Hedersrelaterat våld och förtryck är ett globalt och komplext problem med begränsad forskning. Skolan har en unik möjlighet att tidigt identifiera och förebygga problematiken. Aktuell studie har genom en fokusgruppsintervju och fyra individuella intervjuer med skolpersonal undersökt hur de identifierar och hanterar hedersrelaterat våld och förtryck, samt hur de stödjer den utsatta eleven. En tematisk analys genomfördes och resulterade i fyra huvudteman med underkategorier: (1) Attityder av hedersrelaterat våld och förtryck, (2) Alliansskapande som grund, och (3) Försvårande faktorer i hanteringsarbetet, och (4) Elevens behov tillgodoses. Resultaten visade att hedersrelaterat våld och förtryck var en nedprioriterad fråga som bottnade i attityder på organisationell- och individuellnivå. Allianskapande mellan skolpersonal och elever, samt samverkan inom som utanför skolan, framkom vara viktiga faktorer i både identifierings- och hanteringsarbetet. Däremot, visade resultaten att en bristande tillit gentemot myndigheter förekom bland både skolpersonal och elever, vilket bidrog till ett försvårat identifierings- och hanteringsarbete. Mer forskning behövs för att undersöka komplexiteten av hedersrelaterat våld och förtryck i en skolkontext. Aktuell studie har dock belyst hur skolpersonals attityder samt tillgång till verktyg, utbildning och erfarenheter påverkar deras arbetssätt. Dessutom, hur stor inverkan en allians mellan skolpersonal och elever utgör. Vad som upplevs vara nödvändigt i det förebyggande och hanteringsarbetet av hedersrelaterat våld och förtryck belyses i aktuell studie och komplexiteten diskuteras.

This project is about trying to apply machine learning theories on a selection of data points in order to see if an improvement of current methodology within stress detection and measure selecting could be applicable for the company Linkura AB. Linkura AB is a medical technology company based in Linköping and handles among other things stress measuring for different companies employees, as well as health coaching for selecting measures. In this report we experiment with different methods and algorithms under the collective name of Unsupervised Learning, to identify visible patterns and behaviour of data points and further on we analyze it with the quantity of data received. The methods that have been practiced on during the project are “K-means algorithm” and a dynamic hierarchical clustering algorithm. The correlation between the different data points parameters is analyzed to optimize the resource consumption, also experiments with different number of parameters are tested and discussed with an expert in stress coaching. The results stated that both algorithms can create clusters for the risk groups, however, the dynamic clustering method clearly demonstrate the optimal number of clusters that should be used. Having consulted with mentors and health coaches regarding the analysis of the produced clusters, a conclusion that the dynamic hierarchical cluster algorithm gives more accurate clusters to represent risk groups were done. The conclusion of this project is that the machine learning algorithms that have been used, can categorize data points with stress behavioral correlations, which is usable in measure testimonials. Further research should be done with a greater set of data for a more optimal result, where this project can form the basis for the implementations. / Detta projekt handlar om att försöka applicera maskininlärningsmodeller på ett urval av datapunkter för att ta reda på huruvida en förbättring av nuvarande praxis inom stressdetektering och  åtgärdshantering kan vara applicerbart för företaget Linkura AB. Linkura AB är ett medicintekniskt företag baserat i Linköping och hanterar bland annat stressmätning hos andra företags anställda, samt hälso-coachning för att ta fram åtgärdspunkter för förbättring. I denna rapport experimenterar vi med olika metoder under samlingsnamnet oövervakad maskininlärning för att identifiera synbara mönster och beteenden inom datapunkter, och vidare analyseras detta i förhållande till den mängden data vi fått tillgodosett. De modeller som har använts under projektets gång har varit “K-Means algoritm” samt en dynamisk hierarkisk klustermodell. Korrelationen mellan olika datapunktsparametrar analyseras för att optimera resurshantering, samt experimentering med olika antal parametrar inkluderade i datan testas och diskuteras med expertis inom hälso-coachning. Resultaten påvisade att båda algoritmerna kan generera kluster för riskgrupper, men där den dynamiska modellen tydligt påvisar antalet kluster som ska användas för optimalt resultat. Efter konsultering med mentorer samt expertis inom hälso-coachning så drogs en slutsats om att den dynamiska modellen levererar tydligare riskkluster för att representera riskgrupper för stress. Slutsatsen för projektet blev att maskininlärningsmodeller kan kategorisera datapunkter med stressrelaterade korrelationer, vilket är användbart för åtgärdsbestämmelser. Framtida arbeten bör göras med ett större mängd data för mer optimerade resultat, där detta projekt kan ses som en grund för dessa implementeringar.

Background: Work-related stress (WRS) is associated with musculoskeletal pain (MSP), changes in the autonomic nervous system (ANS) and anxiety. Objective: To determine the feasibility of a follow-up study and treatment efficacy of the Reaset Approach on MSP, ANS and State-Trait anxiety. Methods: 15 subjects with WRS and MSP were assigned into 3 groups (Body, Head-Neck, Head-Neck-Body). Each group received a single 25 minute ‘Reaset Approach’ intervention. Heart rate variability (HRV), electro-dermal activity (EDA), State Trait Anxiety (STAI) and MSP were measured. Results: HRV parameters: SDNN increased in 13 of 15 subjects while SD1 and SD2 increased in 12 of 15 subjects. EDA reduced in 10 of 14 subjects. State Anxiety reduced in all subjects and Trait Anxiety reduced in 14 of 15 subjects. MSP reduced in all subjects after the intervention and were still lower three days afterwards. Conclusions: This pilot study determined that a follow-up study can ensue provided minor modifications are implemented and that the ‘Reaset Approach’ has an influence on the ANS, anxiety and MSP. Results do differ between groups. The intervention groups including the head and neck modalities demonstrated better results. / Hintergrund: Arbeitsbedingter Stress (ABS) ist verbunden mit muskelschmerzen, Veränderungen im autonomen Nervensystem (ANS) und Angst. Ziel: Machbarkeit einer Follow-up-Studie und Wirksamkeit der Behandlung des Reaset Ansatzes auf ANS, Muskelschmerzen und State und Trait- Angst bestimmen. Methoden: 15 Patienten mit ABS und Muskelschmerzen wurden in 3 Gruppen eingeteilt (Körper, Kopf-Hals, Kopf-Hals-Körper). Jede Gruppe erhielt eine einzige 25 Minuten dauernde 'Reaset Approach’-Behandlung. Herzfrequenzvariabilität (HRV), elektro-dermale Aktivität (EDA), State-Trait-Angstsinventar (STAI) und Muskelschmerzen (SF-MPQ) wurden gemessen. Ergebnisse: Die HRV-wert: SDNN ist bei 13 von 15 Probanden erhöht, während SD1 und SD2 bei 12 von 15 Probanden zugenommen hat. EDA war bei 10 von 14 Probanden reduziert. Die State-Angst hat bei allen Probanden und die Trait-Angst bei 14 der 15 Probanden abgenommen. Muskelschmerzen waren bei alle Probanden anschließend an und drei Tage nach der Intervention reduziert. Schlussfolgerung: Diese Pilotstudie hat gezeigt, dass eine Follow-up-Studie fortgesetzt werden kann, sofern kleinere Änderungen durchgeführt werden. Die 'Reaset Approach’ hat einen günstigen Einfluss auf die ANS, State-Trait-Angst und Muskelschmerzen. Ergebnisse zwischen den Gruppen sind unterschiedlich. Die Interventionsgruppen mit einschließlich der Kopf-Hals-Modalitäten zeigten bessere Ergebnisse..

Background: Work-related stress (WRS) is associated with musculoskeletal pain (MSP), changes in the autonomic nervous system (ANS) and anxiety. Objective: To determine the feasibility of a follow-up study and treatment efficacy of the Reaset Approach on MSP, ANS and State-Trait anxiety. Methods: 15 subjects with WRS and MSP were assigned into 3 groups (Body, Head-Neck, Head-Neck-Body). Each group received a single 25 minute ‘Reaset Approach’ intervention. Heart rate variability (HRV), electro-dermal activity (EDA), State Trait Anxiety (STAI) and MSP were measured. Results: HRV parameters: SDNN increased in 13 of 15 subjects while SD1 and SD2 increased in 12 of 15 subjects. EDA reduced in 10 of 14 subjects. State Anxiety reduced in all subjects and Trait Anxiety reduced in 14 of 15 subjects. MSP reduced in all subjects after the intervention and were still lower three days afterwards. Conclusions: This pilot study determined that a follow-up study can ensue provided minor modifications are implemented and that the ‘Reaset Approach’ has an influence on the ANS, anxiety and MSP. Results do differ between groups. The intervention groups including the head and neck modalities demonstrated better results.:I. Abstract (En) III II. Abstract (De) IV III. Table of Contents V IV. Index of figures VIII V. Index of tables IX VI. Index of abbreviations X 1 Introduction 1 2 Background 2 2.1 Work-related musculoskeletal pain 2 2.2 Work-related stress 3 2.3 Osteopathy and the autonomic nervous system 3 2.4 Stress, pain and osteopathy 4 3 Questions 6 3.1 Feasibility 6 3.2 Treatment effect 6 4 Methods 7 4.1 Study design 7 4.2 Participants 8 4.2.1 Inclusion criteria 8 4.2.2 Exclusion criteria 8 4.2.3 Recruitment 8 4.2.4 Randomization 10 4.3 Parameters 11 4.3.1 Heart rate variability 11 4.3.2 Electro-dermal activity 11 4.3.3 State anxiety 11 4.3.4 Trait anxiety 12 4.3.5 Perceived pain 12 4.4 Measuring Instruments 13 4.4.1 Heart rate variability 13 4.4.2 Electro-dermal Activity 13 4.4.3 State-Trait Anxiety Inventory 13 4.4.4 Short-Form McGill Pain Questionnaire 13 4.5 Interventions 14 4.5.1 Intervention ‘B’: Body 14 4.5.2 Intervention ‘HN’: Head and Neck 16 4.5.3 Intervention ‘HNB’: Head, Neck and Body 16 4.6 Study flow 18 4.7 Statistics 20 5 Results 21 5.1 Autonomic nervous system: Heart rate variability 21 5.1.1 SDNN 22 5.1.2 SD1 25 5.1.3 SD2 28 5.2 Autonomic Nervous System: Electro-dermal activity 31 5.3 Anxiety 34 5.3.1 State anxiety 34 5.3.2 Trait anxiety 37 5.4 Musculoskeletal pain 39 5.4.1 Visual analogue scale 40 5.4.2 Total Short-Form McGill Pain Questionnaire 43 6 Discussion 46 6.1 Discussion of the method 46 6.2 Discussion of the results 50 6.2.1 Autonomic nervous system 50 6.2.1.1 Heart rate variability 50 6.2.1.2 Electro-dermal activity 51 6.2.2 Anxiety 51 6.2.2.1 State anxiety 51 6.2.2.2 Trait Anxiety 52 6.2.3 Musculoskeletal pain 52 6.3 Suggestions for future research 53 7 Conclusion 54 8 Literature 55 9 Addendum 63 9.1 Table: SF-MPQ with Sensory, Affective and Evaluative dimension 63 9.2 Patient Information Sheet 64 9.3 Structured telephone interview 70 9.4 Structured pre-treatment interview 72 9.5 SF-MPQ permission 73 9.6 SF-MPQ 74 9.7 STAI License 76 9.8 STAI forms Y-1 and Y-2 77 / Hintergrund: Arbeitsbedingter Stress (ABS) ist verbunden mit muskelschmerzen, Veränderungen im autonomen Nervensystem (ANS) und Angst. Ziel: Machbarkeit einer Follow-up-Studie und Wirksamkeit der Behandlung des Reaset Ansatzes auf ANS, Muskelschmerzen und State und Trait- Angst bestimmen. Methoden: 15 Patienten mit ABS und Muskelschmerzen wurden in 3 Gruppen eingeteilt (Körper, Kopf-Hals, Kopf-Hals-Körper). Jede Gruppe erhielt eine einzige 25 Minuten dauernde 'Reaset Approach’-Behandlung. Herzfrequenzvariabilität (HRV), elektro-dermale Aktivität (EDA), State-Trait-Angstsinventar (STAI) und Muskelschmerzen (SF-MPQ) wurden gemessen. Ergebnisse: Die HRV-wert: SDNN ist bei 13 von 15 Probanden erhöht, während SD1 und SD2 bei 12 von 15 Probanden zugenommen hat. EDA war bei 10 von 14 Probanden reduziert. Die State-Angst hat bei allen Probanden und die Trait-Angst bei 14 der 15 Probanden abgenommen. Muskelschmerzen waren bei alle Probanden anschließend an und drei Tage nach der Intervention reduziert. Schlussfolgerung: Diese Pilotstudie hat gezeigt, dass eine Follow-up-Studie fortgesetzt werden kann, sofern kleinere Änderungen durchgeführt werden. Die 'Reaset Approach’ hat einen günstigen Einfluss auf die ANS, State-Trait-Angst und Muskelschmerzen. Ergebnisse zwischen den Gruppen sind unterschiedlich. Die Interventionsgruppen mit einschließlich der Kopf-Hals-Modalitäten zeigten bessere Ergebnisse..:I. Abstract (En) III II. Abstract (De) IV III. Table of Contents V IV. Index of figures VIII V. Index of tables IX VI. Index of abbreviations X 1 Introduction 1 2 Background 2 2.1 Work-related musculoskeletal pain 2 2.2 Work-related stress 3 2.3 Osteopathy and the autonomic nervous system 3 2.4 Stress, pain and osteopathy 4 3 Questions 6 3.1 Feasibility 6 3.2 Treatment effect 6 4 Methods 7 4.1 Study design 7 4.2 Participants 8 4.2.1 Inclusion criteria 8 4.2.2 Exclusion criteria 8 4.2.3 Recruitment 8 4.2.4 Randomization 10 4.3 Parameters 11 4.3.1 Heart rate variability 11 4.3.2 Electro-dermal activity 11 4.3.3 State anxiety 11 4.3.4 Trait anxiety 12 4.3.5 Perceived pain 12 4.4 Measuring Instruments 13 4.4.1 Heart rate variability 13 4.4.2 Electro-dermal Activity 13 4.4.3 State-Trait Anxiety Inventory 13 4.4.4 Short-Form McGill Pain Questionnaire 13 4.5 Interventions 14 4.5.1 Intervention ‘B’: Body 14 4.5.2 Intervention ‘HN’: Head and Neck 16 4.5.3 Intervention ‘HNB’: Head, Neck and Body 16 4.6 Study flow 18 4.7 Statistics 20 5 Results 21 5.1 Autonomic nervous system: Heart rate variability 21 5.1.1 SDNN 22 5.1.2 SD1 25 5.1.3 SD2 28 5.2 Autonomic Nervous System: Electro-dermal activity 31 5.3 Anxiety 34 5.3.1 State anxiety 34 5.3.2 Trait anxiety 37 5.4 Musculoskeletal pain 39 5.4.1 Visual analogue scale 40 5.4.2 Total Short-Form McGill Pain Questionnaire 43 6 Discussion 46 6.1 Discussion of the method 46 6.2 Discussion of the results 50 6.2.1 Autonomic nervous system 50 6.2.1.1 Heart rate variability 50 6.2.1.2 Electro-dermal activity 51 6.2.2 Anxiety 51 6.2.2.1 State anxiety 51 6.2.2.2 Trait Anxiety 52 6.2.3 Musculoskeletal pain 52 6.3 Suggestions for future research 53 7 Conclusion 54 8 Literature 55 9 Addendum 63 9.1 Table: SF-MPQ with Sensory, Affective and Evaluative dimension 63 9.2 Patient Information Sheet 64 9.3 Structured telephone interview 70 9.4 Structured pre-treatment interview 72 9.5 SF-MPQ permission 73 9.6 SF-MPQ 74 9.7 STAI License 76 9.8 STAI forms Y-1 and Y-2 77

The United Nation’s definition of honour based violence (HRV) in 1999 defines women’s exposure of violence related to honour. In Sweden, HRV was regarded as a social problem in the 1990’s, when women were murdered by their close family members. Loss of honour was explained as a reason for the killings. Ever since the beginning of debate in Swedish media, science has noticed the complexity of HRV.   The aim of this study was to examine how Swedish social services and administrative courts constructed honour based violence (HRV) when law of mandatory care of minors is used in court cases. The lawsuits regarded both females and males, in the ages of 10-17 years old. We used a document analysis of thirteen court cases from 2016 regarding 2§ Law of mandatory care of minors (LVU), which is a paragraph of deficiencies in care of youths. We used the keyword Honour related violence when searching for court cases. We could determine that physical violence is constructed as legal issues when it’s explained in detail, fragmented and when the minor was regarded as believable to the administrative court. Psychological violence included the involvement of threats, threats of physical violence and threats of forced marriages, and was all seen as an integrated view on violence. Honour was constructed as an isolation of the youths, limiting their social and leisure time and the children were controlled by their guardians. According to social services and administrative courts, the control was not seen as age appropriate.

For most of the naturally occurring signals, especially biomedical signals, the underlying physical process generating the signal is often not fully known, making it difficult to obtain a parametric model. Therefore, signal processing techniques are used to analyze the signal for non-parametrically characterizing the underlying system from which the signals are produced. Most of the real life systems are nonlinear and time varying, which poses a challenge while characterizing them. Additionally, multiple sensors are used to extract signals from such systems, resulting in multichannel signals which are inherently coupled. In this thesis, we counter this challenge by using Recurrence Plot based techniques for characterizing biomedical systems such as heart or brain, using signals such as heart rate variability (HRV), electroencephalogram(EEG) or functional magnetic resonance imaging (fMRI), respectively, extracted from them. In time series analysis, it is well known that a system can be represented by a trajectory in an N-dimensional state space, which completely represents an instance of the system behavior. Such a system characterization has been done using dynamical invariants such as correlation dimension, Lyapunov exponent etc. Takens has shown that when the state variables of the underlying system are not known, one can obtain a trajectory in ‘phase space’ using only the signals obtained from such a system. The phase space trajectory is topologically equivalent to the state space trajectory. This enables us to characterize the system behavior from only the signals sensed from them. However, estimation of correlation dimension, Lyapunov exponent, etc, are vulnerable to non-stationarities in the signal and require large number of sample points for accurate computation, both of which are important in the case of biomedical signals. Alternatively, a technique called Recurrence Plots (RP) has been proposed, which addresses these concerns, apart from providing additional insights. Measures to characterize RPs of single and two channel data are called Recurrence Quantification Analysis (RQA) and cross RQA (CRQA), respectively. These methods have been applied with a good measure of success in diverse areas. However, they have not been studied extensively in the context of experimental biomedical signals, especially multichannel data. In this thesis, the RP technique and its associated measures are briefly reviewed. Using the computational tools developed for this thesis, RP technique has been applied on select single channel, multichannel and multimodal (i.e. multiple channels derived from different modalities) biomedical signals. Connectivity analysis is demonstrated as post-processing of RP analysis on multichannel signals such as EEG and fMRI. Finally, a novel metric, based on the modification of a CRQA measure is proposed, which shows improved results. For the case of single channel signal, we have considered a large database of HRV signals of 112 subjects recorded for both normal and abnormal (anxiety disorder and depression disorder) subjects, in both supine and standing positions. Existing RQA measures, Recurrence Rate and Determinism, were used to distinguish between normal and abnormal subjects with an accuracy of 58.93%. A new measure, MLV has been introduced, using which a classification accuracy of 98.2% is obtained. Correlation between probabilities of recurrence (CPR) is a CRQA measure used to characterize phase synchronization between two signals. In this work, we demonstrate its utility with application to multimodal and multichannel biomedical signals. First, for the multimodal case, we have computed running CPR (rCPR), a modification proposed by us, which allows dynamic estimation of CPR as a function of time, on multimodal cardiac signals (electrocardiogram and arterial blood pressure) and demonstrated that the method can clearly detect abnormalities (premature ventricular contractions); this has potential applications in cardiac care such as assisted automated diagnosis. Second, for the multichannel case, we have used 16 channel EEG signals recorded under various physiological states such as (i) global epileptic seizure and pre-seizure and (ii) focal epilepsy. CPR was computed pair-wise between the channels and a CPR matrix of all pairs was formed. Contour plot of the CPR matrix was obtained to illustrate synchronization. Statistical analysis of CPR matrix for 16 subjects of global epilepsy showed clear differences between pre-seizure and seizure conditions, and a linear discriminant classifier was used in distinguishing between the two conditions with 100% accuracy. Connectivity analysis of multichannel EEG signals was performed by post-processing of the CPR matrix to understand global network-level characterization of the brain. Brain connectivity using thresholded CPR matrix of multichannel EEG signals showed clear differences in the number and pattern of connections in brain connectivity graph between epileptic seizure and pre-seizure. Corresponding brain headmaps provide meaningful insights about synchronization in the brain in those states. K-means clustering of connectivity parameters of CPR and linear correlation obtained from global epileptic seizure and pre-seizure showed significantly larger cluster centroid distances for CPR as opposed to linear correlation, thereby demonstrating the efficacy of CPR. The headmap in the case of focal epilepsy clearly enables us to identify the focus of the epilepsy which provides certain diagnostic value. Connectivity analysis on multichannel fMRI signals was performed using CPR matrix and graph theoretic analysis. Adjacency matrix was obtained from CPR matrices after thresholding it using statistical significance tests. Graph theoretic analysis based on communicability was performed to obtain community structures for awake resting and anesthetic sedation states. Concurrent behavioral data showed memory impairment due to anesthesia. Given the fact that previous studies have implicated the hippocampus in memory function, the CPR results showing the hippocampus within the community in awake state and out of it in anesthesia state, demonstrated the biological plausibility of the CPR results. On the other hand, results from linear correlation were less biologically plausible. In biological systems, highly synchronized and desynchronized systems are of interest rather than moderately synchronized ones. However, CPR is approximately a monotonic function of synchronization and hence can assume values which indicate moderate synchronization. In order to emphasize high synchronization/ desynchronization and de-emphasize moderate synchronization, a new method of Correlation Synchronization Convergence Time (CSCT) is proposed. It is obtained using an iterative procedure involving the evaluation of CPR for successive autocorrelations until CPR converges to a chosen threshold. CSCT was evaluated for 16 channel EEG data and corresponding contour plots and histograms were obtained, which shows better discrimination between synchronized and asynchronized states compared to the conventional CPR. This thesis has demonstrated the efficacy of RP technique and associated measures in characterizing various classes of biomedical signals. The results obtained are corroborated by well known physiological facts, and they provide physiologically meaningful insights into the functioning of the underlying biological systems, with potential diagnostic value in healthcare.

This diploma thesis deals with detection of atrial fibrillation from HRV, classification of Poincare map and in the end the divide into two groups, one with detected atrial fibrillation and one not. The result is the decision on which variables are statistically significant for the identification of atrial fibrillations and which are not, and classification of the ECG signals.

Purpose: This degree project aims to see how the energy demand from active heating of detached houses can be improved to meet the energy performance requirements set for nearly zero-energy buildings by Boverket (The Swedish National Board of Housing, Building and Planning). Method: To accomplish this, the benefits from two different energy-saving installations are studied: bedrock heat pumps and heat exchangers in Heat Recovery Ventilation Systems (HRV-systems). These are then compared in a new and an older detached house with very different heat losses. There are several reports of energy-saving systems in detached houses. What distinguishes this work is that it compares the specific results from the added energy-saving system depending on whether it was added first or last. The older detached house is an important part of this work as it represents a possible impact on parts of the existing housing stock with a similar technical standard. The energy balance for the buildings is calculated monthly with all contributions from passive heat considered, and with the energy demand for active heating as the main result. Results: It is very difficult to meet the energy performance requirements for an older detached house without extensive measures or renovations. The HRV-system had a low to very low impact. Both types of detached houses have a lot to gain from an investment in bedrock heating, especially the older one that has high energy demands. However, the new detached house with a higher technical standard in the building envelope, was the only one to meet the energy requirements with the bedrock heat pump on its own. Conclusion: Bedrock heating can be a very profitable investment as it provides heat both for the active heating of the building as well as for the domestic hot water. In order to meet tougher energy requirements, the bedrock heat pump may need to be accompanied by an improved and more energy-efficient building envelope and the supply of self-produced electricity, such as solar cells. HRV-systems require a good air tightness and an energy-efficient building envelope to be profitable. In older detached houses, it is not a profitable investment, as it does not have sufficiently large proportions of controlled ventilation to work with. In newer houses the proportion of controlled ventilation is bigger, but the amount of heat loss that can be affected is still not as big as the energy savings a bedrock heat pump can bring.

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