A demanda crescente por petróleo impulsiona a exploração marítima desta riqueza para águas cada vez mais profundas. O aumento da lâmina dágua exige novas soluções de engenharia principalmente no que se refere à operação de unidades flutuantes de produção. Dentre os desafios impostos pelos novos ambientes de prospecção, destaca-se o processo de ancoragem, neste texto explorado sob a ótica da chamada estaca-torpedo. Embora já tenha sido empregada com sucesso na ancoragem de risers e FPSOs, esta solução encontra-se em constante desenvolvimento, sendo a principal fonte de informação acerca dos lançamentos da estaca-torpedo proveniente de uma unidade de medição inercial (UMI). A presente pesquisa baseou-se no estudo desta UMI e teve como objetivos principais verificar seu desempenho e compreender a empregabilidade deste tipo de monitoração em operações submarinas de maneira mais ampla. Além do estudo detalhado dos sensores, foi dada especial atenção aos algoritmos empregados no tratamento dos sinais provenientes da UMI. Foram estudadas técnicas de correção do sinal, quantificação de ruído, desafios inerentes aos sistemas do tipo strapdown e o processo de integração. Como resultado final foi desenvolvido um algoritmo baseado em quatérnios, alternativo ao atualmente empregado para o processamento dos sinais provenientes da UMI que equipa a estaca-torpedo. / The increasing demand on crude oils constantly pushes the offshore exploitation to deeper waters. As the water depth grows, new engineering challenges arise, especially concerning to the operation of floating production units. Among all the technical issues inherent to the new prospection environment, the mooring system is a significant topic and the development of the torpedo-pile takes place at this scenario. This mooring system has already been successfully applied in anchoring risers and FPSOs; nevertheless, it is in constant study and improvement. The major source of information about the torpedo-pile deployment comes from an inertial measurement unit (IMU). The research presented here is based on this IMU and had as main objective verify its performance and also comprehend the applicability of such kind of unit in other subsea processes. Along with the detailed sensors study, it was given special attention to the algorithms used to process the signals from the IMU. Signal correction techniques and noise quantification were investigated as long as challenges intrinsically related to strapdown navigation systems and the integration process. In the end, an alternative data processing algorithm based on quaternions was produced, to be employed in torpedo-pile launching together with its IMU.

Submitted by Kevin Quispe (kgmq@icomp.ufam.edu.br) on 2018-10-26T19:02:31Z No. of bitstreams: 1 dissertação-kevin-quispe-final.pdf: 2744401 bytes, checksum: cf4d3337afb0d9fa244abbd4ec3d1a5a (MD5) / Approved for entry into archive by Secretaria PPGI (secretariappgi@icomp.ufam.edu.br) on 2018-10-26T19:07:43Z (GMT) No. of bitstreams: 1 dissertação-kevin-quispe-final.pdf: 2744401 bytes, checksum: cf4d3337afb0d9fa244abbd4ec3d1a5a (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2018-10-26T19:15:25Z (GMT) No. of bitstreams: 1 dissertação-kevin-quispe-final.pdf: 2744401 bytes, checksum: cf4d3337afb0d9fa244abbd4ec3d1a5a (MD5) / Made available in DSpace on 2018-10-26T19:15:25Z (GMT). No. of bitstreams: 1 dissertação-kevin-quispe-final.pdf: 2744401 bytes, checksum: cf4d3337afb0d9fa244abbd4ec3d1a5a (MD5) Previous issue date: 2018-08-14 / Human activity recognition (RAH) through sensors embedded in wearable devices such as smartphones has allowed the development of solutions capable of monitoring human behavior. However, such solutions have presented limitations in terms of efficiency in the consumption of computational resources and generalization for different application or data domain configurations. These limitations are explored in this work in the feature extraction process, in which existing solutions use a manual approach to extract the characteristics of the sensor data. To overcome the problem, this work presents an automatic approach to feature extraction based on the symbolic representation of time series --- representation defined by sets of discrete symbols (words). In this context, this work presents an extension of the symbolic representation of the Bag-Of-SFA-Symbols (BOSS) method to handle the processing of multiple time series, reduce data dimensionality and generate compact and efficient classification models. The proposed method, called Multivariate Bag-Of-SFA-Symbols (MBOSS), is evaluated for the classification of physical activities from data of inertial sensors. Experiments are conducted in three public databases and for different experimental configurations. In addition, the efficiency of the method is evaluated in aspects such as computing time and data space. The results, in general, show an efficiency of classification equivalent to the solutions based on the traditional approach of manual extraction, highlighting the results obtained in the database with nine classes of activities (UniMib SHAR), where MBOSS obtained an accuracy of 99% and 87% for the custom and generalized template, respectively. The efficiency results of MBOSS demonstrate the low computational cost of the solution and show the feasibility of application in smartphones. / O reconhecimento de atividade humanas (RAH) por meio de sensores embutidos em dispositivos vestíveis como, por exemplo, smartphones tem permitido o desenvolvimento de soluções capazes de monitorar o comportamento humano. No entanto, tais soluções têm apresentado limitações em termos de eficiência no consumo dos recursos computacionais e na generalização para diferentes configurações de aplicação ou domínio de dados. Essas limitações são exploradas neste trabalho no processo de extração de características, na qual as soluções existentes utilizam uma abordagem manual para extrair as características dos dados de sensores. Para superar o problema, este trabalho apresenta uma abordagem automática de extração de características baseada na representação simbólica de séries temporais --- representação definida por conjuntos de símbolos discretos (palavras). Nesse contexto, este trabalho apresenta uma extensão do método de representação simbólica Bag-Of-SFA-Symbols (BOSS) para lidar com o processamento de múltiplas séries temporais, reduzir a dimensionalidade dos dados e gerar modelos de classificação compactos e eficiêntes. O método proposto, denominado Multivariate Bag-Of-SFA-Symbols (MBOSS), é avaliado para a classificação de atividades físicas a partir de dados de sensores inerciais. Experimentos são conduzidos em três bases de dados públicas e para diferentes configurações experimentais. Além disso, avalia-se a eficiência do método em aspectos como tempo de computação e espaço de dados. Os resultados, em geral, demostram uma eficácia de classificação equivalente as soluções baseadas na abordagem comun de extração manual de características, destacando os resultados obtidos na base de dados com nove classes de atividades (UniMib SHAR), onde o MBOSS obteve uma acurácia de 99% e 87% para o modelo personalizado e generalizado, respectivamente. Os resultados de eficiência do MBOSS demostram o baixo custo computacional da solução e mostram a viabilidade de aplicação em smartphones.

Face aux limites auxquelles doivent faire face les systèmes optoélectroniques (matériel lourd, champ de mesure limité), les capteurs inertiels constituent une alternative prometteuse pour la mesure du mouvement humain. Grâce aux dernières avancées techniques, notamment en termes de miniaturisation des capteurs, leur utilisation en ambulatoire c’est-à-dire de façon autonome et embarquée est devenue possible. Mais ces opérations de miniaturisation ne sont pas sans effet sur les performances de ces capteurs. En effet, une telle mesure est dégradée par différents types de perturbations (stochastiques et déterministes) qui sont alors propagées au cours du processus dit de fusion des données visant à estimer l'orientation des segments humains. Classiquement, cette opération est réalisée à l'aide d'un filtre de Kalman dont le rôle est justement d'estimer une grandeur à partir d'une mesure bruitée en la confrontant à un modèle d'évolution.Dans ce contexte, nous proposons diverses méthodologies dans le but d'accéder à une mesure suffisamment précise pour être exploitée dans le cadre de l'analyse du mouvement humain. La première partie de cette thèse se focalise sur les capteurs. Tout d'abord, nous étudions les bruits de mesure issus des capteurs inertiels, puis nous leur attribuons un modèle afin de les prendre en compte au sein du filtre de Kalman. Ensuite, nous analysons les procédures de calibrage et évaluons leurs effets réels sur la mesure afin d'émettre quelques propositions en termes de compromis performance/facilité de réalisation.Dans une seconde partie, nous nous consacrons à l'algorithme de fusion des données. Après avoir proposé un filtre de Kalman adapté à la mesure du mouvement humain, nous nous focalisons sur un problème récurrent à ce stade : l'identification des matrices de covariance dont le rôle est d'attribuer une caractérisation globale aux erreurs de mesure. Cette méthode, basée sur une confrontation de la mesure avec une référence issue d'un système optoélectronique, met en évidence la nécessité de traiter ce problème rigoureusement.Dans une troisième partie, nous commençons à aborder les problèmes liés à l'utilisation des capteurs inertiels pour la mesure du mouvement humain, notamment le calibrage anatomique et le positionnement des capteurs.En conclusion, les gains apportés par les diverses propositions avancées dans cette thèse sont évalués et discutés. / To face the limits of optoelectronic systems (heavy device, restricted measurement field), inertial sensors are a promising alternative for human motion analysis. Thanks to the latest technical advancements like sensor miniaturization, they can now work autonomously which makes possible to directly embed them on the human segments. But, as a counterpart of these developments, inertial sensor measurement still suffers from both stochastic and deterministic perturbations. The induced errors then propagate over the so-called fusion algorithm used to estimate human segment orientation. A common tool to perform such an operation is the Kalman filter that estimates unknown variables by correcting noisy measurements by the use of a dynamic model.With the aim of achieving a sufficiently accurate measurement to perform human motion analysis, various methodologies are proposed in the present work. The first part of this thesis focuses on the sensors. First, inertial sensor noises are studied and modeled in order to be integrated into the Kalman filter. Calibration processes as their effects over the measurement are for that purposed analyzed. Some recommendations are thus proposed to reach a compromise between calibration performance and complexity.In a second part, the data fusion algorithm is approached. A specific Kalman filter dedicated to human motion measurement is first proposed. Then, a recurrent problem is studied in details: the definition of the covariance matrix that represents a globalcharacterization of the measurement errors. Considering an optoelectronic system as a reference to compare inertial measurement, a method is proposed for this covariance matrix identification, which also highlights the need to address this problem rigorously.In a third part, we begin to address the use of inertial sensors for human motion analysis by focusing on models and IMU-to-segment calibration.To conclude, the benefits made by the proposed methodologies are evaluated and discussed.

Playing a musical instrument is a very beautiful, but very physically demanding craft. Many musicians suffer from musculoskeletal pain caused, among other things, by a rigid, unchanging posture and a focus on performance at the expense of comfort. The theoretical part of the thesis deals with the influence of music production on the musculoskeletal system of the musician and the possibilities of therapy aimed at improving sensorimotor skills and kinesthesia. The practical part followed the influence of therapy inspired by the Feldenkrais method and Alexander's technique on the movement of the musician during and outside the performance. The research was conducted on 19 professional string musicians. Testing of probands consisted of measurements with inertial sensors, objective measurements of sensorimotor skills and kinesthesia and a questionnaire survey. The parameter measured by the inertial sensors was a jerk (indicates the smoothness of the movement). The results of the measurements show that, even after a single therapy, the smoothness of the chest movement improved statistically significantly.

The loss of mobility among the elderly has become a significant health and socio-economic concern worldwide. Poor mobility due to gradual deterioration of the musculoskeletal system causes older adults to be more vulnerable to serious health risks such as joint injuries, bone fractures and traumatic brain injury. The costs associated with the treatment and management of these injuries are a huge financial/social burden on the government, society and family. Knee is one of the key joints that bear most of the body weight, so its proper function is essential for good mobility. Further, Continuous monitoring of the knee joint can potentially provide important quantitative information related to knee health and mobility that can be utilized for health assessment and early diagnoses of mobility-related problems. In this research work, we developed an easy-to-use, low-cost, multi-sensor-based wearable device to monitor and assess the knee joint and proposed an analysis system to characterize and classify an individual’s knee joint features with respect to the baseline characteristics of his/her peer group. The system is composed of a set of different miniaturized sensors (inertial motion, temperature, pressure and galvanic skin response) to obtain linear acceleration, angular velocity, skin temperature, muscle pressure and sweat rate of a knee joint during different daily activities. A database is constructed from 70 healthy adults in the age range from 18 to 86 years using the combination of all signals from our knee joint monitoring system. In order to extract relevant features from the datasets, we employed computationally efficient methods such as complementary filter and wavelet packet decomposition. Minimum redundancy maximum relevance algorithm and principal component analysis were used to select key features and reduce the dimension of the feature vectors. The obtained features were classified using the support vector machine, forming two distinct clusters in the baseline knee joint characteristics corresponding to gender, age, body mass index and knee/leg health condition. Thus, this simple, easy‐to‐use, cost-effective, non-invasive and unobtrusive knee monitoring system can be used for real-time evaluation and early diagnoses of joint disorders, fall detection, mobility monitoring and rehabilitation. / Thesis / Master of Applied Science (MASc)

In der vorliegenden Publikation wird ein Verfahren beschrieben, dass eine infrastrukturlose Positionierung im Inneren von Gebäuden ermöglicht. Unter infrastrukturlos wird in diesem Zusammenhang die autarke Positionierung eines Systems auf Basis seiner Inertialsensorik ohne den Einsatz von im Gebäude installierter Zusatzlösungen, wie Funksysteme, verstanden. Aufgrund der insbesondere über die Zeit erhöhten Fehlerbehaftung solcher Sensoren werden bei diesem Verfahren Innenraumkarten in den Lokalisierungsprozess einbezogen. Diese Kartendaten erlauben den Ausschluss invalider Positionen und Bewegungen, wie das Durchqueren von Wänden, und ermöglichen somit eine wesentliche Verbesserung der Ortungsgenauigkeit.

Dans ce mémoire, nous présentons l'étude d'un senseur inertiel à ondes de matière embarqué dans un avion effectuant des vols paraboliques.Une source laser bi-fréquence robuste et compacte permettant de refroidir et d'interroger simultanément des atomes de 87Rb et 39K a été développée. Elle est basée sur des lasers télécom asservis sur un peigne de fréquences optique et doublés en fréquence. L'utilisation de composants optiques fibrés permet de rendre le système intrinsèquement résistant aux vibrations et aux fluctuations thermiques. Le dispositif a été validé en vol par l'obtention d'un double piège magnéto-optique.Nous avons utilisé la source laser pour faire fonctionner un interféromètre à atomes froids de 87Rb dans l'avion. Un accéléromètre mécanique auxiliaire permet d'augmenter la dynamique du capteur atomique et d'enregistrer des franges d'interférences malgré le niveau élevé des fluctuations d'accélération. Le senseur hybride ainsi réalisé a une résolution de 4.10-3 m.s-2.Hz-1/2, environ 100 fois plus faible que le niveau des vibrations dans l'avion.Dans la perspective de réaliser un test du principe d'équivalence en microgravité avec des atomes froids, nous étudions enfin de manière théorique le fonctionnement d'un interféromètre différentiel et nous intéressons à l'influence de certains effets systématiques. / In this thesis, we report on the study of a matter-wave inertial sensor, operated in an airplane carrying out parabolic flights.We have developped a compact and robust dual-wavelength laser source to cool and interrogate 87Rb and 39K atoms. It is based on frequency-doubled telecom lasers locked on a femtosecond optical frequency comb. The use of fibered optical components makes the setup intrinsically immune to vibrations and thermal fluctuations. The laser source was validated in flight by obtaining a double-species magneto-optical trap.We have used the source to carry out airborne measurements with an atom interferometer operating with cold 87Rb atoms. An auxiliary mechanical accelerometer makes it possible to increase the atomic sensor's dynamic range, and to record interference fringes despite the high level of acceleration fluctuations. This hybrid sensor has a resolution of 4.10-3 m.s-2.Hz-1/2, which is approximately 100 times lower than the typical vibration level in the plane.In the perspective of testing the equivalence principle with cold atoms in microgravity, we finally theoretically study the operation of a differential interferometer and investigate the influence of some systematic effects.

På avdelningen Medicinsk Teknik-Forskning och Utveckling på Norrlands Universitetssjukhus (MT-FoU) pågår en utveckling av ett rörelsemätsystem (MoLab) som syftar till att ge kvantitativa data från individer med nedsatt rörelsefunktion. Denna information kan fungera som underlag för behandling och användas för att utvärdera uppföljning av behandlingar. Mätsystemet begränsas idag av att det är beroende av en accesspunkt med tillhörande lokalt nätverk för att föra över data till insamlingsdator via TCP/IP-protokollet.   Examensarbetet syftar till att öka mätsystemets mobilitet genom att inkludera en portabel och trådlös mätlösning utan krav på stationär accesspunkt och insamlingsdator vid insamlingstillfället. Med ett mer mobilt mätsystem kan data inhämtas från individer i dennes autentiska och vardagliga miljö.   En lokal lagringsyta har kopplats till sensorenheterna och användargränssnittet utgörs istället av en fjärrkontroll, som startar och stoppar mätningar. Fjärrkontrollen fungerar också som en accesspunkt som sensorenheterna ansluter till och som vidarebefordrar start- och stoppsignaler via UDP-broadcast från fjärrkontroll till alla uppkopplade sensorenheter. Vid given stoppsignal överförs sensordata till fjärrkontrollen för efterföljande lagring på dess interna minneskort. Det är viktigt att mätningarna sker synkront mellan sensorenheterna, där startsynkroniseringen kan kvantifieras som tidsdifferensen mellan sensorenheternas mätstart.  Med metoden som föreslås i detta arbete, hamnar startsynkroniseringen väl under ett väldefinierat tröskelvärde på 2 ms som också fanns implementerat i MoLab och är därför en tänkbar metod för att utöka mobiliteten för MoLab. / The department of Biomedical Engineering Research and Development at University Hospital (MT-FoU) is developing a motion measurement system (MoLab) that aims to provide quantitative data from individuals with impaired mobility. This information can serve as a basis for treatments and used to evaluate follow-up of treatments. The measuring system is today limited by the fact that it is dependent on an access point and associated local network to communicate data to an evaluation computer via the TCP/IP protocol. This is a bachelor thesis that aims to give this measuring system greater freedom to measure without dependence of a stationary access point and evaluation computer. With a more mobile system, data can be obtained in a more authentic and everyday environment for the individuals to be measured.  An internal memory has been connected to the inertial sensor devices, and the user interface is instead a remote control, which starts and stops measurements. The remote-control acts as the access point which the sensor devices connects to and start and stop signals are transmitted via UDP broadcast from the remote-control to the sensor devices. In case of a given stop signal, sensor data is transferred to the internal memory of the remote control. It is important that the measurements take place synchronously where the synchronization can be quantified as the time difference between the sensor devices at the measurement start. With this method, start synchronization ends up well below a well-defined threshold value of 2 ms that was also implemented in MoLab, giving it greater mobility.

Apresenta-se o desenvolvimento de modelos matemáticos e algoritmos de fusão sensorial para navegação terrestre usando uma unidade de medição inercial (UMI) de baixo desempenho e o Filtro Estendido de Kalman. Os modelos foram desenvolvidos com base nos sistemas de navegação inercial strapdown (SNIS). O termo baixo desempenho refere-se à UMIs que por si só não são capazes de efetuar o auto- alinhamento por girocompassing. A incapacidade de se navegar utilizando apenas uma UMI de baixo desempenho motiva a investigação de técnicas que permitam aumentar o grau de precisão do SNIS com a utilização de sensores adicionais. Esta tese descreve o desenvolvimento do modelo completo de uma fusão sensorial para a navegação inercial de um veículo terrestre usando uma UMI de baixo desempenho, um hodômetro e uma bússola eletrônica. Marcas topográficas (landmarks) foram instaladas ao longo da trajetória de teste para se medir o erro da estimativa de posição nesses pontos. Apresenta-se o desenvolvimento do Filtro de Kalman Adaptativo Suavizado (FKAS), que estima conjuntamente os estados e o erro dos estados estimados do sistema de fusão sensorial. Descreve-se um critério quantitativo que emprega as incertezas de posição estimadas pelo FKAS para se determinar a priori, dado os sensores disponíveis, o intervalo de tempo máximo que se pode navegar dentro de uma margem de confiabilidade desejada. Conjuntos reduzidos de landmarks são utilizados como sensores fictícios para testar o critério de confiabilidade proposto. Destacam-se ainda os modelos matemáticos aplicados à navegação terrestre, unificados neste trabalho. Os resultados obtidos mostram que, contando somente com os sensores inerciais de baixo desempenho, a navegação terrestre torna-se inviável após algumas dezenas de segundos. Usando os mesmos sensores inerciais, a fusão sensorial produziu resultados muito superiores, permitindo reconstruir trajetórias com deslocamentos da ordem de 2,7 km (ou 15 minutos) com erro final de estimativa de posição da ordem de 3 m. / This work presents the development of the mathematical models and the algorithms of a sensor fusion system for terrestrial navigation using a low-grade inertial measurement unit (IMU) and the Extended Kalman Filter. The models were developed on the basis of the strapdown inertial navigation systems (SINS). Low-grade designates an IMU that is not able to perform girocompassing self-alignment. The impossibility of navigating relying on a low performance IMU is the motivation for investigating techniques to improve the SINS accuracy with the use of additional sensors. This thesis describes the development of a comprehensive model of a sensor fusion for the inertial navigation of a ground vehicle using a low-grade IMU, an odometer and an electronic compass. Landmarks were placed along the test trajectory in order to allow the measurement of the error of the position estimation at these points. It is presented the development of the Smoothed Adaptive Kalman Filter (SAKF), which jointly estimates the states and the errors of the estimated states of the sensor fusion system. It is presented a quantitative criteria which employs the position uncertainties estimated by SAKF in order to determine - given the available sensors, the maximum time interval that one can navigate within a desired reliability. Reduced sets of landmarks are used as fictitious sensors to test the proposed reliability criterion. Also noteworthy are the mathematical models applied to terrestrial navigation that were unified in this work. The results show that, only relying on the low performance inertial sensors, the terrestrial navigation becomes impracticable after few tens of seconds. Using the same inertial sensors, the sensor fusion produced far better results, allowing the reconstruction of trajectories with displacements of about 2.7 km (or 15 minutes) with a final error of position estimation of about 3 m.

L’Onera développe des capteurs inertiels MEMS vibrants avec des performances qui peuvent intéresser des applications spatiales. Les électroniques analogiques traditionnellement associées ne sont à priori pas limitantes par rapport aux performances physiques des capteurs. En revanche, elles se montrent encombrantes, non reconfigurables, et ne délivrent pas les grandeurs mesurées sous forme numérique à l’ordinateur de bord. En outre,dans le cadre d’une utilisation spatiale, elles sont sujettes à dépendance et à obsolescence :le remplacement d’un composant implique une nouvelle qualification.Cette thèse propose une nouvelle architecture numérique générique, limitant au maximum les composants analogiques nécessaires. Les travaux portent principalement sur deux capteurs développés par l’Onera : l’accéléromètre à lame vibrante VIA et le gyromètre vibrant à effet Coriolis VIG, mais sont justement transposables à d’autres familles. Une première fonction clé identifiée est la datation d’évènements pour la mesure de fréquence et de phase, une seconde concerne la synthèse numérique directe de fréquence pour le pilotage de résonateurs, et une troisième traite la génération de signaux sinusoïdaux purs à partir des trains binaires délivrés par le système numérique. Ces fonctions sont réalisées sous forme de périphériques numériques autour d’un processeur embarqué, le tout synthétisé sur composant programmable FPGA. Le manuscrit débute par un rappel des lois physiques et des technologies de mesure inertielle, suivi d’une revue des oscillateurs, analogiques et numériques, afin de déterminer l’architecture numérique souhaitée. Le chapitre suivant aborde de façon théorique les fonctions numériques envisagées, et en détermine les éléments de performance. La mise en oeuvre de ces fonctions et les premiers résultats expérimentaux sont ensuite présentés d’abord au niveau de la fonction seule, et enfin dans une architecture complète incluant le capteur et le logiciel embarqué, pour fournir de vraies mesures inertielles. Ces résultats encouragent le déploiement d’électronique numérique dans les prochaines générations de capteurs. / Onera has been developing vibrating inertial MEMS sensors with performances good enough for space uses. Associated conventional analog electronics are not limiting the physical performances of the sensors. They are, however, bulky, not reconfigurable, and do not deliver digital measurements to the on-board computer. Furthermore, when used for space applications, they have to cope with dependency and obsolescence requiring a new qualification when any part is changed.This thesis offers a new digital generic architecture with as few analog parts as possible. Work has been focused on two sensors developed by Onera: the VIA, a vibrating beam accelerometer, and the VIG, a Coriolis vibrating gyro, but can address other sensors. A first digital function identified is event timestamping for frequency and phase measurements; a second key function is the direct digital synthesis of the oscillating sensors driving signal; the third one generates pure sine signals from binary sequences output from the digital platform. These function are implemented as peripherals of an embedded processor on a FPGA.This dissertation firstly reminds physical laws and technologies of inertial measurements, followed by a quick review of oscillators, analog and digital, in order to introduce the chosen digital architecture. A following chapter studies the theory of the digital functions considered and identifies their performances. Afterwards, realisations and first experimental results are exposed, at a function level first, at a global level then, with the sensor and the embedded software to provide real inertial readings. The results gathered boost the idea of deploying digital electronics in future sensor releases.