Obesity, type 2 diabetes, and cardiovascular diseases are major problems in today's society, causing millions of deaths every year. One of the main risk factors for these diseases is a dysregulation of the fatty acid metabolism, where the balance between release and uptake of fatty acids is disturbed. Thus, understanding how fatty acid metabolism works is of great importance in the battle against these diseases. The human fatty acid release and uptake can be unraveled by measuring the difference in metabolite concentrations between an artery before the adipose tissue and a vein draining the tissue. Such measurements are called arterio-venous. However, due to the complexity of the fatty acid mechanisms, the resulting measurements alone are not enough to understand all of the involved reactions governing the metabolism. One analytical tool to decipher such complex mechanisms is mathematical modeling. A few mathematical models have previously used arterio-venous data of the fatty acid metabolism, but none of the previous models describe a full day including several meals and nightly fast. In this project, I combine mathematical modeling and arterio-venous data to investigate the mechanisms of fatty acid metabolism during three consecutive meals and fasting. The resulting mathematical model can explain arterio-venous data of free fatty acids, triglycerides, and glycerol. The model predictions show that re-esterification of monacylglycerides, a mechanism that has not been considered before when analyzing arterio-venous data, is of importance to be able to accurately describe the fatty acid metabolism. Additionally, the model predicts that there is a hormonal regulation during the night. Finally, it is shown that many of the previous simple calculations used to approximate metabolic reactions do not capture the desired reactions but instead calculate more complex properties, while the use of the model allows for a more detailed analysis separating all of the different reaction rates. These results give new insights into the complex mechanisms of fatty acid metabolism and provide a new tool to analyze arterio-venous data more comprehensively. In the future, this can lead to a better understanding of metabolic diseases such as obesity, type 2 diabetes, and cardiovascular diseases.

In radiotherapy, a quantity asked for by clinics when calculating a treatment plan, along withdose, is linear energy transfer. Linear energy transfer is defined as the absorbed energy intissue per particle track length and has been shown to increase with relative biologicaleffectiveness untill the overkilling effect. In this master thesis the dose averaged linear energytransfer from proton and carbon ion beams was simulated using the FLUKA multi purposeMonte Carlo code. The simulated distributions have been compared to algorithms fromRaySearch Laboratories AB in order to investigate the agreement between the computationmethods. For the proton computation algorithm improvements to the current scoring algorithmwere also implemented. A first version of the linear energy transfer validation code was alsoconstructed. Scoring of linear energy transfer in the RaySearch algorithm was done with theproton Monte Carlo dose engine and the carbon pencil beam dose engine. The results indicatedthat the dose averaged linear energy transfer from RaySearch Laboratories agreed well for lowenergies for both proton and carbon beams. For higher energies shape differences were notedwhen using both a small and large field size. The protons, the RaySearch algorithm initiallyoverestimates the linear energy transfer which could result from fluence differences in FLUKAcompared to the RaySearch algorithm. For carbon ions, the difference could stem from someloss of information in the tables used to calculate the linear energy transfer in the RaySearchalgorithm. From validation γ-tests the proton linear energy transfer passed for (3%/3mm) and(1%/1mm) with no voxels out of tolerance. γ-tests for the carbon linear energy transfer passedwith no voxels out of tolerance for (5%/5mm) and a fail rate of 2.92% for (3%/3mm).

Traumatic brain injuries (TBIs) are a major public health problem worldwide where the symptoms can be anything from mild concussion to severe swelling of the brain tissue. As a result of TBI the intracranial pressure (ICP) can elevate to pathological levels with severe consequences such as hypoxia, ischemia and brain hemorrhage. TBI and the subsequent ICP increase could hence lead to disability or in worst cases death. Therefore to understand the severity of a head injury and the path regarding further treatments, monitoring of a patient's ICP is crucial in the intensive care units (ICU) environment. Invasive methods of ICP monitoring are at this present date the standard in ICU because of the accuracy when compared to non-invasive methods. All invasive ICP monitoring methods come with a risk to the patient and require the presence of a neurosurgeon. The thesis's objective was to develop a gradually increasing ICP testbed for a new non-invasive microwave based skin patch sensor. The aim with this project was to verify if a dependence in the resonance characteristic of the NASA SansEC microwave sensor with respect to ICP exists as suggested by previous works in a novel testbed and to provide a correlation model based on the testbed experiment. The developed testbed simulate increasing ICP by increasing volume of an artificial cerebro-spinal fluid (aCSF) liquid, a liquid emulating the CSF. The microwave sensor's resonance frequency is due to the permittivity changes caused by the change (increasing) in the fluid volume, which for this setup is directly correlated to the pressure change as well. Trials with different aCSF samples were made to ensure that the used aCSF in the testbed had the same dielectric properties as human CSF. The developed testbed had a simple structure made with several plastic containers of rectangular shape which were found to be well suited for the purpose of the experiment. For the microwave sensor trials an Fieldfox microwave analyzer was used and the sensor was evaluated around 1 - 4 GHz. The testbed pressure was increasing from 0 - 47 mmHg covering most useful ICP ranges. Larger pressures were also possible but limited by the height of the work room and the increase of complexity in the testbed design. The results from the trials showed a total resonance frequency shift of 76 MHz from 4 - 30 mmHg with an linear correlation of R2 = 0,91. The sensor measurements above 30 mmHg showed a saturation where the first principal frequencies were stable at 1,368 GHz. The linear relationship obtained for 4-30 mmHg is a reassurance that the Nasa SansEC sensor should be studied further. Future work should include new trials with modifications to the testbed setup and sensor design.

Obesity has in recent times become a more serious health issue and was estimated to affect over 650 million people world-wide in 2016. Furthermore, the list of obesity-associated diseases is countless, many of which have severe consequences. Type 2 diabetes (T2D) is such a disease, and it was estimated to be over 1.5 million new cases in America alone in 2015. It is thought that insulin resistance development which causes T2D is associated with a low-level chronic inflammation in the adipose tissue. The inflammatory state is caused by the pro-inflammatory cytokine tumor necrosis factor-alpha (TNF-α) which is secreted by macrophages. To further understand the complexity of the underlying mechanisms of both the adipocytes as well as the macrophages, mathematical models are being developed in the fields of systems biology. However, as of now, no mathematical model has been developed which can explain the association between chronic inflammation and the development of insulin resistance. Because of this, a first model will be presented which is able to describe the mechanisms of insulin resistance development caused by chronic inflammation. The model was fitted to data from intraperitoneal glucose tolerance test in mice and yielded a cost below the threshold of chi-square test, which suggests that the model cannot be rejected. Furthermore, the model was expanded, introducing more complexity in the intracellular cascade reaction of an activated macrophage. Once again, the model was fitted to the same data and yielded a cost below the threshold of chi-square test. Uncertainty tests were made to further validate the models and showed a low uncertainty for both models. These results increase the understanding regarding the association between adipocytes and macrophages, in the role of insulin resistance caused by chronic inflammation. This increased knowledge can help, for instance, in the development of new drugs which are able to prevent the development of insulin resistance and T2D.

Introduction: Handcycling is an excellent exercise for people with spinal cord injuries. However, some users experience barriers to transferring to the handcycle. The most common barriers are the height difference between the handcycle and sitting surface and dependence on others. Purpose: This thesis aims to develop an assistive technology to help users independently transfer in and out of a handcycle. Methods: The framework for the thesis is the double-diamond, guiding the designing of the products concepts. Users, professionals, and manufacturers were interviewed regarding the facilitators and barriers while transferring in and out of the handcycle and the product needs to help prevent the barriers. A content analysis was performed to find the facilitators and barriers, and a need analysis was performed to find the needs for the product. The needs were translated into target specifications to have measurable characteristics. Benchmarking was performed, and the products were evaluated in regard to the target specifications. The market segment, personas, mood board, and design brief served to inspire and inform the specifications for the product. Brainstorming and sketching were performed to generate four concepts. The participants evaluated these concepts, and the top-ranked concept was further developed. A computer-aided model was created and rendered to better illustrate the product. A guide on how to use the product was developed based on TAI 4.0, which also was used to find limitations in the transfer technique of the new product. An evaluation regarding the target specifications was also performed. Result: The final product concept allows height transfer and can be used independently. It fulfills seven out of the seventeen target specifications in the current state. However, six target specifications cannot be defined yet as they should be developed further in other iterations. Conclusion: A lifting device concept for transferring was developed. It would still need further iterations to keep improving the product before it would be able to be released for users.

Introduction: Assessing brain maturation in preterm neonates is essential for the health of the neonates. Machine learning methods have been introduced as a prospective assessment tool for neonatal electroencephalogram(EEG) signals. Explainable methods are essential in the medical field, and more research regarding explainability is needed in the field of using machine learning for neonatal EEG analysis. Methodology: This thesis develops an explainable machine learning model that estimates postmenstrual age in very preterm neonates from EEG signals and investigates the importance of the features used in the model. Dual-channel EEG signals had been collected from 14 healthy preterm neonates of postmenstrual age spanning 25 to 32 weeks. The signals were converted to amplitude-integrated EEG (aEEG) and a list of features was extracted from the signals. A regression tree model was developed and the feature importance of the model was assessed using permutation importance and Shapley additive explanations. Results: The model had an RMSE of 1.73 weeks (R2=0.45, PCC=0.676). The best feature was the mean amplitude of the lower envelope of the signal, followed by signal time spent over 100 µV. Conclusion: The model is performing comparably to human experts, and as it can be improved in multiple ways, this result indicates a promising outlook for explainable machine learning model applications in neonatal EEG analysis.

Sector-Wise Golden Angle (SWIG) is a novel approach that was developed to address the limitations associated with Golden Angle radial imaging, commonly used for high temporal resolution flow measurements. Golden angle radial imaging is a time-efficient method that effectively reduces motion sensitivity. However, binned or retrospectively gated imaging where multiple heartbeats are utilized to acquire a single time series may lead to uneven coverage of k- space, ultimately resulting in poor image quality. In contrast, SWIG restricts the radial profiles to a sector of k-space per heartbeat, ensuring even distributions of spokes during retrospectively gated acquisitions. One drawback of SWIG is the loss of ability to reconstruct real-time images. The combination of sorted and unsorted acquisition simultaneously holds significant potential and could be applied in various domains. The goal of the thesis work was to design a trajectory that combines radial and spiral k-space sampling, enabling hybrid real-time and retrospectively gated imaging. The objective was to obtain an image series with comparable quality to a SWIG readout while retaining the ability to reconstruct a low-resolution real-time image series from the same data. To evaluate the hybrid trajectory, the numerical phantom XCAT was used to generate synthetic MRI images. Binned images were sampled using a hybrid-SWIG method, yielding similar image quality to a conventional SWIG image series, with the added benefit of being able to reconstruct a low-resolution real-time image series. Although the current method was only evaluated in a numerical phantom and may require additional adjustment to be suitable for a real MRI scanner, the results show that it is possible to combine radial and spiral imaging in a single readout.

På substratenheten på Karolinska Universitetssjukhuset inventerades och produktionsplanerades allt för hand på papper 3 gånger i veckan. Syftet med projektet har varit att hitta en digital lösning för att effektivisera arbetet kopplat till inventeringen och produktionsplaneringen. Målet har därför varit att utveckla en skrivbordsapplikation för att uppnå detta syfte genom avläsning av QR-koder. Projektet genomfördes genom programmering i språket Java och utnyttjade JavaFX för alla grafiska komponenter. Databaskopplingen som krävdes använde mySQL för att sammankoppla program med databas. För utvecklandet av applikationen så har designmönstret Model-View-Controller använts. Vi som författare anser att applikationen bör bearbetas vidare, detta då en del funktionalitet skulle behöva optimeras och även utvecklas vidare för att uppnå önskad användarvänlighet. Dock är vår slutsats att alla de uppsatta målen uppfylldes. / At the substrate unit at Karolinska University Hospital they previously did their inventory and production planning by hand three times a week. The purpose of the project has been to find a digital solution to streamline this unit’s workload connected to inventory and production planning. Therefore, the aim of the project was to develop a desktop application to fulfill the purpose of the project by scanning QR-codes. The project has been performed through programming in the language Java and used the JavaFX library for all graphical components. The database connection used mySQL to connect the program to the database. For the development of the application the design-pattern Model-View-Controller were used. As authors of the report, we consider that the application should be further optimized, and additional functions should be introduced in order to achieve greater usability. However, our conclusion is that the application fulfills the aims set at the beginning of the project.

Böjsenor är senor i fingrarna som är kopplade till underarmens muskler. De läker långsamt efter en skada och kan därför gå av efter en reparation om patienten tränar för mycket eller för tungt. Vid för lite träning fastnar senan i omgivande vävnad och fingret blir stelt. Rehabiliteringen efter en böjsenskada pågår under minst tre månader efter operationen. Det kan därför bli svårt för patienter att upprätthålla motivationen och följa alla instruktioner korrekt under hela denna tid.   Syftet med projektet var att skapa en mobilapplikation som stödjer patienter i deras rehabilitering av en böjsenskada samt att implementera ett digitalt vinkelmätningsverktyg i applikationen. Applikationen utvecklades för både iOS- och Android-enheter med hjälp av deras officiella utvecklingsmiljöer, Android Studio och Xcode. Några funktioner som applikationen består av är en kalender med översikt av träningsplanen, möjligheten att utvärdera pass, möjligheten att skapa träningsprogram och exportera träningsdata. Applikationen innehåller även information om träningsinnehållet, kontaktinformation och allmänna råd till patienten.   Innan applikationen kan publiceras måste den testas på patienter för att få återkoppling om användarvänlighet och funktionalitet. De önskade funktionerna från uppdragsgivaren och målen uppnåddes med undantag av funktionen att lägga till möten som prioriterades bort. Det digitala vinkelmätningsverktyget implementerades för Android men inte för iOS. / Flexor tendons are tendons in the fingers that are connected to the muscles in the forearm. They heal slowly after an injury and can rupture again after the repair if the patient exercises too much or lifts too heavy. Insufficient exercise can cause the tendon to adhere to surrounding tissue, resulting in finger stiffness. Rehabilitation following a flexor tendon injury typically lasts for at least three months after surgery. Therefore, patients may find it challenging to maintain motivation and follow all instructions correctly throughout this period. The purpose of this project was to develop a mobile application that supports patients in their rehabilitation of a flexor tendon injury along with the implementation of a digital angle measuring tool. The application was developed for both iOS and Android devices using their official integrated development environments, Android Studio and Xcode. Some features that the application consists of are a calendar providing an overview of the training plan, the ability to evaluate sessions, the ability to create custom training programs and export training data. Additionally, the application contains information about the training content, contact details, and general advice for the patient. Before the application can be published, it needs to be tested on patients to gather feedback on user-friendliness and functionality. The desired features from the client and the goals for the project were achieved, apart from the meeting scheduling feature, which was deprioritized. The digital angle measuring tool was implemented for Android but not for iOS.

Vårdens digitala system präglas idag av en hög komplexitet och saknar ensammanhållen standard. Ett ökat behov för digitalisering inom vården harlett till stora utvecklingar, men även nya utmaningar. Ett av de viktigastesystemen, som genomsyrar hela vårdsystemet, är patientjournalen. I detta arbete undersöks möjligheterna till att applicera en ny teknologi föranvändning inom den svenska vårdens informationshantering, blockkedjor. Blockkedjor har huvudsakligen använts för implementering avkryptovalutor men har, på grund av sina riktighet- och spårbarhetsgarantier,blivit alltmer vanlig för användning inom övrig informationshantering. Inledningsvis undersöks förutsättningarna som ett journalsystem ska levaupp till enligt säkerhetsprinciperna Konfidentialitet, Riktighet,Tillgänglighet och Spårbarhet. Intervjuer med områdeskunniga förjournalsystemen inom Region Halland och Region Stockholm belyser någraav de brister och utmaningar som finns inom vården idag. Informationsinhämtning från lagrum och föreskrifter lägger grunden till dekrav som ett journalsystem ska uppfylla. Efter den inledande undersökningen studeras litteratur kopplat tillimplementeringar av blockkedjor i syfte att hämta in information gällandeblockkedjans komponenter för vidare behandling. Här behandlas blandannat utvecklardokument, state-of-the-art och analyser relaterade tillblockkedjor. Slutligen bearbetas blockkedjetekniken ihop med journalsystemensförutsättningar och resulterar i en teoretisk modell av ett blockkedjesystemför användning som patientjournal inom den svenska vården. Slutsatsen dras att möjligheten för en praktisk implementering av denteoretiska modellen är möjlig, men att vården i dagsläget inte harförutsättningarna för ett omfattande systembyte till en relativt obeprövadteknologi.