A sensor node 'AccuMicroMotion' is proposed that has the ability to detect motion in 6 degrees of freedom for the application of physiological activity monitoring. It is expected to be light weight, low power, small and cheap. The sensor node may collect and transmit 3 axes of acceleration and 3 axes of angular rotation signals from MEMS transducers wirelessly to a nearby base station while attached to or implanted in human body. This dissertation proposes a wireless electronic system-on-a-single-chip to implement the sensor in a traditional CMOS process. The system is low power and may operate 50 hours from a single coin cell battery. A CMOS readout circuit, an analog to digital converter and a wireless transmitter is designed to implement the proposed system. In the architecture of the 'AccuMicroMotion' system, the readout circuit uses chopper stabilization technique and can resolve DC to 1 KHz and 200 nV signals from MEMS transducers. The base band signal is digitized using a 10-bit successive approximation register analog to digital converter. Digitized outputs from up to nine transducers can be combined in a parallel to serial converter for transmission by a 900 MHz RF transmitter that operates in amplitude shift keying modulation technique. The transmitter delivers a 2.2 mW power to a 50 Ù antenna. The system consumes an average current of 4.8 mA from a 3V supply when 6 sensors are in operation and provides an overall 60 dB dynamic range. Furthermore, in this dissertation, a methodology is developed that applies accelerated electrical stress on MOS devices to extract BSIM3 models and RF parameters through measurements to perform comprehensive study, analysis and modeling of several analog and RF circuits under hot carrier and breakdown degradation.

Human Activity Recognition (HAR) is a growing field of research concerned with classifying human activities from sensor data. Modern smartphones contain numerous sensors that could be used to identify the physical activities of the smartphone wearer, which could have applications in sectors such as healthcare, eldercare, and fitness. This project aims to use smartphone sensor data together with machine learning to perform HAR on the following human locomotion activities: standing, walking, running, ascending stairs, descending stairs, and biking. The classification was done using a random forest classifier. Furthermore, in the special case of walking, an algorithm that can count the number of steps in a given data sequence was developed. The step counting algorithm was not based on a previous implementation and could therefore be considered novel. The step counter achieved a testing accuracy of 99.1\% and the HAR classifier a testing accuracy of 100\%. It is speculated that the abnormally high accuracies can be attributed primarily to the lack of data diversity, as in both cases only two persons collected the data. / Mänsklig aktivitetsigenkänning är ett växande forskningsområde som handlar om att klassificera mänskliga aktiviteter från sensordata. Moderna mobiltelefoner innehåller många sensorer som kan användas för att identifiera de fysiska aktiviteterna som bäraren utför, vilket har tillämpningar inom sektorer som sjukvård, äldreomsorg och personlig hälsa. Detta projekt använder sensordata från mobiltelefoner tillsammans med maskininlärning för att utföra aktivitetsigenkänning på följande aktiviteter: stå, gå, springa, gå uppför trappor, gå nedför trappor och cykla. Klassificeringen gjordes med hjälp av en ``random forest''-klassificerare. Vidare utvecklades en algoritm som kan räkna antalet steg i en given datasekvens som samlats in när användaren går. Stegräkningsalgoritmen baserades inte på en tidigare implementering och kan därför betraktas som ny. Stegräknaren uppnådde en testnoggrannhet på 99,1\% och aktivitetsigenkänningen en testnoggrannhet på 100\%. De oväntat höga noggrannheterna antas främst bero på bristen av diversitet i datan, eftersom den endast samlades in av två personer i båda fallen. / Kandidatexjobb i elektroteknik 2022, KTH, Stockholm

Human Activity Recognition (HAR) is a widelyresearched field that has gained importance due to recentadvancements in sensor technology and machine learning. InHAR, sensors are used to identify the activity that a person is performing.In this project, the six everyday life activities walking,biking, sitting, standing, ascending stairs and descending stairsare classified using smartphone accelerometer and gyroscope datacollected by three subjects in their everyday life. To performthe classification, two different machine learning algorithms,Artificial Neural Network (ANN) and Support Vector Machine(SVM) are implemented and compared. Moreover, we comparethe accuracy of the two sensors, both individually and combined.Our results show that the accuracy is higher using only theaccelerometer data compared to using only the gyroscope data.For the accelerometer data, the accuracy is greater than 95%for both algorithms and only between 83-93% using gyroscopedata. Also, there is a small synergy effect when using both sensors,yielding higher accuracy than for any individual sensor data, andreaching 98.5% using ANN. Furthermore, for all sensor types, theANN outperforms the SVM algorithm, having a greater accuracyby more than 1.5-9 percentage points. / Aktivitetsigenkänning är ett noga studeratforskningsområde som växt i popularitet på senare tid på grundav nya framsteg inom sensorteknologi and maskininlärning. Inomaktivitetsigenkänning använder man sensorer för att identifieravilken aktivitet en person utför. I det här projektet undersökervi de sex olika vardagsmotionsaktiviteterna gå, cykla, sitta, stå och gå i trappor (up/ner) med hjälp av data från accelerometeroch gyroskop i en smartphone som samlats in av tre olikapersoner. Två olika maskininlärningsalgoritmer implementerasoch jämförs: Artificial Neural Network (ANN) och SupportVector Machine (SVM). Vidare jämför vi noggranheten förde två sensorna, både individuellt och gemensamt. Våra resultvisar att noggranheten är större när enbart accelerometerdatananvänds jämfört med att använda enbart gyroskopdatan. Föraccelerometerdatan erhålls en noggranhet större än 95 % förbåda algoritmerna medan den siffran bara är mellan 83-93 %för gyroskopdatan. Dessutom existerar det en synergieffekt vidanvändande av båda sensorerna, och noggranheten når då 98.5% vid användande av ANN. Vidare visar våra resultat att ANNhar en noggranhet som är 1.5-9 procentenheter bättre än SVMför alla sensorer. / Kandidatexjobb i elektroteknik 2021, KTH, Stockholm

Background: The term physical behavior includes sedentary and non-sedentary everyday physical activities. Objective measurement methods are recommended when sedentary behaviors are to be measured. Data from a thigh worn accelerometer can, together with the Acti4 software, be used to distinguish different physical behaviors. Due to different shapes of thighs and how the accelerometers have been placed on the thighs there is a need to compensate for individual differences in reference angles in respect to gravity. Normally this is done by letting the participants perform a reference position when they stand up and that time is noted in a diary. However, this is very time  consuming. One alternative is to automatically estimate the compensation angles from walking episodes in the existing data. Objective: The aim of this study was to validate two new features to the Acti4 software, detection of lying and automatic reference angle generation. Methods: Ten participants underwent a 45-minute standardized protocol, and a 48-hour free-living protocol, with recordings of the different physical behaviors lying, sitting, standing, walking, running, stair walking, and cycling. Video recordings of the standardized protocol, and accelerometer data and diaries together with the participants review of the results from the software from the free-living protocol, has been used to validate the software. Results: During the standardized protocol, the overall accumulated performance of the software to identify the same physical behavior as in the video recordings was 81.1% (sensitivity), 96.7% (specificity) and 94.8% (accuracy). Participants agreed that most identified physical behavior episodes were correct, when reviewing the result from the software. When the two different reference angle generation methods were compared, almost no difference was found in the results of the standardized protocol, neither when comparing total time registered per behavior accumulated for all participants during the free-living protocol. Conclusions: The software may be used in research as a valid tool to measure physical behavior. However, the sensitivity to detect lying and stair walking may vary between individuals. When conducting research with thigh worn accelerometers, researchers may use the easier to use method with automatically generated reference angles instead of the more burdensome method with manually recorded diary annotation.

The early diagnosis of CP (Cerebral Palsy) in infants is important for developing meaningful interventions. One of the major symptoms of the CP is lack of the coordinated movements of a baby. The bilateral coordinated movement (BCM) is that a baby shows in the early development stage. Each limb movement shows various ranges of speed and angle with fluency in a normal infant. When a baby has CP the movements are cramped and more synchronized. A quantitative method is needed to diagnose the BCM. Data is collected from 3-axis accelerometers, which are connected, to each limb of the baby. Signal processing the collected data using short time Fourier transforms, along with the formation of time-dependent transfer functions and the coherence property is the key to the diagnostic approach. Combinations of each limb's movement and their relationship can represent the correlated movement. Data collected from a normal baby is used to develop the technique for identifying the fidgety movement. Time histories and the resulting diagnostic tool are presented to show the regions of the described movement. The evaluation of the transduction approach and the analysis is discussed in detail. The application of the quantitative tool for the early diagnosis of CP offers clinicians the opportunity to provide interventions that may reduce the debilitating impact this condition has on children. Tools such as this can also be used to assess motor development in infants and lead to the identification and early intervention for other conditions. / Master of Science

Simultaneously achieving high-sensitivity and a large resonance frequency of micromachined accelerometers is difficult because of the inherent trade-off between the two. In this thesis, we present a mechanical displacement-amplifying technique that is amenable to micromachining to enhance sensitivity without compromising on the resonance frequency and cross-axis sensitivity. Depending on the requirements of sensitivity alone or sensitivity and resonance frequency, Displacement-amplifying Compliant Mechanisms (DaCMs) are designed using the selection map-based technique, which indicates the limits of what is possible for given specifications on size and microfabrication. In order to prove the benefits of a DaCM, we modified the designs of two very sensitive capacitive micromachined accelerometers from the literature by incorporating DaCMs and showed that, within the same footprint on the chip, the displacement sensitivity could be enhanced by more than 60% while the resonance frequency was also improved by more than 30%. As the focus of the thesis is to explore the integration of DaCMs into accelerometers, the analytical, computational, and practical aspects are discussed in detail. Both single and dual axis in-plane accelerometers are considered. The fabrication processes used are Silicon-on-Insulator Multi-user MEMS Processes (SOIMUMPs) and a customized Silicon-on-Insulator (SOI) based process. The fabricated accelerometers are packaged and brought to the product form. They were tested at the die level as well as in the packaged form. Under dynamic conditions, the measured amplification factor of the fabricated single-axis in-plane accelerometer was observed to be 11. The overall dimension of the accelerometer was 4.25 mm × 1.25 mm. The first in-plane natural frequency of the fabricated accelerometer was found to be 6.25 kHz. The voltage sensitivity of the packaged accelerometer with the DaCM measured 26.7 mV/g at 40 Hz with differential capacitance sensitivity of 3926 ppm/g around the base capacitance of 0.75 pF. The fabricated dual-axis accelerometer has a special configuration of twelve folded-beam suspension blocks that de-couple any displacements along the two in-plane orthogonal axes. The decoupling feature is retained even after adding the DaCMs along both the axes. The total device size was 8.6 mm × 8.6 mm. The device was also fabricated and packaged inside a ceramic flat-pin package using hybrid die-to-die wire-bonding. Die-level dynamic characterization showed that the average geometric advantage achieved using the DaCMs is 6.2 along both the in-plane axes. The measured axial voltage sensitivity of about 580 mV/g for both the axes was achieved with a cross-axial sensitivity of less than 2% and a natural frequency of 920 Hz. The static capacitance sensitivity was found to be 0.296 × 106 ppm/g with a base capacitance of 0.977 pF. Also presented in this work is a wide-band dual-axis accelerometer without an amplifying mechanism. Its first two in-plane modal frequencies measured 14.2 kHz. The measured sensitivity of the packaged accelerometer along both the axes of the device was found to be 62 mV/g at 200 Hz. Aiming at towards cost-effective accelerometers for small-volume markets, we also developed a single-axis and two dual-axis meso-scale spring-steel in-plane accelerometers equipped with Allegro A1395 linear Hall-effect sensors for sensing the displacement of the proof-mass. The single-axis in-plane meso-scale accelerometer also contains a DaCM. It is observed through simulation that the single-axis design with a DaCM is 39% more sensitive and has 41% more bandwidth compared to a single-axis design without a DaCM. The measured sensitivity of the fabricated single-axis spring-steel accelerometer with a DaCM was found to be 71.4 mV/g with a minimum resolvable acceleration of 14 milli-g. The unique features of the first generation of dual-axis accelerometers are that a rechargeable Li-ion battery adds to the proof-mass. It also contains a de-coupling mechanism that can decompose any planar acceleration into its axial components. The second generation of dual-axis accelerometers is more compact in size. All the mechanical elements of the accelerometers are made of EN J42/AISI 1080 spring steel foil machined using Wire-cut Electro-Discharge- Machining. The measured sensitivity of the first generation of dual-axis meso-scale accelerometers is 78 and 108 mV/g along the X and Y axes whereas the second generation device exhibits a sensitivity of 40 mV/g for both the axes. The thesis concludes that the sensitivity of a displacement-based sensor can be improved using a suitably designed DaCM without compromising the resonance frequency and hence the bandwidth. Furthermore, the work describing the development of meso-scale accelerometers also establishes spring steel as a viable material for meso-scale applications.

Baigiamajame magistro darbe nagrinėjamos statinės ir dinaminės jėgos veikiančios tiesiaeigiame žingsniniame variklyje (TŽV). Apžvelgiami žingsninių variklių tipai, jų savybės ir charakteristikos. Analizuojamos variklio postūmio ir traukos jėgos bei matematinio modelio sudarymas. Tiriamojoje dalyje tiesiaeigiuose žingsniniuose varikliuose veikiančios jėgos tiriamos sudarant matematinius modelius, visi skaičiavimai atlikti naudojant programinį paketą MATHCAD. Ekperimento metu gautų rezultatų apdorojimui naudojamas programinis paketas DynaMax. Gautos statinės jėgos dedamųjų Fx, veikiančios išilgai judėjimo krypties, ir Fy, veikiančios vertikaliąja ašimi, priklausomybės nuo polių postūmio danties atžvilgiu, keičiant įvairius parametus (poliaus ir danties pločių santykį, magnetinę įtampą, oro tarpą). Taip pat atlikti tyrimai, parodantys kaip kinta dinaminė jėga, esant skirtingoms apvijos maitinimo įtampoms. Teoriniai skaičiavimai palyginti su eksperimentiniais tyrimo rezultatais. Išnagrinėjus teorinius ir praktinius matavimus pateikiamos baigiamojo darbo išvados ir pasiūlymai. Darbą sudaro 6 dalys: įvadas, teorinė dalis, tiriamoji dalis, išvados ir pasiūlymai, literatūra, priedai. Darbo apimtis – 70 psl. teksto be priedų, 45 iliustr., 14 lent., 14 bibliografiniai šaltiniai, 11 internetinių prieigų. Atskirai pridedami darbo priedai. / At the final Master's work dealt with the static and dynamic forces acting linear stepper motor (LSM). Overview of types of stepping motors, their properties and characteristics. Examines the push and pull the engine and the power of the mathematical model. The exploratory part of rectilineal stepping motors operating in the force under investigation for the mathematical models, all calculations performed using the software package MathCAD. Experimentation of the results of treatment using the software package DynaMax. The resulting static force added Fx, acting along the direction of movement, and the Fy in the vertical axis of dependence on the poles pull the tooth, the modification of various parameters (polarity, and the tooth width ratio, magnetic tension, the air space). Studies also showing changes in dynamic forces at different supply voltage windings. Theoretical calculations compared with experimental test results. The examination of the theoretical and practical measurements are presented on the final conclusions and proposals. Structure: introduction, theoretical part, searching part, conclusions and suggestions, references, appendix. Thesis consist of: 70 p. text without extras, 45 pictures, 14 tables, 14 bibliographical entries and 11 internet entries. Appendixes included.

Physical inactivity is one of the major public health problems in many parts of the World. In Scotland it is reported that two thirds of Scottish adults (>16yrs) and one third of Scottish children (<16yrs) do not do sufficient physical activity to gain the health benefits of physical activity. Furthermore, there is still much debate about the nature and volume of physical activity required to provide health benefits. Therefore, more investigations are required to help improve our understanding of the links between physical activity, obesity and health. In addition, the assessment of habitual physical activity needs to be accurately quantified using appropriate methods that are valid and reliable. The main aims of this thesis were thus to assess the validity and reliability of three new generations of movement sensing devices (Actigraph, ActivPAL and SenseWear PRO2) in adults and adolescents in a controlled laboratory environment and to then use the most valid and reliable device in assessing the habitual physical activity of adults (lean and overweigh/obese) and adolescents in a free-living situation. Following objectively assessing the habitual physical activity, investigation of the associations between physical activity status and cardiovascular and metabolic disease risk markers in adults and adolescents were the last main aims of this thesis. In the first study, the results indicated that the new generations of the three devices were reliable in assessing EE during walking on the flat and on a 5% incline in lean and overweight/obese adults and lean adolescents. However, none iii of these devices and the methods or programme versions that were selected and applied was able to accurately estimate EE during walking on a treadmill. However, based on the sensitivity data obtained and previous evidence, the Actigraph was considered the most appropriate device for assessing the habitual physical activity due to its ability to discriminate between physical activity intensities. The second and third studies concluded that adults (including lean and overweight/obese) met the recommended physical activity guidelines for health and wellbeing purposes. However, the data suggest that overweight/obese participants may need to be advised to spend more time in MVPA and probably more vigorous activity to not only reduce body fat but also to increase cardiorespiratory fitness and reduce their chances of future cardiovascular and metabolic disease. The fourth and fifth studies, demonstrated that the Scottish adolescents –in the cross sectional study- were below the recommended physical activity guidelines. When the method of physical activity assessment was adjusted the Scottish adolescents were similar to the adolescents in other European countries and were observed to be more active than adolescents in some of the developed countries such as American adolescents (Texas State). In the case of lean adolescents who have a low physical activity- but who are not sedentary- the cardiovascular and metabolic disease risk markers may not be obvious at this stage, but the differences in glucose and HOMA-IR suggest that there may be early signs of progression towards metabolic disease in this group. iv The importance of the associations between vigorous physical activity and body fat, as well as between body fat and the risk markers of metabolic disease, suggests that future intervention studies should focus on monitoring the outcome from vigorous physical activity interventions vs. moderate activity within current guidelines.

Le travail présenté dans ce mémoire concerne la réalisation d’un microsystème intégrant une centrale inertielle permettant la détection de mouvements. Le microsystème étudié est composé d’un accéléromètre capacitif associé à son électronique de traitement. L’accéléromètre capacitif a conduit à l’élaboration d’un outil logiciel afin de le pré-dimensionner. Ce pré-dimensionnement a été effectué en fonction des spécifications de l’application et de la technologie de fabrication. Cet outil intègre des modèles fluidiques et électrostatiques en vue de calculer des paramètres du modèle de l’accéléromètre pour une simulation système. L’électronique de traitement de l’accéléromètre capacitif a été conçue autour d’un convertisseur ”Sigma-Delta”. L’architecture ”Sigma-Delta” a nécessité des modifications pour pouvoir être adaptée au capteur. Nous avons alors développé, sous ”Matlab-Simulink”, une bibliothèque de composants permettant d’ajuster le fonctionnement du convertisseur. Une fois l’architecture optimisée et les caractéristiques des composants connues, la conception de l’architecture ”Sigma-Delta” est ainsi réalisable sous le logiciel CADENCE. / The aim of this thesis is the realisation of microsystem for movements detection. This microsystem is composed of capacitive accelerometers and of their electronics. The conception of capacitive accelerometers has induced developement of a software for the first dimensionnement of sensors. This software computes parameters of capacitive accelerometers thanks to electrostatic models, flow models, specifications of application and fabrication process. The electronics of capacitive accelerometer is a ”Sigma-Delta” convertor. The adaptation of convertor leads to developement of components libraries for ”Matlab-Simulink”. The simulation systems allows to fit parametres convertor for the application. After that,the conception of convertor under CADENCE software is then possible.

The growing presence of the Internet in day-to-day tasks, along with the evolution of computational systems, contributed to increase data exposure. This scenario highlights the need for safer user authentication systems. An alternative to deal with this is by the use of biometric systems. However, biometric features may change over time, an issue that can affect the recognition performance due to an outdated biometric reference. This effect can be called as template ageing in the area of biometrics and as concept drift in machine learning. It raises the need to automatically adapt the biometric reference over time, a task performed by adaptive biometric systems. This thesis studied adaptive biometric systems considering biometrics in a data stream context. In this context, the test is performed on a biometric data stream, in which the query samples are presented one after another to the biometric system. An adaptive biometric system then has to classify each query and adapt the biometric reference. The decision to perform the adaptation is taken by the biometric system. Among the biometric modalities, this thesis focused on behavioural biometrics, particularly on keystroke dynamics and on accelerometer biometrics. Behavioural modalities tend to be subject to faster changes over time than physical modalities. Nevertheless, there were few studies dealing with adaptive biometric systems for behavioural modalities, highlighting a gap to be explored. Throughout the thesis, several aspects to enhance the design of adaptive biometric systems for behavioural modalities in a data stream context were discussed: proposal of adaptation strategies for the immune-based classification algorithm Self-Detector, combination of genuine and impostor models in the Enhanced Template Update framework and application of score normalization to adaptive biometric systems. Based on the investigation of these aspects, it was observed that the best choice for each studied aspect of the adaptive biometric systems can be different depending on the dataset and, furthermore, depending on the users in the dataset. The different user characteristics, including the way that the biometric features change over time, suggests that adaptation strategies should be chosen per user. This motivated the proposal of a modular adaptive biometric system, named ModBioS, which can choose each of these aspects per user. ModBioS is capable of generalizing several baselines and proposals into a single modular framework, along with the possibility of assigning different adaptation strategies per user. Experimental results showed that the modular adaptive biometric system can outperform several baseline systems, while opening a number of new opportunities for future work. / A crescente presença da Internet nas tarefas do dia a dia, juntamente com a evolução dos sistemas computacionais, contribuiu para aumentar a exposição dos dados. Esse cenário evidencia a necessidade de sistemas de autenticação de usuários mais seguros. Uma alternativa para lidar com isso é pelo uso de sistemas biométricos. Contudo, características biométricas podem mudar com o tempo, o que pode afetar o desempenho de reconhecimento devido a uma referência biométrica desatualizada. Esse efeito pode ser chamado de template ageing na área de sistemas biométricos adaptativos ou de mudança de conceito em aprendizado de máquina. Isso levanta a necessidade de adaptar automaticamente a referência biométrica com o tempo, uma tarefa executada por sistemas biométricos adaptativos. Esta tese estudou sistemas biométricos adaptativos considerando biometria em um contexto de fluxo de dados. Neste contexto, o teste é executado em um fluxo de dados biométrico, em que as amostras de consulta são apresentadas uma após a outra para o sistema biométrico. Um sistema biométrico adaptativo deve então classificar cada consulta e adaptar a referência biométrica. A decisão de executar a adaptação é tomada pelo sistema biométrico. Dentre as modalidades biométricas, esta tese foca em biometria comportamental, em particular em dinâmica da digitação e em biometria por acelerômetro. Modalidades comportamentais tendem a ser sujeitas a mudanças mais rápidas do que modalidades físicas. Entretanto, havia poucos estudos lidando com sistemas biométricos adaptativos para modalidades comportamentais, destacando uma lacuna para ser explorada. Ao longo da tese, diversos aspectos para aprimorar o projeto de sistemas biométricos adaptativos para modalidades comportamentais em um contexto de fluxo de dados foram discutidos: proposta de estratégias de adaptação para o algoritmo de classificação imunológico Self-Detector, combinação de modelos genuíno e impostor no framework do Enhanced Template Update e aplicação de normalização de scores em sistemas biométricos adaptativos. Com base na investigação desses aspectos, foi observado que a melhor escolha para cada aspecto estudado dos sistemas biométricos adaptativos pode ser diferente dependendo do conjunto de dados e, além disso, dependendo dos usuários no conjunto de dados. As diferentes características dos usuários, incluindo a forma como as características biométricas mudam com o tempo, sugerem que as estratégias de adaptação deveriam ser escolhidas por usuário. Isso motivou a proposta de um sistema biométrico adaptativo modular, chamado ModBioS, que pode escolher cada um desses aspectos por usuário. O ModBioS é capaz de generalizar diversos sistemas baseline e propostas apresentadas nesta tese em um framework modular, juntamente com a possibilidade de atribuir estratégias de adaptação diferentes por usuário. Resultados experimentais mostraram que o sistema biométrico adaptativo modular pode superar diversos sistemas baseline, enquanto que abre um grande número de oportunidades para trabalhos futuros.