Prostate cancer (PCa) is the most common cancer type among men in Sweden. The most prevalent curative treatment for PCa is radical prostatectomy (RP), i.e., complete surgical removal of the prostate. Unfortunately, cancer cells are found near the resection surface in 35 % of the RP patients. This indicates an increased risk of PCa reccurence.Our main objective is to develop a novel medical instrument for detecting PCa. The idea is to combine the techniques of Raman spectroscopy (RS) and the tactile resonance method (TRM) into one integrated instrument. The TRM would provide a swift and gentle survey of the region of interest, while the RS adds detailed information of the molecular content where malignancy is suspected. The dual mode instrument could be well suited for detecting and locating tumour cells in the surgical margin during RP. The studies included in this thesis are important steps towards this objective.Paper A investigated how the two data sets from each of the technologies could be compared and combined for tissue characterisation. The data set of RS was a spectrum with peaks characteristic to the sample's molecular content. The TRM output variable was a scalar value related to the sample stiness. The data sets could be compared and combined by applying principal component analysis (PCA) to the RS spectra followed by an hierarchical cluster analysis (HCA). A linear regression analysis showed that the PCs explained 67% of the stiffness variations. HCA was used to classify each RS measurement into groups consisting of similar measurements. The TRM's sensitivity and specificity of classifying these groups were evaluated by ROC curves and the area under the curve (AUC). The harder group could successfully be discriminated from the softer groups (AUC = 0.99).Paper B used support vector machines (SVM) as a method to classify and differentiate porcine and human prostate tissue types using the combined data sets. Prostate tissue is highly inhomogenous, with streaks of small anatomical structures. The analysis was evaluated within areas of three levels of homogenity, to avoid mismatching the measured tissue. The tissue homogenity was evaluated within the RS measurement area and the tissue type was set to the main histological content. Areas in which no single tissue type surpassed the threshold level were excluded from the analysis. The cross-validation accuracy for determining the tissues types within homogenous (main tissue type > 83%) porcine samples was 82% using TRM data alone. It increased to 87% while using the combined data sets of TRM and RS. For discerning healthy and cancerous human prostate tissue, the cross-validation accuracy was 67% and 77% for TRM alone versus TRM and RS combined.Paper C covered a number of design considerations which have to be addressed during the combination of TRM and RS. The effects of attaching an RS probe into a tubular TRM element were investigated. We investigated the temperature increase caused by the laser illumination from the RS and its eect on the TRM measurement parameter Δf. We also investigated if and how RS could be performed under ambient light. A thin RS probe and a small amount of rubber latex was preferable for attaching the RS probe inside the TRM sensor. The temperature rise of the TRM sensor due to a fibreoptic NIR-RS at 270 mWduring 20 s was less than 2ºC. The variation of Δf during a 5ºC temperature change was approximately 20 Hz. This is small compared to previous in vitro TRM studies. Fibre-optic NIR-RS was feasible in a dimmed bright environment using a small light shield and automatic subtraction of a pre-recorded contaminant spectrum. The results of these studies indicate how the hardware and and software could be combined into one integrated probe for prostate cancer detection.

Stroke affects around 20 million people around the world every year. Clinically, stroke is a result of brain damage due to the shortage of oxygen delivered to the nerve cells. To minimize suffering and costs related to the disease, extensive research is performed on different levels. The focus of our research is to achieve fundamental understanding on how the lack of oxygen in brain tissue activates intrinsic biomolecular defense mechanisms that may reduce brain damage. More knowledge may hopefully lead to new therapeutic and preventive strategies on the molecular level for individuals in the risk zone for stroke or those who have just suffered a stroke. The area of study is based on the discovery of a hemoprotein called neuroglobin (Ngb), which is found in various regions in the brain, in the islets of Langerhans, and in the retina. Several studies have shown that Ngb seems to have a protective function against hypoxia-related damage. However, until now, it has not been understood how Ngb affects the nerve system and protects neurons from damage. The well-established patch-clamp technique is routinely used to measure and analyze the electrophysiological activity of individual biological cells. To perform accurate patchclamp experiments, it is important to create well-controlled physiological conditions, i.e. different oxygen levels and fast changes of nutrients and other biochemical substances. A promising approach is to apply lab-on-a-chip technologies combined with optical manipulation techniques. These give optimal control over fast changing environmental conditions and enable multiple readouts. The conventional open patch-clamp configuration cannot provide adequate control of the oxygen content. Therefore, it was substituted by a gas-tight multifunctional microfluidic system, a lab-on-a-chip, with an integrated patch-clamp micropipette. The system was combined with optical tweezers and optical spectroscopy. Laser tweezers were used to optically guide and steer single cells towards the fixed micropipette. Optical spectroscopy was used to investigate the biochemical composition of the sample. The designed, closed lab-on-a-chip acted as a multifunctional system for simultaneous electrophysiological and spectroscopic experiments with good control over the oxygen content in the liquid perifusing the cells. The system was tested in a series of experiments: optically trapped human red blood cells were steered to the fixed patch-clamp pipette within the microfluidic system. The oxygen content within the microfluidic channels was measured to 1 % compared to the usual 4-7 %. The trapping dynamics were monitored in real-time while the spectroscopic measurements were performed simultaneously to acquire absorption spectra of the trapped cell under varying environments. To measure the effect of the optical tweezers on the sample, neurons from rats in a Petri dish were optically trapped and steered towards the patch-clamp micropipette where electrophysiological investigations were performed. The optical tweezers had no effect on the electrophysiological measurements. Similar investigations within a closed microfluidic system were initiated and showed promising results for further developments of a complete lab-on-a-chip multifunctional system for reliable patch-clamp measurements. The future aim is to perform complete protocols of patch-clamp electrophysiological investigations while simultaneously monitoring the biochemical composition of the sample by optical spectroscopy. The straightforwardness and stability of the microfluidic chip have shown excellent potential to enable high volume production of scalable microchips for various biomedical applications. The subsequent ambition is to use this system as a mini laboratory that has benefits in cell sorting, patch-clamp, and fertilization experiments where the gaseous and the biochemical content is of importance. The long-term goal is to study the response of individual neurons and defense mechanisms under hypoxic conditions that may establish new ways to understand cell behavior related to Ngb for various diseases such as stroke, Alzheimer’s and Parkinson’s.

This licentiate thesis presents ubiquitous systems for human communication and awareness from the perspectives of improving our everyday life experiences and relieving our scarcest resource, ourselves. The thesis also presents different methods of designing such systems with the user needs in focus. The goal of this work is to construct systems which support the user with context-based information and functionality that simplifies the user's tasks. The applied nature of this thesis is indicated by the three prototypes, which has been developed and evaluated. The first prototype provided spectators of sport-events with added information about the contestants and hence improved the experience of the event. The second prototype supported nurses in elderly care with their tasks by making organization and information gathering less time consuming and thus leaving more time for talking to the patients. Finally, the third prototype realized a system for ubiquitous human communication. The third prototype utilizes an algorithm for selecting and using media resources in the environment. This algorithm decouples several difficult problems and can be used to combine leading research in different areas of awareness together to create accurate resource selection. The motivation for creating prototypes has been to get experience from using systems which empower users and to find methods for satisfying user needs. Involving users early in the design process can help satisfy user needs. Hence, it is important to find methods and strategies for involving users, especially as not everyone can see the opportunities a new technology has to offer. In this thesis four methods and strategies are described and tested. These are paper prototypes, wizard of oz studies, questionnaires and real prototypes which were developed and then evaluated. These methods are compared and some of the findings are being discussed in this thesis. The evaluation of the prototypes and the user-studies show that it is possible to improve everyday life experiences using a combination of ubiquitous, pervasive, wearable and context-aware computing. A majority of all the users who answered the questionnaire for the first prototype answered that the system improved their experience of the sport event. The nurses who used the second prototype were positively surprised over how the technology could save both time and create a better group awareness. Most of the users who participated in the user-study for the third prototype were positive to using a mix of media resources to get richer communication, they were also in favour of using resources in the environment to save money and improve quality. The main results in this thesis are valuable insights into user opinions of ubiquitous systems, methods for involving users in the design process, and several design rules which can serve as a guideline for designing future ubiquitous systems. / Godkänd; 2006; 20070109 (haneit)

The goal of this report is to develop code in Python that implements and evaluates a multivariate linear error propagation for commonly used DCE-MRI models. Two pharmoacokinetic models (PK-models) were tested; modified Kety model and two-compartment exchange model. The analysis compared a Monte carlo simulated signal and a simple analytic model for uncertainty. The purpose of comparing was to have the Monte carlo method and the linear error estimation method reasonably close in terms of estimation of the error of the PK-parameters (parameters are specific for the PK-model). The analysis included an inspection of the resulting plots of the Coefficent of Variation (CV) of the estimation of the PK-parameters, when increasing the ratio of the true value and the added error for each of the input parameters. Generally the CV increased, I.e. the precision decreased, as the noise level increased. For both PK-models, error in injection time of contrast agent were the input parameter with the least tolerance of noise. By comparing the results from both methods, the conclusion is to implement the modified Kety model as the PK-model used in MICE Toolkit (NONPI Medical AB, Umeå, Sweden) and keep the noise to signal level below 15\% in order to obtain precision of the results to less than 33\% error. We have verified the uncertainty estimation method works well for the Modified Kety model but not so well for the two-compartment exchange model. The scope of this study only included two PK-models and one signal model, therefore it would be beneficial to test the linear estimation method used here on other PK-models and signal models to find what models it works well for. / Målet med denna rapport är att utveckla kod i Python som implementerar och utvärderar multivariat linjär felpropagering för ofta använda DCE-MRI modeller. Två farmakokinetiska modeller (PK-modeller) testades; den modifierade Kety-modellen och två-utrymme utbytesmodellen. Analysen jämförde en Monte carlo-simulerad signal och en enkel analytisk modell för osäkerhet. Syftet med jämförelsen var att ha Monte carlo-metoden och den linjära feluppskattningsmetoden någorlunda nära när det gäller uppskattning av PK-parametrarnas fel (parametrarna är specifika för PK-modellen). Analysen innebar en inspektion av de resulterande kurvorna för variationskoefficienten (CV) för uppskattningen av PK-parametrarna, när förhållandet mellan det sanna värdet och det pålagda felet för var och en av ingångsparametrarna ökades. Generellt ökade CV:n, det vill säga precisionen minskade när bruset/felet ökade. För båda PK-modellerna var det fel i injektionstid för kontrastmedel den ingångsparameter som hade minst tolerans för brus. Genom att jämföra resultaten från båda metoderna är slutsatsen att använda den modifierade Kety-modellen som PK-modell i MICE Toolkit (NONPI Medical AB, Umeå, Sverige) och hålla brus-till-signal nivån under 15\% för att få precision av resultaten till mindre än 33\% fel. Vi har verifierat att metoden för osäkerhetsuppskattning fungerar bra för den modifierade Kety-modellen men inte så bra för två-utrymme utbytesmodellen. Omfattningen av denna studie inkluderade endast två PK-modeller och en signalmodell, därför skulle det vara fördelaktigt att testa den linjära uppskattningsmetoden som används här på andra PK-modeller och signalmodeller för att hitta vilka modeller den fungerar bra för.

While markerless motion capture provided acceptable accuracy, no clear patterns emerged regarding the individual effects of surface properties on technique. This is most likely due to limitations such as sample size, lack of standardizing data set (players) across facilities, and limited control over player behavior. However, analyzing one individual's motion capture data across surfaces showed potential for distinguishing turning styles based on facility parameters. The method in this thesis demonstrates the potential of markerless motion capture for injury prevention research in football. Despite inconclusive results on the individual facility parameter effects, the ability to distinguish player styles across surfaces suggests valuable future directions for investigating personalized risk factors and optimizing playing surfaces. Further research with larger, more diverse samples and a broader set of biomechanical and facility features could provide deeper insight into injury prevention strategies.

Heart rate variability, HRV, has been well researched for some decades. The oscillations of the heart rate is studied over a time period of some minutes up to 24 hours, it is measured with electrocardiography, ECG. From this one has concluded that the heart rate signal oscillates in accordance with the respiration, the resistance in the vessels etc. The most frequently used examination method of the heart is done with ultrasound, called echocardiography. One interesting variable at a time is measured and it is measured for a single heartbeat. With inspiration ofthe HRV studies this project focuses on some of the variables measured with ultrasound but over time andsimultaneously. The variables of interest are the myocardial motion and the blood flow in the left part ofthe heart, they are measured over two minutes. To complement these variables the well known variables HRand Resp are measured with ECG and added to the analysis. The methods used for analysing the variables are first of all descriptive statistics like mean and standard deviation. Secondly spectral analysis is performed to investigate in which frequencies the variables oscillates. Through coherence this is compared with the spectrum for HR where the three peaks have known origin. Finally principal component analysis, PCA, is performed as a method to compare all variables at the same time. The analyses are performed on seven measurements from five (5) healthy persons and five measurementsfrom four (4) patients with the disease FAP (“Skelleftesjukan”). The variables are investigated and described for the healthy persons first, then the healthy persons and patients are compared. The result from the study shows that most of the echo-variables oscillate in accordance with the respirationand the heart rate. For a healthy person the oscillations are within normal values and the relative deviation isaround 10%. The patients with FAP are most affected in the variables connected to the myocardium apartfrom HR, which is known since before. The coherence between the echo-variables and HR is low in one of VLF, very low frequency, or LF, lowfrequency, region and high in the other. In HF, high frequency, region the coherence is high for all variables. Finally the PCA was conducted on measurements from all healthy persons as one data set, from one ofthe healthy persons and from one of the patients with FAP. The analysis showed that for healthy personsrespiration is the process causing most variation and all of the echo-variables have a correlation to therespiration. For a patient with FAP the respiration is not as salient. A PCA over blocks of data at different time points however show that the signals are not oscillating in the same way multivariately over the wholetime series. / Hjärtfrekvensvariabilitet, HRV, är ett väl utforskat område sedan några årtionden tillbaka. Svängningarna i hjärtfrekvensen studeras över tidsperioder av några minuter upp till 24 timmar och mäts med elektrokardiografi, EKG. Från det har man kunnat sluta sig till att signalen för hjärtfrekvensen oscillerar enligt signalen för andningen, kärlresistans etc. Den mest använda undersökningsmetoden på hjärtat utförs med ultraljud, ekokardiografi. De intressanta variablerna mäts en i taget och för ett hjärtslag åt gången. Med inspiration från studierna av HRV fokuserar det här projektet på några av variablerna som mäts med ultraljud, men som tidsserier och simultant mätta. De intressanta variablerna är tagna från hjärtmuskeln och blodflödet i den vänstra delen av hjärtat. Mätningarna görs över två minuter. För att komplettera dessa variabler mäts de välkända variablerna HR och Resp med EKG och läggs till analysen. Metoderna för att analysera datat är först av allt beskrivande statistik, såsom medelvärde och standardavvikelse. I ett andra steg görs en spektralanalys för att undersöka inom vilka frekvenser signalerna oscillerar. Genom koherens jämförs detta med spektrum för HR där de tre topparna har känt ursprung. Slutligen utförsen principalkomponentanalys, PCA, som en metod för att jämföra alla variabler samtidigt. Analyserna utförs på sju mätninger från fem (5) friska personer och fem mätningar från fyra (4) patienter med FAP (“Skelleftesjukan”). Variablerna undersöks och beskrivs först för de friska personerna, sedan jämförs de friska och sjuka personerna. Resultatet av studien visar att största delen av eko-variablerna oscillerar i enighet med andningen och hjärtfrekvensen. För en frisk person är svängningarna inom normala värden och den relativa avvikelsen är ungefär 10%. För patienterna med FAP påverkas framförallt variablerna kopplade till hjärtmuskeln förutom HR som man visste sedan tidigare. Koherensen mellan eko-variablerna och HR är låg i antingen VLF-, very low frequency, eller LF-, low frequency, området och hög i den andra. I HF-, high frequency, området är koherensen hög för alla variabler. Slutligen görs PCA på mätningarna från alla friska personer som ett dataset, på en av de friska personerna och på en av patienterna med FAP. Analysen visar att för friska personer är andningen den process som orsakar mest variation och alla eko-variabler har en korrelation till andningen. För en patient med FAP är andningen inte lika framträdande. En PCA av block ur datat vid olika tidpunkter i signalen visar dock att signalerna inte svänger multivariat på samma sätt genom hela tidsserien.

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