniskorrelierte Potentiale gemessen: Die EPN, die visuelle P200 und P300, die akustische P300 und das LPP. Bezüglich der frühen und späten Verarbeitung visuell-affektiver Stimuli konnten folgende Daten erhoben werden. In der Teilstudie 1 lösten in der Läsionsgruppe nur stark erregend angenehme vs. neutrale Bilder eine EPN aus. Ein signifikanter Gruppeneffekt bestand jedoch nicht. In der Teilstudie 2 war weder für schwach noch für starke erregend affektive vs. neutrale Bilder eine EPN in der Läsions- und Kontrollgruppe nachweisbar. In der Teilstudie 3 konnte zwar nur in der Kontrollgruppe für stark erregend angenehme vs. neutrale Bilder eine EPN nachgewiesen werden, die Gruppen unterschieden sich jedoch nicht signifikant voneinander. In der Teilstudie 4 lösten weder schwach noch stark erregend affektive Bilder ein LPP in der Läsionsgruppe aus. Ein signifikanter Gruppeneffekt bestand nicht, trotz nachweisbaren LPPs in der Kontrollgruppe für schwach erregend angenehme und stark erregend affektive vs. neutrale Bilder. Bezogen auf kognitive Verarbeitungsprozesse konnte in beiden Gruppen in der Teilstudie 2 eine visuelle P300 nach der Präsentation seltener Zielreize nachgewiesen werden. Die Läsionsgruppe wies dagegen eine signifikante visuelle P200 nach Präsentation von Zielreizen gegenüber der Kontrollgruppe auf. Eine akustische P300 (P3b) war in der Teilstudie 3 nach der Präsentation akustischer Zielreize in keiner Gruppe nachweisbar. Dagegen bestand in der Kontrollgruppe eine signifikant stärkere P3a. Die Ergebnisse zeigen, dass Patienten mit einer Kleinhirnläsion keine Beeinträchtigung in der frühen oder späten Verarbeitung visuell-affektiver Stimuli aufweisen. Sie sind in der Lage, eine Bottom-up-Prozessierung visuell-affektiver Stimuli durchzuführen und sie nach ihrer Motivationsrelevanz einzuordnen. Patienten mit einer Kleinhirnläsion unterscheiden sich nicht signifikant in ihrer neuronalen Aktivität gegenüber der Kontrollgruppe während intra- und crossmodaler Verarbeitungsprozesse von visuell-affektiven Stimuli während visueller oder akustischer Aufgaben. Die in vielen Studien beobachteten affektiven Auffälligkeiten bei Patienten mit einer Kleinhirnischämie sind daher auf spätere Verarbeitungs- und Ausführungsprozesse von Emotionen zurückzuführen, welche einer kognitiven und somit Top-down-Kontrolle unterliegen. Patienten mit einer Kleinhirnläsion benötigen allerdings mehr Arbeitsgedächtnisleistung, um die gestellte visuell-kognitive Aufgabe zu absolvieren. Des Weiteren weisen sie Beeinträchtigungen in supramodalen kognitiven Verarbeitungsprozessen auf. Je schwieriger die kognitiven Anforderungen sind, umso mehr weisen Patienten mit einer Kleinhirnläsion Beeinträchtigungen in Form veränderter neuronaler Aktivität auf. Die Ergebnisse dieser Arbeit weisen darauf hin, dass das Kleinhirn vor allem an kognitiven und weniger an affektiven Verarbeitungsprozessen beteiligt ist.
Objective: To characterize a socially active humanoid robot’s therapeutic interaction as a therapeutic assistant when providing arm rehabilitation (i.e., arm basis training (ABT) for moderate-to-severe arm paresis or arm ability training (AAT) for mild arm paresis) to stroke survivors when using the digital therapeutic system Evidence-Based Robot-Assistant in Neurorehabilitation (E-BRAiN) and to compare it to human therapists’ interaction.
Methods: Participants and therapy: Seventeen stroke survivors receiving arm rehabilitation (i.e., ABT [n = 9] or AAT [n = 8]) using E-BRAiN over a course of nine sessions and twenty-one other stroke survivors receiving arm rehabilitation sessions (i.e., ABT [n = 6] or AAT [n = 15]) in a conventional 1:1 therapist–patient setting. Analysis of therapeutic interaction: Therapy sessions were videotaped, and all therapeutic interactions (information provision, feedback, and bond-related interaction) were documented offline both in terms of their frequency of occurrence and time used for the respective type of interaction using the instrument THER-I-ACT. Statistical analyses: The therapeutic interaction of the humanoid robot, supervising staff/therapists, and helpers on day 1 is reported as mean across subjects for each type of therapy (i.e., ABT and AAT) as descriptive statistics. Effects of time (day 1 vs. day 9) on the humanoid robot interaction were analyzed by repeated-measures analysis of variance (rmANOVA) together with the between-subject factor type of therapy (ABT vs. AAT). The between-subject effect of the agent (humanoid robot vs. human therapist; day 1) was analyzed together with the factor therapy (ABT vs. AAT) by ANOVA.
Main results and interpretation: The overall pattern of the therapeutic interaction by the humanoid robot was comprehensive and varied considerably with the type of therapy (as clinically indicated and intended), largely comparable to human therapists’ interaction, and adapted according to needs for interaction over time. Even substantially long robot-assisted therapy sessions seemed acceptable to stroke survivors and promoted engaged patients’ training behavior.
Conclusion: Humanoid robot interaction as implemented in the digital system E-BRAiN matches the human therapeutic interaction and its modification across therapies well and promotes engaged training behavior by patients. These characteristics support its clinical use as a therapeutic assistant and, hence, its application to support specific and intensive restorative training for stroke survivors.
Arm Ability Training (AAT) has been specifically designed to promote manual dexterity recovery for stroke patients who have mild to moderate arm paresis. The motor control problems that these patients suffer from relate to a lack of efficiency in terms of the sensorimotor integration needed for dexterity. Various sensorimotor arm and hand abilities such as speed of selective movements, the capacity to make precise goal-directed arm movements, coordinated visually guided movements, steadiness, and finger dexterity all contribute to our “dexterity” in daily life. All these abilities are deficient in stroke patients who have mild to moderate paresis causing focal disability. The AAT explicitly and repetitively trains all these sensorimotor abilities at the individual's performance limit with eight different tasks; it further implements various task difficulty levels and integrates augmented feedback in the form of intermittent knowledge of results. The evidence from two randomized controlled trials indicates the clinical effectiveness of the AAT with regard to the promotion of “dexterity” recovery and the reduction of focal disability in stroke patients with mild to moderate arm paresis. In addition, the effects have been shown to be superior to time-equivalent “best conventional therapy.” Further, studies in healthy subjects showed that the AAT induced substantial sensorimotor learning. The observed learning dynamics indicate that different underlying sensorimotor arm and hand abilities are trained. Capacities strengthened by the training can, in part, be used by both arms. Non-invasive brain stimulation experiments and functional magnetic resonance imaging data documented that at an early stage in the training cortical sensorimotor network areas are involved in learning induced by the AAT, yet differentially for the tasks trained. With prolonged training over 2 to 3 weeks, subcortical structures seem to take over. While behavioral similarities in training responses have been observed in healthy volunteers and patients, training-induced functional re-organization in survivors of a subcortical stroke uniquely involved the ipsilesional premotor cortex as an adaptive recruitment of this secondary motor area. Thus, training-induced plasticity in healthy and brain-damaged subjects are not necessarily the same.
Connectivity-Based Predictions of Hand Motor Outcome for Patients at the Subacute Stage After Stroke
(2016)
Background: Connectivity-based predictions of hand motor outcome have been proposed to be useful in stroke patients. We intended to assess the prognostic value of different imaging methods on short-term (3 months) and long-term (6 months) motor outcome after stroke.
Methods: We measured resting state functional connectivity (rsFC), diffusion weighted imaging (DWI) and grip strength in 19 stroke patients within the first days (5–9 days) after stroke. Outcome measurements for short-term (3 months) and long-term (6 months) motor function was assessed by the Motricity Index (MI) of the upper limb and the box and block test (BB). Patients were predominantly mildly affected since signed consent was necessary at inclusion. We performed a multiple stepwise regression analysis to compare the predictive value of rsFC, DWI and clinical measurements.
Results: Patients showed relevant improvement in both motor outcome tests. As expected grip strength at inclusion was a predictor for short- and long-term motor outcome as assessed by MI. Diffusion-based tract volume (DTV) of the tracts between ipsilesional primary motor cortex and contralesional anterior cerebellar hemisphere showed a strong trend (p = 0.05) for a predictive power for long-term motor outcome as measured by MI. DTV of the interhemispheric tracts between both primary motor cortices was predictive for both short- and long-term motor outcome in BB. rsFC was not associated with motor outcome.
Conclusions: Grip strength is a good predictor of hand motor outcome concerning strength-related measurements (MI) for mildly affected subacute patients. Therefore additional connectivity measurements seem to be redundant in this group. Using more complex movement recruiting bilateral motor areas as an outcome parameter, DTV and in particular interhemispheric pathways might enhance predictive value of hand motor outcome.
Introduction: Outcome measures are key to tailor rehabilitation goals to the stroke patient's individual needs and to monitor poststroke recovery. The large number of available outcome measures leads to high variability in clinical use. Currently, an internationally agreed core set of motor outcome measures for clinical application is lacking. Therefore, the goal was to develop such a set to serve as a quality standard in clinical motor rehabilitation poststroke.
Methods: Outcome measures for the upper and lower extremities, and activities of daily living (ADL)/stroke-specific outcomes were identified and presented to stroke rehabilitation experts in an electronic Delphi study. In round 1, clinical feasibility and relevance of the outcome measures were rated on a 7-point Likert scale. In round 2, those rated at least as “relevant” and “feasible” were ranked within the body functions, activities, and participation domains of the International Classification of Functioning, Disability, and Health (ICF). Furthermore, measurement time points poststroke were indicated. In round 3, answers were reviewed in reference to overall results to reach final consensus.
Results: In total, 119 outcome measures were presented to 33 experts from 18 countries. The recommended core set includes the Fugl–Meyer Motor Assessment and Action Research Arm Test for the upper extremity section; the Fugl–Meyer Motor Assessment, 10-m Walk Test, Timed-Up-and-Go, and Berg Balance Scale for the lower extremity section; and the National Institutes of Health Stroke Scale, and Barthel Index or Functional Independence Measure for the ADL/stroke-specific section. The Stroke Impact Scale was recommended spanning all ICF domains. Recommended measurement time points are days 2 ± 1 and 7; weeks 2, 4, and 12; 6 months poststroke and every following 6th month.
Discussion and Conclusion: Agreement was found upon a set of nine outcome measures for application in clinical motor rehabilitation poststroke, with seven measurement time points following the stages of poststroke recovery. This core set was specifically developed for clinical practice and distinguishes itself from initiatives for stroke rehabilitation research. The next challenge is to implement this clinical core set across the full stroke care continuum with the aim to improve the transparency, comparability, and quality of stroke rehabilitation at a regional, national, and international level.
Introduction: Outcome measures are key to tailor rehabilitation goals to the stroke patient's individual needs and to monitor poststroke recovery. The large number of available outcome measures leads to high variability in clinical use. Currently, an internationally agreed core set of motor outcome measures for clinical application is lacking. Therefore, the goal was to develop such a set to serve as a quality standard in clinical motor rehabilitation poststroke.
Methods: Outcome measures for the upper and lower extremities, and activities of daily living (ADL)/stroke-specific outcomes were identified and presented to stroke rehabilitation experts in an electronic Delphi study. In round 1, clinical feasibility and relevance of the outcome measures were rated on a 7-point Likert scale. In round 2, those rated at least as “relevant” and “feasible” were ranked within the body functions, activities, and participation domains of the International Classification of Functioning, Disability, and Health (ICF). Furthermore, measurement time points poststroke were indicated. In round 3, answers were reviewed in reference to overall results to reach final consensus.
Results: In total, 119 outcome measures were presented to 33 experts from 18 countries. The recommended core set includes the Fugl–Meyer Motor Assessment and Action Research Arm Test for the upper extremity section; the Fugl–Meyer Motor Assessment, 10-m Walk Test, Timed-Up-and-Go, and Berg Balance Scale for the lower extremity section; and the National Institutes of Health Stroke Scale, and Barthel Index or Functional Independence Measure for the ADL/stroke-specific section. The Stroke Impact Scale was recommended spanning all ICF domains. Recommended measurement time points are days 2 ± 1 and 7; weeks 2, 4, and 12; 6 months poststroke and every following 6th month.
Discussion and Conclusion: Agreement was found upon a set of nine outcome measures for application in clinical motor rehabilitation poststroke, with seven measurement time points following the stages of poststroke recovery. This core set was specifically developed for clinical practice and distinguishes itself from initiatives for stroke rehabilitation research. The next challenge is to implement this clinical core set across the full stroke care continuum with the aim to improve the transparency, comparability, and quality of stroke rehabilitation at a regional, national, and international level.
Introduction: Outcome measures are key to tailor rehabilitation goals to the stroke patient's individual needs and to monitor poststroke recovery. The large number of available outcome measures leads to high variability in clinical use. Currently, an internationally agreed core set of motor outcome measures for clinical application is lacking. Therefore, the goal was to develop such a set to serve as a quality standard in clinical motor rehabilitation poststroke.
Methods: Outcome measures for the upper and lower extremities, and activities of daily living (ADL)/stroke-specific outcomes were identified and presented to stroke rehabilitation experts in an electronic Delphi study. In round 1, clinical feasibility and relevance of the outcome measures were rated on a 7-point Likert scale. In round 2, those rated at least as “relevant” and “feasible” were ranked within the body functions, activities, and participation domains of the International Classification of Functioning, Disability, and Health (ICF). Furthermore, measurement time points poststroke were indicated. In round 3, answers were reviewed in reference to overall results to reach final consensus.
Results: In total, 119 outcome measures were presented to 33 experts from 18 countries. The recommended core set includes the Fugl–Meyer Motor Assessment and Action Research Arm Test for the upper extremity section; the Fugl–Meyer Motor Assessment, 10-m Walk Test, Timed-Up-and-Go, and Berg Balance Scale for the lower extremity section; and the National Institutes of Health Stroke Scale, and Barthel Index or Functional Independence Measure for the ADL/stroke-specific section. The Stroke Impact Scale was recommended spanning all ICF domains. Recommended measurement time points are days 2 ± 1 and 7; weeks 2, 4, and 12; 6 months poststroke and every following 6th month.
Discussion and Conclusion: Agreement was found upon a set of nine outcome measures for application in clinical motor rehabilitation poststroke, with seven measurement time points following the stages of poststroke recovery. This core set was specifically developed for clinical practice and distinguishes itself from initiatives for stroke rehabilitation research. The next challenge is to implement this clinical core set across the full stroke care continuum with the aim to improve the transparency, comparability, and quality of stroke rehabilitation at a regional, national, and international level.
Background: Inflammatory markers, such as C-reactive Protein (CRP), Interleukin-6 (IL-6), tumor necrosis factor (TNF)-alpha and fibrinogen, are upregulated following acute stroke. Studies have shown associations of these biomarkers with increased mortality, recurrent vascular risk, and poor functional outcome. It is suggested that physical fitness training may play a role in decreasing long-term inflammatory activity and supports tissue recovery.
Aim: We investigated the dynamics of selected inflammatory markers in the subacute phase following stroke and determined if fluctuations are associated with functional recovery up to 6 months. Further, we examined whether exposure to aerobic physical fitness training in the subacute phase influenced serum inflammatory markers over time.
Methods: This is an exploratory analysis of patients enrolled in the multicenter randomized-controlled PHYS-STROKE trial. Patients within 45 days of stroke onset were randomized to receive either four weeks of aerobic physical fitness training or relaxation sessions. Generalized estimating equation models were used to investigate the dynamics of inflammatory markers and the associations of exposure to fitness training with serum inflammatory markers over time. Multiple logistic regression models were used to explore associations between inflammatory marker levels at baseline and three months after stroke and outcome at 3- or 6-months.
Results: Irrespective of the intervention group, high sensitive CRP (hs-CRP), IL-6, and fibrinogen (but not TNF-alpha) were significantly lower at follow-up visits when compared to baseline (p all ≤ 0.01). In our cohort, exposure to aerobic physical fitness training did not influence levels of inflammatory markers over time. In multivariate logistic regression analyses, increased baseline IL-6 and fibrinogen levels were inversely associated with worse outcome at 3 and 6 months. Increased levels of hs-CRP at 3 months after stroke were associated with impaired outcome at 6 months. We found no independent associations of TNF-alpha levels with investigated outcome parameters.
Conclusion: Serum markers of inflammation were elevated after stroke and decreased within 6 months. In our cohort, exposure to aerobic physical fitness training did not modify the dynamics of inflammatory markers over time. Elevated IL-6 and fibrinogen levels in early subacute stroke were associated with worse outcome up to 6-months after stroke.
Clinical Trial Registration: ClinicalTrials.gov, NCT01953549.
Objective: The instrument THERapy-related InterACTion (THER-I-ACT) was developed to document therapeutic interactions comprehensively in the human therapist–patient setting. Here, we investigate whether the instrument can also reliably be used to characterise therapeutic interactions when a digital system with a humanoid robot as a therapeutic assistant is used.
Methods: Participants and therapy: Seventeen stroke survivors receiving arm rehabilitation (i.e., arm basis training (ABT) for moderate-to-severe arm paresis [n = 9] or arm ability training (AAT) for mild arm paresis [n = 8]) using the digital therapy system E-BRAiN over a course of nine sessions. Analysis of the therapeutic interaction: A total of 34 therapy sessions were videotaped. All therapeutic interactions provided by the humanoid robot during the first and the last (9th) session of daily training were documented both in terms of their frequency and time used for that type of interaction using THER-I-ACT. Any additional therapeutic interaction spontaneously given by the supervising staff or a human helper providing physical assistance (ABT only) was also documented. All ratings were performed by two trained independent raters.
Statistical analyses: Intraclass correlation coefficients (ICCs) were calculated for the frequency of occurrence and time used for each category of interaction observed.
Results: Therapeutic interactions could comprehensively be documented and were observed across the dimensions provision of information, feedback, and bond-related interactions. ICCs for therapeutic interaction category assessments from 34 therapy sessions by two independent raters were high (ICC ≥0.90) for almost all categories of the therapeutic interaction observed, both for the occurrence frequency and time used for categories of therapeutic interactions, and both for the therapeutic interaction performed by the robot and, even though much less frequently observed, additional spontaneous therapeutic interactions by the supervisory staff and a helper being present. The ICC was similarly high for an overall subjective rating of the concentration and engagement of patients (0.87).
Conclusion: Therapeutic interactions can comprehensively and reliably be documented by trained raters using the instrument THER-I-ACT not only in the traditional patient–therapist setting, as previously shown, but also in a digital therapy setting with a humanoid robot as the therapeutic agent and for more complex therapeutic settings with more than one therapeutic agent being present.