Tese (doutorado)—Universidade de Brasília, Faculdade de Medicina, Programa de Pós-Graduação em Ciências Médicas, 2018. / Submitted by Fabiana Santos (fabianacamargo@bce.unb.br) on 2018-10-01T22:26:10Z No. of bitstreams: 1 2018_MariaLuciaCamposGonçalves.pdf: 1281502 bytes, checksum: bbe3ae145e7491bfe74f46dd29de3f32 (MD5) / Approved for entry into archive by Fabiana Santos (fabianacamargo@bce.unb.br) on 2018-10-08T22:34:00Z (GMT) No. of bitstreams: 1 2018_MariaLuciaCamposGonçalves.pdf: 1281502 bytes, checksum: bbe3ae145e7491bfe74f46dd29de3f32 (MD5) / Made available in DSpace on 2018-10-08T22:34:00Z (GMT). No. of bitstreams: 1 2018_MariaLuciaCamposGonçalves.pdf: 1281502 bytes, checksum: bbe3ae145e7491bfe74f46dd29de3f32 (MD5) Previous issue date: 2018-10-08 / Introdução: Os músculos do assoalho pélvico atuam como suporte dos órgãos pélvicos, estabilizam a articulação sacroilíaca e contribuem como fator esfincteriano nos mecanismos de continência, micção e evacuação. Diversos pesquisadores documentaram a repercussão dos exercícios físicos em atletas como causa ou agravante para as disfunções dos músculos do assoalho pélvico. Objetivo: Estudar os efeitos da prática do exercício físico moderado no ganho funcional da musculatura do assoalho pélvico de mulheres não atletas, por meio do biofeeedback eletromiográfico. Material e método: Participaram 90 mulheres com idade ≥18 anos, que constituíram três grupos, cada um com 30 mulheres: Grupo de Estudo (E) - mulheres que iniciaram a prática regular de exercício físico assim que ingressaram na pesquisa. Grupo Exercício físico (EF) - mulheres que já praticavam exercício físico e Grupo Controle (C) - mulheres que se mantiveram sedentária durante todo o estudo. Todas foram avaliadas por biofeedback de eletromiografia dos músculos do assoalho pélvico, realizadas em dois momentos: ao ingressar na pesquisa (T1) e ao final do 3º mês subsequente a primeira mensuração (T2). Resultado: A média de idade das participantes foi de 35,7±9,75 anos sem diferença estatística entre os grupos (grupo E 34,70±10,07, grupo C 35,73±9,67 e grupo EF 36,67±9,75 - p=0,7412). Os valores médios do biofeedback eletromiográfico dos músculos do assoalho pélvico no T1 apresentaram diferença estatística significante entre os três grupos (grupo E 13,12±1,96μv, grupo C 13,43±12,8μv; 14,1 e grupo EF 15,00 ±2,44 μv p = 0,0013). Os valores de T1 nos grupos E e C foram menores do que no grupo EF (valores de p = 0,0020 e p = 0,0127, respectivamente). Não houve diferença estatisticamente significante entre os grupos E e C (valor de p = 1,0000). Na comparação entre os grupos para os valores obtidos no T2, o grupo E foi o que apresentou maior valor quando comparado aos grupos C e EF (Grupo E18,5μv X Grupo C 15,3μv valor de p < 0,0001, Grupo E X Grupo EF 16,1μv p = 0,0008). Não houve diferença estatisticamente significante entre os grupos S e EF. O grupo E apresentou a maior variação entre T1 e T2 para análise ajustada para idade, seguidos dos grupos EF e grupo C (Grupo E 4,7μv p<0,0001, Grupo EF 2,1μv p<0,0001 e C 1,5 p=0,0002). Conclusão: É possível concluir que mulheres praticantes de exercício físico moderado apresentam melhor função muscular do assoalho pélvico do que as mulheres sedentárias. / Introduction: Several investigators have documented physical exercise as a cause of pelvic floor muscle dysfunction in female athletes. However, studies in non-athletes are lacking. Objective: To assess the influence of moderate physical exercise on pelvic floor muscle electromyographic (EMG) biofeedback signal in female non-athletes. Material and Method: Prospective, non-randomized design. The sample comprised 90 adult women (age ≥18 years), divided into three groups: Intervention (I), women who began physical exercise upon study enrollment; Moderate Exercise (ME), women who already engaged in physical activity; and Sedentary (S), women who led a sedentary lifestyle. All underwent EMG biofeedback of the pelvic floor muscles upon study enrollment (T1) and at the end of the 3rd subsequent month (T2). Results: Mean age was 35.7 (SD: 7.5) years, with no significant difference across groups. T1 values in groups I and S were lower than in group ME (p=0.0020 and p=0.0127, respectively). There was no statistically significant difference between groups S and I (p=1.0000). On comparison across groups at T2, values were highest in group I (18.5 μV vs. 15.3 μV in group S, p<0.0001; vs. 16.1 μV in group ME, p=0.0008). There was no statistically significant difference between groups S and ME. On age-adjusted analysis, group I exhibited the greatest change between T1 and T2 (I, 4.7 μV, p<0.0001; ME, 2.1 μV, p<0.0001; S, 1.5 μV, p=0.0002). Conclusion: Women who exercise exhibit better pelvic floor muscle function than women who do not engage in physical activity.

Five studies were performed to explore the feasibility of treating severe chronic stuttering with EMG feedback. EMG spiking from the throat was found to correlate with stuttering, and to differentiate between stuttering and fluent speech. EMG spiking tended to disappear when stuttering was reduced by metronome-paced speech and by speech therapy. Likewise, when EMG spiking was reduced by feedback training, stuttering was concurrently reduced. Presentation of the feedback tone without instructions or information produced no reduction in stuttering or EMG spiking. Pseudofeedback was also generally ineffective. It was concluded that the feedback effect is apparently not an artifact of instructions, masking, distraction, adaptation, slowing of speech, or of a stutter-contingent aversive tone, nor is it a Hawthorne or placebo effect. Implications of the results are discussed. / Arts, Faculty of / Psychology, Department of / Graduate

This study investigated the relationship among anxiety, depression, and sleep disturbances and the treatment of these three disorders through neurotherapy. Research suggests that these conditions commonly co-occur in the general population and that central nervous system (CNS) arousal may play a primary role in the development and maintenance of these disorders. Several recent studies suggested that neurotherapy, a biofeedback-based treatment for CNS dysregulation, might be an effective treatment for comorbid conditions, particularly the ones of interest here, depression, anxiety, and sleep disturbances. This investigation used a clinical case-series design to assess pre/post neurotherapy changes on objective measures of anxiety, depression, and sleep and to determine whether changes in anxiety and depression then predict improvements in sleep quality. Data for 23 participants (10 males) were obtained from files of adults (Mage = 40.22 years, SD = 16.20) who received at least 15 neurotherapy sessions (M = 47.83 sessions, SD = 22.23) the University of North Texas Neurotherapy Lab. Matched pair t-tests revealed that symptoms of sleep disturbance, depression, and anxiety showed significant improvements following neurotherapy. Neurotherapy treatment effect sizes generally ranged from moderate to large (d = .414 - .849). Multiple regression analysis found that changes in self-reported anxiety symptoms, but not depressive symptoms, predicted observed improvements in sleep quality (adjusted R2 = .26). Last, the implications and limitations were discussed in relation to neurotherapy practice and the associated research.

No description available.

No description available.

The repeated-measures experimental design utilized in the present study permitted a controlled comparison of the clinical efficacy of meditation treatment (MT), biofeedback treatment (BT), and pharmacological control (PC) conditions in the reduction of seven dependent variables: (1) within clinic (W-C) systolic blood pressure (SBP), (2) W-C diastolic blood pressure (DBP), (3) outside-clinic (0-C) SEP, (4) 0-C DBP, (5) within-session (W-S) SEP, (6) W-S DBP, and (7) antihypertensive medication requirements. Twenty-four medicated subjects with medically .verified essential hypertension were matched by rank-order on sex, age, and mean baseline levels of SBP and DBP, and randomly assigned to MT, BT, or PC conditions, each composed of five females and three males.

Using a single-subject multiple baseline design across participants, this study examined the impact of computer-assisted biofeedback to promote engagement of students diagnosed as having autism spectrum disorder. The study was conducted in a public school classroom setting. Specifically the on-task behavior during an individualized academic activity was investigated. Three 9-10 year old children participated in the study. In the baseline phase, data was collected on speed to engagement and percentage of time on-task during an academic activity. A 15-second momentary time sampling procedure was used for a 5 minute session each day of the week for a five week period to measure the participant's engagement. In the intervention phase, the participants completed a three to four minute computer-assisted biofeedback session prior to the academic activity and collection of data on engagement. In addition, data were collected on performance level of the academic activity. Data were also collected on educator and parent perception of generalization of self-regulation of behavior. The data suggest: (a) speed to engagement increased when using a computer-assisted biofeedback program for all participants; (b) time on-task improved over baseline conditions for all participants; (c) academic achievement was impacted by computer-assisted biofeedback for one participant; and (d) educators perceived a generalization of self-regulation of behavior, while parents did not indicate any generalization of self-regulation of behavior occurred in the home environment.

Hintergrund: Das Auftreten einer kardialen autonomen Dysfunktion nach einem akutem ischämischen Schlaganfall (AIS) geht mit einer ungünstigen Prognose und einer erhöhten Mortalität einher. In der vorliegenden Arbeit wurde die Hypothese untersucht, dass Herzfrequenzvariabilitäts (HRV)-Biofeedback die autonome Herzfunktion nach Schlaganfall verbessern kann. Methodik/Design: 48 AIS-Patienten erhielten unter randomisierten Bedingungen entweder HRV- oder Sham-Biofeedback (1:1) zusätzlich zur standardisierten Stroke Unit Versorgung. Bei sämtlichen Studienteilnehmern wurde vor Beginn der ersten und nach Abschluss der letzten Biofeedbacksitzung eine autonome Funktionsmessung durchgeführt, die neben der Messung der HRV auch eine Erfassung der autonomen vasomotorischen (die neurovaskuläre Regulation der arteriellen Blutgefäßweite erfassenden) und sudomotorischen (die neuronale Regulation der Schweißdrüsenfunktion quantifizierenden) Funktion beinhaltete. Die HRV wurde mittels Standardabweichung der NN-Intervalle (SDNN), der Standardabweichung der Differenzen benachbarter NN-Intervalle (SD of ΔNN), der Quadratwurzel des Mittelwerts aus der Summe der Quadrate der Differenzen zwischen benachbarten NN-Intervallen (RMSSD), sowie mittels des Variationskoeffizienten der R-R-Intervalle (CVNN) untersucht. Während die Parameter SDNN und RMSSD vorwiegend parasympathisch determinierten Indikatoren der HRV entsprechen, stellt der CVNN einen kompositen Parameter der sympathischen und der parasympathischen Aktivität dar. Darüber hinaus wurde eine Frequenzanalyse der HRV durchgeführt, um die Frequenzbänder der HRV differenziert zu erfassen und den Wirkmechanismus des HRV-Biofeedbacks auf die kardiale autonome Funktion zu charakterisieren. Die beiden sympathisch regulierten Funktionen der Vaso- und Sudomotorik wurden nach sympathischer Aktivierung gemessen, wobei die vasomotorische Funktion mittels Photoplethysmographie (PPG) der vasokonstriktorischen Reaktion (VCR) und die sudomotorische Hautleitwertänderung (SSR) durch Ableiteelektroden erfasst wurde. Die Bewertung des Schweregrades der autonomen Symptome durch den Survey of Autonomic Symptoms (SAS; TIS: Gesamtschwere autonomer Symptome) und des funktionellen Defizites durch die modifizierte Rankin-Skala (mRS) erfolgten vor Beginn der Intervention und drei Monate nach Interventionsbeendigung. Das Studienprotokoll wurde vor Beginn der Untersuchung in der Datenbank clinicaltrials.gov hinterlegt [clinicaltrials.gov identifier: NCT03865225]. Ergebnisse: 48 AIS-Patienten (19 Frauen; Alter im Median 69 [Interquartilsbereich 18.0] Jahre) wurden in die Untersuchung eingeschlossen. Angesichts einer hohen Adhärenz und Verträglichkeit der HRV-Biofeedbackanwendung (<0.1% fehlende Daten, keine Studienabbrühe während der Hospitalisierungsphase, unerwünschte Wirkungen: leichtgradig n=1/48) ließ sich das HRV-Biofeedbackverfahren unproblematisch in das das Setting einer multidisziplinären Stroke Unit integrieren. Die Anwendung von HRV-Biofeedback führte zu einer Erhöhung der HRV unter metronomischer Atmung (SDNN: 34,1 [45.0] ms Baseline vs. 43,5 [79.0] ms post-Intervention, p=0,015; SD of ΔNN: 29.3 [52.7] ms baseline vs. 46.4 [142.1] ms post-intervention, p=0.013; RMSSD: 29,1 [52.2] ms Baseline vs. 46,0 [140.6] ms post-Intervention, p=0.015; nicht-signifikanter Trend einer Erhöhung des CVNN: 4.1 [5.1] % Baseline vs. 5.4 [7.2] % post-Intervention, p=0.052), die nach dem Sham-Biofeedback nicht zu verzeichnen war (p=nicht signifikant (ns)). Zudem ergab die Frequenzanalyse der HRV unter metronomischer Atmung nach HRV-Biofeedback einen Anstieg im Niederfrequenzband (LF) (484.8 [1941.4] ms2 Baseline vs. 1471.3 [3329.9] ms2 post-Intervention, p=0.019) und der Total Power (1273.9 [3299.2] ms2 Baseline vs. 1771.5 [13038.8] ms2 post-Intervention, p=0.022), der in der Sham-Biofeedbackgruppe nicht beobachtet wurde (p=ns). In beiden Studiengruppen zeigte sich keine Veränderung der sympathischen Funktionen der Sudo- und Vasomotorik (p=ns). HRV-Biofeedback führte zu einer Linderung des Schweregrades autonomer Symptome drei Monate nach der Intervention (TIS: 7.5 [7.0] Baseline vs. 3.5 [8.0] Follow-Up, p=0.029), welche in der Sham-Biofeedbackgruppe ausblieb (p=ns). Erwartungsgemäß zeigten beide Studiengruppen nach drei Monaten eine Besserung der funktionellen Defizite (HRV-Biofeedbackgruppe, mRS: 2.0 [1.0] Baseline vs. 0.0 [2.0] Follow-Up, p=0.023; Sham-Biofeedbackgruppe, mRS: 2.2 [2.0] Baseline vs. 1.0 [2.0] Follow-Up, p=0.0005). Schlussfolgerungen: Die Integration von HRV-Biofeedback in die multidisziplinäre Standardversorgung einer Schlaganfallstation führte bei Patienten mit AIS zu einer Verbesserung der kardialen autonomen Funktion. Diese funktionelle Verbesserung wurde wahrscheinlich durch einen vorwiegend parasympathischen Mechanismus vermittelt und ging mit einer anhaltenden Linderung autonomer Symptome einher.:1.EINLEITUNG 1 2. HINTERGRUND 4 2.1 Schlaganfall: Pathophysiologie und klinische Bedeutung 4 2.1.1 Definition und Klassifikation 4 2.1.2 Epidemiologie 7 2.1.3 Lokalisationsbezogene klinische Präsentation 9 2.1.4 Therapie 13 2.1.5 Risikofaktoren 16 2.2 Autonomes Nervensystem (ANS): Grundlagen und Beeinträchtigungen bei Schlaganfallpatienten16 2.2.1 Anatomische und physiologische Grundlagen 17 2.2.1.1 Sympathisches Nervensystem (SNS) 20 2.2.1.2 Parasympathisches Nervensystem (PaNS) 22 2.2.1.3 Enterisches Nervensystem (ENS) 23 2.2.2 Autonome Dysfunktion beim Schlaganfall 24 2.3 Herzratenvariabilität (HRV): Ein diagnostisches Target der kardialen autonomen Funktion 25 2.3.1 Definition 25 2.3.2 Relevanz 27 2.3.3 Anwendungsbereiche 28 2.4 Biofeedback: Allgemeine Therapieprinzipien und HRV-spezifische Anwendung 29 2.4.1 Definition 29 2.4.2 Anwendungsbereiche 29 2.4.3 Herzratenvariabilitäts-gestütztes Biofeedback 31 3. FORSCHUNGSLÜCKE („RESEARCH GAP“) 32 4. ZIELSETZUNG UND HYPOTHESEN 32 5. METHODIK 33 5.1 Ethik 33 5.2 Studiendesign und Messprotokoll 34 5.3 Patienten 36 5.3.1 Patientenrekrutierung 36 5.3.2 Einschlusskriterien 36 5.3.3 Ausschlusskriterien 36 5.3.4 Patienteninformation und -einverständniserklärung 37 5.3.5 Randomisierung 37 5.4 Funktionsmessungen 37 5.4.1 Funktionen des autonomen Nervensystems 37 5.4.1.1 Kardiale autonome Funktion: Herzratenvariabilität (HRV) 40 5.4.1.2 Sudomotorische autonome Funktion: Sympathetic Skin Response (SSR) 44 5.4.1.3 Vasomotorische autonome Funktion: Photoplethysmographie (PPG) 46 5.4.2 Symptomschwere und funktionelle Beeinträchtigung 48 5.4.2.1 Autonomes Outcome: Survey of Autonomic Symptoms (SAS) 48 5.4.2.2 Funktionelles Outcome: modified Rankin Scale (mRS) 49 5.4.2.3 Neurologisches Outcome: National Institutes of Health Stroke Scale (NIHSS) 49 5.5 Studienintervention: Herzratenvariabilitätsgestütztes Biofeedback 50 5.6 Statistische Analyse 51 6. ERGEBNISSE 52 6.1 Demographische Daten und Baseline-Charakteristika 52 6.2 Rekrutierung und fehlende Daten 54 6.3 Autonome Funktionsmessungen 56 6.3.1 Kardiale autonome Funktion: Herzratenvariabilität (HRV) 56 6.3.2 Sudomotorische autonome Funktion: Sympathetic Skin Response (SSR) 61 6.3.3 Vasomotorische autonome Funktion: Photoplethysmographie (PPG) 61 6.4 Symptomschwere und funktionelle Beeinträchtigung 62 6.4.1 Autonomes Outcome: Survey of Autonomic Symptoms (SAS) 62 6.4.2 Funktionelle Beeinträchtigung: modified Rankin Scale (mRS) 63 7. DISKUSSION 63 7.1. Zentrale Erkenntnisse 63 7.2 Autonome Funktionen 64 7.2.1 Kardiale autonome Funktion: Herzratenvariabilität (HRV) 64 7.2.2 Sudomotorische Funktionsmessung: Sympathetic Skin Response (SSR) 71 7.2.3 Vasomotorische Flussmessung 72 7.3 Symptomschwere und funktionelle Beeinträchtigung 73 7.3.1 Symptome des autonomen Nervensystems: Survey of Autonomic Symptoms (SAS) 73 7.3.2 Funktionelle Beeinträchtigung: modified Rankin Scale (mRS) 75 7.4 Limitationen und Ausblick 76 8. ZUSAMMENFASSUNG 78 8.1 Zusammenfassung 78 8.2. Summary 80 9. LITERATURVERZEICHNIS 82 10. ANHANG 109 10.1 Anhang I Fragebögen Klinischer Outcomes 109 10.2 Anhang II Demographische Daten 112 10.3. Anhang III Autonome Funktionsmessungen 116 10.4 Anhang IV Symptomschwere und funktionelle Beeinträchtigung 119 10.5 Erklärung zur Eröffnung des Promotionsverfahrens 122 10.6 Erklärung zur Einhaltung gesetzlicher Vorgaben 123 / Background: The occurrence of cardiac autonomic dysfunction following acute ischaemic stroke (AIS) worsens clinical outcome and is associated with an increased mortality. Therefore, we tested the hypothesis that heart rate variability (HRV) biofeedback can improve autonomic cardiac function post stroke. Methods/Design: We allocated (1:1) 48 AIS patients in a randomized fashion to undergo nine sessions of either HRV- or sham-biofeedback over three days in addition to standard stroke unit care. Autonomic function measurements, consisting of measurements of HRV, vasomotor (neurovascular control of arterial blood flow) and sudomotor (neural sweat gland control) function, were performed in all study participants before the start of the first biofeedback session and after completion of the last session. HRV was assessed using standard deviation of NN intervals (SDNN), a marker for primarily parasympathetically mediated cardiac modulation, Standard deviation of differences between adjacent NN intervals (SD of ΔNN) and root mean square of successive differences between normal heartbeats (RMSSD), a predominantly parasympathetic measure of HRV as well as via coefficient of variation of R-R intervals (CVNN), a composite parameter of sympathetic and parasympathetic activity. Moreover, frequency analysis of HRV components was carried out to further explore the mechanism whereby HRV biofeedback alters cardiac autonomic function. Both sympathetically regulated vasomotor and sudomotor functions were measured after sympathetic activation with vasomotor function recorded by photoplethysmography (PPG) of vasoconstrictory response (VCR) and sudomotor skin conductance changes of the sympathetic skin response (SSR) by conduction electrodes. Assessment of severity of autonomic symptoms via Survey of Autonomic Symptoms (SAS; TIS: Total symptom score) and functional deficits via modified Rankin scale (mRS) was performed before the start of the intervention and three months post intervention. The study protocol was registered at clinicaltrials.gov prior to commencement of study [clinicaltrials.gov identifier: NCT03865225]. Results: We included 48 AIS patients (19 females; ages median 69 [interquartile range 18.0] years. Implementation of HRV biofeedback into the setting of a stroke unit was feasible with no dropouts and high adherence and tolerability. Adding HRV biofeedback to stroke unit care led to an increased HRV under metronomic breathing (SDNN: 34.1 [45.0] ms baseline vs. 43.5 [79.0] ms post-intervention, p=0.015; SD of ΔNN: 29.3 [52.7] ms baseline vs. 46.4 [142.1] ms post-intervention, p=0.013; RMSSD: 29.1 [52.2] ms baseline vs. 46.0 [140.6] ms post-intervention, p=0.015; non-significant trend towards increase in CVNN: 4.1 [5.1] % baseline vs. 5.4 [7.2] % post-intervention, p=0.052) which was not seen after sham biofeedback (p=non-significant (ns)). In addition, frequency analysis of HRV revealed an increase in the low frequency band (LF) under metronomic breathing (484.8 [1941.4] ms2 baseline vs. 1471.3 [3329.9] ms2 post-intervention, p=0.019 and in total power (Total Power: 1273.9 [3299.2] ms2 baseline vs. 1771.5 [13038.8] ms2 post-intervention, p=0.022) after HRV biofeedback, which was not seen in the sham biofeedback group (p=ns). No changes in sympathetic sudomotor and vasomotor functions were detected in either study group (p=ns). HRV biofeedback led to a decrease of severity of autonomic symptoms (TIS: 7.5 [7.0] baseline vs. 3.5 [8.0] follow-up, p=0.029), which was absent in the sham biofeedback group. (p=ns). As expected both study groups showed an alleviation of functional deficits after three months (HRV biofeedback group, mRS: 2.0 [1.0] baseline vs. 0.0 [2.0] follow-up, p=0.023; Sham biofeedback group, mRS: 2.2 [2.0] baseline vs. 1.0 [2.0] follow-up, p=0.0005). Conclusions: Integrating HRV biofeedback into standard multidisciplinary stroke unit care for AIS led to improved cardiac autonomic function. This functional improvement was likely mediated by a predominantly parasympathetic mechanism and translated into sustained alleviation of autonomic symptoms.:1.EINLEITUNG 1 2. HINTERGRUND 4 2.1 Schlaganfall: Pathophysiologie und klinische Bedeutung 4 2.1.1 Definition und Klassifikation 4 2.1.2 Epidemiologie 7 2.1.3 Lokalisationsbezogene klinische Präsentation 9 2.1.4 Therapie 13 2.1.5 Risikofaktoren 16 2.2 Autonomes Nervensystem (ANS): Grundlagen und Beeinträchtigungen bei Schlaganfallpatienten16 2.2.1 Anatomische und physiologische Grundlagen 17 2.2.1.1 Sympathisches Nervensystem (SNS) 20 2.2.1.2 Parasympathisches Nervensystem (PaNS) 22 2.2.1.3 Enterisches Nervensystem (ENS) 23 2.2.2 Autonome Dysfunktion beim Schlaganfall 24 2.3 Herzratenvariabilität (HRV): Ein diagnostisches Target der kardialen autonomen Funktion 25 2.3.1 Definition 25 2.3.2 Relevanz 27 2.3.3 Anwendungsbereiche 28 2.4 Biofeedback: Allgemeine Therapieprinzipien und HRV-spezifische Anwendung 29 2.4.1 Definition 29 2.4.2 Anwendungsbereiche 29 2.4.3 Herzratenvariabilitäts-gestütztes Biofeedback 31 3. FORSCHUNGSLÜCKE („RESEARCH GAP“) 32 4. ZIELSETZUNG UND HYPOTHESEN 32 5. METHODIK 33 5.1 Ethik 33 5.2 Studiendesign und Messprotokoll 34 5.3 Patienten 36 5.3.1 Patientenrekrutierung 36 5.3.2 Einschlusskriterien 36 5.3.3 Ausschlusskriterien 36 5.3.4 Patienteninformation und -einverständniserklärung 37 5.3.5 Randomisierung 37 5.4 Funktionsmessungen 37 5.4.1 Funktionen des autonomen Nervensystems 37 5.4.1.1 Kardiale autonome Funktion: Herzratenvariabilität (HRV) 40 5.4.1.2 Sudomotorische autonome Funktion: Sympathetic Skin Response (SSR) 44 5.4.1.3 Vasomotorische autonome Funktion: Photoplethysmographie (PPG) 46 5.4.2 Symptomschwere und funktionelle Beeinträchtigung 48 5.4.2.1 Autonomes Outcome: Survey of Autonomic Symptoms (SAS) 48 5.4.2.2 Funktionelles Outcome: modified Rankin Scale (mRS) 49 5.4.2.3 Neurologisches Outcome: National Institutes of Health Stroke Scale (NIHSS) 49 5.5 Studienintervention: Herzratenvariabilitätsgestütztes Biofeedback 50 5.6 Statistische Analyse 51 6. ERGEBNISSE 52 6.1 Demographische Daten und Baseline-Charakteristika 52 6.2 Rekrutierung und fehlende Daten 54 6.3 Autonome Funktionsmessungen 56 6.3.1 Kardiale autonome Funktion: Herzratenvariabilität (HRV) 56 6.3.2 Sudomotorische autonome Funktion: Sympathetic Skin Response (SSR) 61 6.3.3 Vasomotorische autonome Funktion: Photoplethysmographie (PPG) 61 6.4 Symptomschwere und funktionelle Beeinträchtigung 62 6.4.1 Autonomes Outcome: Survey of Autonomic Symptoms (SAS) 62 6.4.2 Funktionelle Beeinträchtigung: modified Rankin Scale (mRS) 63 7. DISKUSSION 63 7.1. Zentrale Erkenntnisse 63 7.2 Autonome Funktionen 64 7.2.1 Kardiale autonome Funktion: Herzratenvariabilität (HRV) 64 7.2.2 Sudomotorische Funktionsmessung: Sympathetic Skin Response (SSR) 71 7.2.3 Vasomotorische Flussmessung 72 7.3 Symptomschwere und funktionelle Beeinträchtigung 73 7.3.1 Symptome des autonomen Nervensystems: Survey of Autonomic Symptoms (SAS) 73 7.3.2 Funktionelle Beeinträchtigung: modified Rankin Scale (mRS) 75 7.4 Limitationen und Ausblick 76 8. ZUSAMMENFASSUNG 78 8.1 Zusammenfassung 78 8.2. Summary 80 9. LITERATURVERZEICHNIS 82 10. ANHANG 109 10.1 Anhang I Fragebögen Klinischer Outcomes 109 10.2 Anhang II Demographische Daten 112 10.3. Anhang III Autonome Funktionsmessungen 116 10.4 Anhang IV Symptomschwere und funktionelle Beeinträchtigung 119 10.5 Erklärung zur Eröffnung des Promotionsverfahrens 122 10.6 Erklärung zur Einhaltung gesetzlicher Vorgaben 123

<p> The effectiveness of auditory frontalis EMG feedback as a means of teaching general relaxation to spastic and athetoid cerebral palsy individuals was investigated in a pilot study. It was hypothesized that an increase in voluntary ability to reduce levels of muscle activity would translate into improved functional skills and act as an effective coping response in dealing with stress and anxiety.</p> <p> Two subjects - one athetoid (female; 16 years old) and the other spastic (male; 19 years old were studied in depth, each through the use of an A-B-A single-subject design, where the B phase consisted of ten 15-minute sessions of auditory feedback of the frontalis muscle. Generalization of relaxation was assessed by monitoring forearm flexor and extensor muscle activity, peripheral skin temperature, and respiration rate. A Tektronix 4051 desktop computer was utilized to facilitate data management. In addition to the physiological measures, functional evaluations were conducted prior to and after training and a questionnaire was answered by the subject's relatives. Although there was no clear tendency for either subject to reduce absolute levels of EMG, one subject demonstrated a striking reduction in variability of muscle activity across sessions. Functional assessments for these subjects indicated mild to moderate improvements.</p> / Thesis / Master of Engineering (MEngr)

Anterior cruciate ligament (ACL) injuries are common orthopaedic injuries among athletes who participate in sports that involve cutting and changing directions. Many of these adolescent athletes intend to return to sports (RTS), and therefore undergo ACL reconstruction (ACLR). These athletes exhibit unfavorable landing biomechanics from muscle atrophy and asymmetrical neuromuscular control post-ACLR, putting them at a higher risk of re-injury. Thus, rehabilitation following ACLR is important to improve kinetic and kinematic outcomes and reduce re-injury risk. Biofeedback during rehabilitation is thought to be one way to potentially restore neuromuscular control deficits of athletes recovering from ACLR. Therefore, understanding the effectiveness of a biofeedback intervention on factors associated with re-injury among post-ACLR patients is essential in successful RTS. The purpose of this study is to analyze the effect of a 6-week biofeedback intervention on eccentric knee joint power (ECCKP), limb stiffness, and limb stiffness symmetry (using normalized symmetry index, NSI), in addition to secondary lower extremity outcomes that are associated with these metrics, during landing among patients following ACLR. This study used data collected from an ACL-Biofeedback Trial (ClinicalTrials.gov: AR069865) where participants were randomized into a biofeedback (BF) or control group (C). The BF group received visual and tactile feedback during a series of controlled squats while the C group participated in several online and in-person educational sessions. Participants completed 10 stop-jump tasks before (pre), after (post), and 6 weeks after (ret) the intervention. Kinetic, kinematic, and ground reaction forces (GRF) were collected from embedded force plates and 3D motion capture. Partaking in a biofeedback intervention did not improve ECCKP, limb stiffness, or limb stiffness NSI compared to controls. A group-by-time interaction was found for hip excursion (p=0.035), and a main effect of time was found for ECCKP, with this variable increasing by 18.5% from pre to ret (p=0.001). In addition, when considering surgical versus non-surgical limbs, this cohort exhibited interlimb asymmetries in stiffness, peak resultant GRF (rGRF), and time to reach peak rGRF (p<0.009). Further, a group-by-limb interaction (p=0.005) and a 7.1% reduction in peak rGRF were found from post to ret (p=0.02). Participants in this study also exhibited limb stiffness asymmetry greater than 10%, which supports existing literature that observed interlimb asymmetries in athletes following ACLR around the typical RTS time (9-12 months post-ACLR). The results from this analysis demonstrated that the current biofeedback intervention was inadequate in improving ECCKP, limb stiffness, and limb stiffness NSI, but additional biofeedback studies with larger sample sizes that investigate task dependencies are needed to better understand the effectiveness of biofeedback interventions. / Master of Science / Anterior cruciate ligament (ACL) injuries are common orthopaedic injuries among athletes who participate in sports that involve cutting and changing directions. Many of these adolescent athletes intend to return to their pre-injury level, therefore undergo a surgical procedure called ACL reconstruction (ACLR). However, following this procedure, athletes display unsafe and stiff landing patterns due to muscle weakness and asymmetrical neuromuscular, or mind-body, control post-ACLR, which increases their risk of re-injury once they return to sport (RTS) following recovery. Rehabilitation for patients following ACLR is of the utmost importance in improving unsafe movement patterns to reduce the risk of re-injury. Biofeedback training refers to receiving external signals that can be processed and transferred to the muscles in the body. This technique aims to restore the neuromuscular deficits of athletes following ACLR and could potentially be helpful during ACLR rehabilitation. Therefore, understanding the effectiveness of a biofeedback intervention on outcomes associated with an increased risk of re-injury in patients following ACLR is important to safely RTS. The purpose of this study is to determine the effect of a 6-week biofeedback intervention on the ability of the knee to absorb impact forces (quantified as eccentric knee joint power, ECCKP), limb stiffness, and limb stiffness symmetry (measured with normalized symmetry index, NSI), along with secondary outcomes related to these variables, among patients following ACLR. This study used data collected from an ACL-Biofeedback Trial (ClinicalTrials.gov: AR069865) where participants were randomized into a biofeedback (BF) or control group (C). The BF group received visual and resisted feedback during a series of controlled squats while the C group participated in several online and in-person educational sessions. Participants completed 10 stop-jump tasks before and after the intervention, and biomechanical data was obtained. The biofeedback intervention did not result in an improved ability for the knee to absorb impact from landing, and it was not able to decrease limb stiffness or limb stiffness asymmetry. It was able to improve hip excursion, which allows for a favorable, less upright posture when landing. ECCKP improved for both groups, indicating that the biofeedback did not add extra benefit to the participant's rehabilitation outside of the study. Asymmetries were observed between the surgical and non-surgical limbs in limb stiffness, peak GRF, and the time it takes to reach this peak GRF. This sample exhibited limb stiffness asymmetry greater than the recommended 10% threshold, raising concern for when these athletes RTS. The results from this analysis demonstrated that the current biofeedback intervention was inadequate in improving ECCKP, limb stiffness, and limb stiffness NSI, but biofeedback in ACLR rehabilitation can still be efficacious in improving hip biomechanics and overall neuromuscular control but may be task-dependent and call for a larger sample size.