No description available.

No description available.

Due to its inherent complexity such as limited work volume and degree of freedom, minimally invasive surgery (MIS) is ergonomically challenging to surgeons than traditional open surgery. Specifically, MIS can expose performing surgeons to excessive ergonomic risks including muscle fatigue that may lead to critical errors in surgical procedures. Therefore, detecting the vulnerable muscles and time-to-fatigue during MIS is of great importance in order to prevent these errors. In this research, different surgical skill and ergonomic assessment methods are reviewed and their advantages and disadvantages are studied. According to the literature review, which is included in chapter 1, some of these methods are subjective and those that are objective provide inconsistent results. Muscle fatigue analysis has shown promising results for skill and ergonomic assessments. However, due to the data analysis issues, this analysis has only been successful in intense working conditions. The goal of this research is to apply an appropriate data analysis method to minimally invasive surgical setting which is considered as a low-force muscle activity. Therefore, surface electromyography is used to record muscle activations of subjects while they performed various real laparoscopic operations and dry lab surgical tasks. The muscle activation data is then reconstructed using Recurrence Quantification Analysis (RQA), which has been proven to be a reliable analysis, to detect possible signs of muscle fatigue on different muscle groups. The results of this data analysis method is validated using subjective fatigue assessment method. In order to study the effect of muscle fatigue on subject’s performance, standard Fundamental of Laparoscopic Surgery (FLS) tasks performance analysis is used.

No description available.

No description available.

The human brain is highly sensitive to social information and so is our language production system: people adjust not just what they say but also how they say it in response to the social context. For instance, we are sensitive to the presence of others, and our interactional expectations and goals affect how we individually choose to talk about and refer to things. This thesis is an investigation of the social factors that might lead speakers to adapt linguistically to others. The question of linguistic adaptation is conceived and addressed at two levels: as lexical convergence (i.e., interlocutors coordinating their lexical choices with each other), and as spatial perspective taking in language use (i.e., speakers abandoning their self perspective in favour of another's when verbally locating objects in space). What motivated my research was two-fold. First, I aimed to contribute to the understanding of the interplay between the automatic cognitive accounts and the strategic social accounts of linguistic convergence. At the same time, I wanted to explore new analytical tools for the investigation of interpersonal coordination in conversation (cross-recurrence quantification analysis (CRQA)). Second, there are conflicting explanations as to why people often abandon their self spatial perspective when another person is present in the environment. I aimed to clarify this by bringing together insights from different research fields: spatial language production, spatial cognition, joint attention and joint action. A first set of experiments investigated the effects of speakers' deceptive goals on lexical convergence. Given the extensive evidence that one interlocutor's choices of words shapes another's during collaborative interaction, would we still observe this coordination of linguistic behaviour under conditions of no coordination of intents? In two novel interactive priming paradigms, half of the participants deceived their naïve partner in a detective game (Experiment 1) or a picture naming/matching task (Experiment 2-3) in order to jeopardise their partner's performance in resolving the crime or in a related memory task. Crucially, participants were primed by their partner with suitable-yet-unusual names for objects. I did not find any consistent evidence that deceiving led to a different degree of lexical convergence between deceivers and deceived than between truthful interlocutors. I then explored possibilities and challenges of the use of cross-recurrence quantification analysis (CRQA) (a new analytical tool borrowed from dynamical systems) for the study of lexical convergence in conversation. I applied CRQA in Experiment 4, where I focused on the strategic social accounts of linguistic convergence and investigated whether speakers' tendency to match their interlocutors' lexical choices depended on the social impression that they formed of each other in a previous interaction, and whether this tendency was further modulated by the interactional goal. I developed a novel two-stage paradigm: pairs of participants first experienced a collectivist or an individualistic co-player in an economic decision game (in reality, a pre-set computer programme) and then engaged in a discussion of a survival scenario (this time with the real other) divided in an open-ended vs. joint-goal driven part. I found no evidence that the social impression of their interlocutor affected speakers' degree of lexical convergence. Greater convergence was observed in the joint-goal dialogues, replicating previous findings at syntactic level. Experiments 5-7 left the interactive framework of the previous two sets of experiments and explored spatial perspective taking in a non-interactive language task. I investigated why the presence of a person in the environment can induce speakers to abandon their self perspective to locate objects: Do speakers adapt their spatial descriptions to the vantage point of the person out of intentionality-mediated simulation or of general attention-orienting mechanisms? In an online paradigm, participants located objects in photographs that sometimes contained a person or a plant in various positions with respect to the to-be-located object. Findings were consistent with the simulated intentional accounts and linked non-self spatial perspective in language to the apprehension of another person’s visual affordance. Experiments 8-9 investigated the role of shared experience on perspective taking in spatial language. Prior to any communicative and interactional demand, do speakers adapt their spatial descriptions to the presumed perspective of someone who is attending to the same environment at the same time as them? And is this tendency further affected by the number of co-attendees? I expanded the previous online paradigm and induced participants into thinking that someone else was doing the task at the same time as them. I found that shared experience reinforced self perspective (via shared perspective) rather than reinforcing non-self perspective (via unshared perspective). I did not find any crowd effect.

Diese Arbeit beschäftigt sich mit verschiedenen Aspekten und Anwendungen von Recurrence Plots. Nach einer Übersicht über Methoden, die auf Recurrence Plots basieren, werden neue Komplexitätsmaße eingeführt, die geometrische Strukturen in den Recurrence Plots beschreiben. Diese neuen Maße erlauben die Identifikation von Chaos-Chaos-Übergängen in dynamischen Prozessen. In einem weiteren Schritt werden Cross Recurrence Plots eingeführt, mit denen zwei verschiedene Prozesse untersucht werden. Diese bivariate Analyse ermöglicht die Bewertung von Unterschieden zwischen zwei Prozessen oder das Anpassen der Zeitskalen von zwei Zeitreihen. Diese Technik kann auch genutzt werden, um ähnliche Abschnitte in zwei verschiedenen Datenreihen zu finden. Im Anschluß werden diese neuen Entwicklungen auf Daten verschiedener Art angewendet. Methoden, die auf Recurrence Plots basieren, können an die speziellen Probleme angepaßt werden, so daß viele weitere Anwendungen möglich sind.<br /> <br /> Durch die Anwendung der neu eingeführten Komplexitätsmaße können Chaos-Chaos-Übergänge in Herzschlagdaten vor dem Auftreten einer lebensbedrohlichen Herzrhythmusstörung festgestellt werden, was für die Entwicklung neuer Therapien dieser Herzrhythmusstörungen von Bedeutung sein könnte. In einem weiteren Beispiel, in dem EEG-Daten aus einem kognitiv orientierten Experiment untersucht werden, ermöglichen diese Komplexitätsmaße das Erkennen von spezifischen Reaktionen im Gehirn bereits in Einzeltests. Normalerweise können diese Reaktionen erst durch die Auswertung von vielen Einzeltests erkannt werden.<br /> <br /> Mit der Hilfe von Cross Recurrence Plots wird die Existenz einer klimatischen Zirkulation, die der heutigen El Niño/ Southern Oscillation sehr ähnlich ist, im Nordwesten Argentiniens vor etwa 34000 Jahren nachgewiesen. Außerdem können mit Cross Recurrence Plots die Zeitskalen verschiedener Bohrlochdaten aufeinander abgeglichen werden. Diese Methode kann auch dazu genutzt werden, ein geologisches Profil mit Hilfe eines Referenzprofiles mit bekannter Zeitskala zu datieren. Weitere Beispiele aus den Gebieten der Molekularbiologie und der Spracherkennung unterstreichen das Potential dieser Methode. / In this work, different aspects and applications of the recurrence plot analysis are presented. First, a comprehensive overview of recurrence plots and their quantification possibilities is given. New measures of complexity are defined by using geometrical structures of recurrence plots. These measures are capable to find chaos-chaos transitions in processes. Furthermore, a bivariate extension to cross recurrence plots is studied. Cross recurrence plots exhibit characteristic structures which can be used for the study of differences between two processes or for the alignment and search for matching sequences of two data series. The selected applications of the introduced techniques to various kind of data demonstrate their ability. Analysis of recurrence plots can be adopted to the specific problem and thus opens a wide field of potential applications. <br /> <br /> Regarding the quantification of recurrence plots, chaos-chaos transitions can be found in heart rate variability data before the onset of life threatening cardiac arrhythmias. This may be of importance for the therapy of such cardiac arrhythmias. The quantification of recurrence plots allows to study transitions in brain during cognitive experiments on the base of single trials. Traditionally, for the finding of these transitions the averaging of a collection of single trials is needed. <br /> <br /> Using cross recurrence plots, the existence of an El Niño/Southern Oscillation-like oscillation is traced in northwestern Argentina 34,000 yrs. ago. In further applications to geological data, cross recurrence plots are used for time scale alignment of different borehole data and for dating a geological profile with a reference data set. Additional examples from molecular biology and speech recognition emphasize the suitability of cross recurrence plots.

We study the chaotic phase synchronization (CPS) between the external periodically driving signals and the nonlinear dynamic systems. The periodical signal was applied to drive the Chua circuit system with two-scroll attractor and the four-scroll attractor circuit system. The phase synchronization between the outputs of these two circuit systems and the driving signals were investigated. Besides, the chaotic phase synchronization of the periodically pump-modulated microchip Nd:YVO4 laser and the microchip Nd:YVO4 laser with optical feedback were also examined in this study. Phase synchronization (PS) transition of these periodically driven nonlinear dynamic systems exhibited via the stroboscopic technique and recurrence probability. The recurrence probability and correlation probability of recurrence were utilized to estimate the degree of PS. In this thesis, the degree of PS was studied by taking into account the amplitude and frequency of the external driving signal. The experimental compatible numerical simulations also reflected the fact that the Arnold tongues are experimentally and numerically exhibited in the periodically driven nonlinear dynamic systems.

Sleep disordered breathing (SDB) is a highly prevalent but an under-diagnosed disease. Among adults in the ages between 30 to 60 years, 24% of males and 9% of females show conditions of SDB, while 82% of men and 93% of women with moderate to severe SDB remain undiagnosed. Polysomnography (PSG) is the reference diagnostic test for SDB. During PSG, a number of physiological signals are recorded during an overnight sleep and then manually scored for sleep/wake stages and SDB events to obtain the reference diagnosis. The manual scoring of SDB events is an extremely time consuming and cumbersome task with high inter- and intra-rater variations. PSG is a labour intensive, expensive and patient inconvenient test. Further, PSG facilities are limited leading to long waiting lists. There is an enormous clinical need for automation of PSG scoring and an alternative automated ambulatory method suitable for screening the population. During the work of this thesis, we focus (1) on implementing a framework that enables more reliable scoring of SDB events which also lowers manual scoring time, and (2) implementing a reliable automated screening procedure that can be used as a patient-friendly home based study. The recordings of physiological measurements obtained during patients’ sleep of- ten suffer from data losses, interferences and artefacts. In a typical sleep scoring session, artifact-corrupted signal segments are visually detected and removed from further consideration. We developed a novel framework for automated artifact detection and signal restoration, based on the redundancy among respiratory flow signals. The signals focused on are the airflow (thermistor sensors) and nasal pressure signals that are clinically significant in detecting respira- tory disturbances. We treat the respiratory system as a dynamical system, and use the celebrated Takens embedding theorem as the theoretical basis for sig- nal prediction. In this study, we categorise commonly occurring artefacts and distortions in the airflow and nasal pressure measurements into several groups and explore the efficacy of the proposed technique in detecting/recovering them. Results we obtained from a database of clinical PSG signals indicated that theproposed technique can detect artefacts/distortions with a sensitivity >88% and specificity >92%. This work has the potential to simplify the work done by sleep scoring technicians, and also to improve automated sleep scoring methods. During the next phase of the thesis we have investigated the diagnostic ability of single – and dual–channel respiratory flow measuring devices. Recent studies have shown that single channel respiratory flow measurements can be used for automated diagnosis/screening for sleep disordered breathing (SDB) diseases. Improvements for reliable home-based monitoring for SDB may be achieved with the use of predictors based on recurrence quantification analysis (RQA). RQA essentially measures the complex structures present in a time series and are relatively independent of the nonlinearities present in the respiratory measurements such as those due to breathing nonlinearities and sensor movements. The nasal pressure, thermistor-based airflow, abdominal movement and thoracic movement measurements obtained during Polysomnography, were used in this study to implement an algorithm for automated screening for SDB diseases. The algorithm predicts SDB-affected measurement segments using twelve features based on RQA, body mass index (BMI) and neck circumference using mixture discriminant analysis (MDA). The rate of SDB affected segments of data per hour of recording (RDIS) is used as a measure for the diagnosis of SDB diseases. The operating points to be chosen were the prior probability of SDB affected data segments (π1) and the RDIS threshold value, above which a patient is predicted to have a SDB disease. Cross-validation with five-folds, stratified based on the RDI values of the recordings, was used in estimating the operating points. Sensitivity and specificity rates for the final classifier were estimated using a two-layer assessment approach with the operating points chosen at the inner layer using five-fold cross-validation and the choice assessed at the outer layer using repeated learning-testing. The nasal pressure measurement showed higher accuracy compared to other respiratory measurements when used alone. The nasal pressure and thoracic movement measurements were identified as the best pair of measurements to be used in a dual channel device. The estimated sensitivity and specificity (standard error) in diagnosing SDB disease (RDI ≥ 15) are 90.3(3.1)% and 88.3(5.5)% when nasal pressure is used alone and together with the thoracic movement it was 89.5(3.7)% and 100.0(0.0)%. Present results suggest that RQA of a single respiratory measurement has potential to be used in an automated SDB screening device, while with dual-channel more reliable accuracy can be expected. Improvements may be possible by including other RQA based features and optimisation of the parameters.

Sleep disordered breathing (SDB) is a highly prevalent but an under-diagnosed disease. Among adults in the ages between 30 to 60 years, 24% of males and 9% of females show conditions of SDB, while 82% of men and 93% of women with moderate to severe SDB remain undiagnosed. Polysomnography (PSG) is the reference diagnostic test for SDB. During PSG, a number of physiological signals are recorded during an overnight sleep and then manually scored for sleep/wake stages and SDB events to obtain the reference diagnosis. The manual scoring of SDB events is an extremely time consuming and cumbersome task with high inter- and intra-rater variations. PSG is a labour intensive, expensive and patient inconvenient test. Further, PSG facilities are limited leading to long waiting lists. There is an enormous clinical need for automation of PSG scoring and an alternative automated ambulatory method suitable for screening the population. During the work of this thesis, we focus (1) on implementing a framework that enables more reliable scoring of SDB events which also lowers manual scoring time, and (2) implementing a reliable automated screening procedure that can be used as a patient-friendly home based study. The recordings of physiological measurements obtained during patients’ sleep of- ten suffer from data losses, interferences and artefacts. In a typical sleep scoring session, artifact-corrupted signal segments are visually detected and removed from further consideration. We developed a novel framework for automated artifact detection and signal restoration, based on the redundancy among respiratory flow signals. The signals focused on are the airflow (thermistor sensors) and nasal pressure signals that are clinically significant in detecting respira- tory disturbances. We treat the respiratory system as a dynamical system, and use the celebrated Takens embedding theorem as the theoretical basis for sig- nal prediction. In this study, we categorise commonly occurring artefacts and distortions in the airflow and nasal pressure measurements into several groups and explore the efficacy of the proposed technique in detecting/recovering them. Results we obtained from a database of clinical PSG signals indicated that theproposed technique can detect artefacts/distortions with a sensitivity >88% and specificity >92%. This work has the potential to simplify the work done by sleep scoring technicians, and also to improve automated sleep scoring methods. During the next phase of the thesis we have investigated the diagnostic ability of single – and dual–channel respiratory flow measuring devices. Recent studies have shown that single channel respiratory flow measurements can be used for automated diagnosis/screening for sleep disordered breathing (SDB) diseases. Improvements for reliable home-based monitoring for SDB may be achieved with the use of predictors based on recurrence quantification analysis (RQA). RQA essentially measures the complex structures present in a time series and are relatively independent of the nonlinearities present in the respiratory measurements such as those due to breathing nonlinearities and sensor movements. The nasal pressure, thermistor-based airflow, abdominal movement and thoracic movement measurements obtained during Polysomnography, were used in this study to implement an algorithm for automated screening for SDB diseases. The algorithm predicts SDB-affected measurement segments using twelve features based on RQA, body mass index (BMI) and neck circumference using mixture discriminant analysis (MDA). The rate of SDB affected segments of data per hour of recording (RDIS) is used as a measure for the diagnosis of SDB diseases. The operating points to be chosen were the prior probability of SDB affected data segments (π1) and the RDIS threshold value, above which a patient is predicted to have a SDB disease. Cross-validation with five-folds, stratified based on the RDI values of the recordings, was used in estimating the operating points. Sensitivity and specificity rates for the final classifier were estimated using a two-layer assessment approach with the operating points chosen at the inner layer using five-fold cross-validation and the choice assessed at the outer layer using repeated learning-testing. The nasal pressure measurement showed higher accuracy compared to other respiratory measurements when used alone. The nasal pressure and thoracic movement measurements were identified as the best pair of measurements to be used in a dual channel device. The estimated sensitivity and specificity (standard error) in diagnosing SDB disease (RDI ≥ 15) are 90.3(3.1)% and 88.3(5.5)% when nasal pressure is used alone and together with the thoracic movement it was 89.5(3.7)% and 100.0(0.0)%. Present results suggest that RQA of a single respiratory measurement has potential to be used in an automated SDB screening device, while with dual-channel more reliable accuracy can be expected. Improvements may be possible by including other RQA based features and optimisation of the parameters.