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41	Platform development of body area network for gait symmetry analysis using IMU and UWB technology Persson, Anders January 2018 (has links) Having a device with the capability of measure motions from gait produced by a human being, could be of most importance in medicine and sports. Physicians or researchers could measure and analyse key features of a person's gait for the purpose of rehabilitation or science, regarding neurological disabilities. Also in sports, professionals and hobbyists could use such a device for improving their technique or prevent injuries when performing. In this master thesis, I present the research of what technology is capable of today, regarding gait analysis devices. The research that was done has then help the development of a suggested standalone hardware sensor node for a Body Area Network, that can support research in gait analysis. Furthermore, several algorithms like for instance UWB Real-Time Location and Dead Reckoning IMU/AHRS algorithms, have been implemented and tested for the purpose of measuring motions and be able to run on the sensor node device. The work in this thesis shows that a IMU sensor have great potentials for generating high rate motion data while performing on a small mobile device. The UWB technology on the other hand, indicates a disappointment in performance regarding the intended application but can still be useful for wireless communication between sensor nodes. The report also points out the importance of using a high performance micro controller for achieving high accuracy in measurements. BAN Body Area Network gait gait symmetry gait symmetry analysis IMU inertial measurement unit UWB Ultra Wide-Band sensor node sensors sensor fusion electronics hardware Engineering and Technology Teknik och teknologier Elektroteknik och elektronik Embedded Systems Inbäddad systemteknik Communication Systems Kommunikationssystem Robotics Robotteknik och automation Signal Processing Signalbehandling Computer Systems Datorsystem Annan elektroteknik och elektronik Medicinsk laboratorie- och mätteknik Medical Equipment Engineering Medicinsk apparatteknik
42	Cooperative wireless channel characterization and modeling: application to body area and cellular networks Liu, Lingfeng 23 March 2012 (has links) Cooperative wireless communication is an attractive technique to explore the spatial channel resources by coordination across multiple links, which can greatly improve the communication performance over single links. In this dissertation, we study the cooperative multi-link channel properties by geometric approaches in body area networks (BANs) and cellular networks respectively.<p><p>In the part of BANs, the dynamic narrowband on-body channels under body motions are modeled statistically on their temporal and spatial fading based on anechoic and indoor measurements. Common body scattering is observed to form inter-link correlation between links closely distributed and between links having synchronized movements of communication nodes. An analytical model is developed to explain the physical mechanisms of the dynamic body scattering. The on-body channel impacts to simple cooperation protocols are evaluated based on realistic measurements. <p><p>In the part of cellular networks, the cluster-level multi-link COST 2100 MIMO channel model is developed with concrete modeling concepts, complete parameterization and implementation methods, and a compatible structure for both single-link and multi-link scenarios. The cluster link-commonness is introduced to the model to describe the multi-link properties. The multi-link impacts by the model are also evaluated in a distributed MIMO system by comparing its sum-rate capacity at different ratios of cluster link-commonness. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished Electricité Sciences exactes et naturelles Wireless communication systems Wireless sensor networks Transmission sans fil Réseaux de capteurs sans fil visibility region capacity channel modeling cooperative wireless communication multiple cylinder scattering Doppler spectrum 2.4 GHz IEEE 802.15.6 UWB COST 2100 channel model MIMO cooperative relay cluster DMC BAN body area network distributed MIMO diversity polarization MPC on-body channel dynamic body scattering surface wave fading shadowing pathloss cross-channel correlation
43	Enhanching the Human-Team Awareness of a Robot Wåhlin, Peter January 2012 (has links) The use of autonomous robots in our society is increasing every day and a robot is no longer seen as a tool but as a team member. The robots are now working side by side with us and provide assistance during dangerous operations where humans otherwise are at risk. This development has in turn increased the need of robots with more human-awareness. Therefore, this master thesis aims at contributing to the enhancement of human-aware robotics. Specifically, we are investigating the possibilities of equipping autonomous robots with the capability of assessing and detecting activities in human teams. This capability could, for instance, be used in the robot's reasoning and planning components to create better plans that ultimately would result in improved human-robot teamwork performance. we propose to improve existing teamwork activity recognizers by adding intangible features, such as stress, motivation and focus, originating from human behavior models. Hidden markov models have earlier been proven very efficient for activity recognition and have therefore been utilized in this work as a method for classification of behaviors. In order for a robot to provide effective assistance to a human team it must not only consider spatio-temporal parameters for team members but also the psychological.To assess psychological parameters this master thesis suggests to use the body signals of team members. Body signals such as heart rate and skin conductance. Combined with the body signals we investigate the possibility of using System Dynamics models to interpret the current psychological states of the human team members, thus enhancing the human-awareness of a robot. / Användningen av autonoma robotar i vårt samhälle ökar varje dag och en robot ses inte längre som ett verktyg utan som en gruppmedlem. Robotarna arbetar nu sida vid sida med oss och ger oss stöd under farliga arbeten där människor annars är utsatta för risker. Denna utveckling har i sin tur ökat behovet av robotar med mer människo-medvetenhet. Därför är målet med detta examensarbete att bidra till en stärkt människo-medvetenhet hos robotar. Specifikt undersöker vi möjligheterna att utrusta autonoma robotar med förmågan att bedöma och upptäcka olika beteenden hos mänskliga lag. Denna förmåga skulle till exempel kunna användas i robotens resonemang och planering för att ta beslut och i sin tur förbättra samarbetet mellan människa och robot. Vi föreslår att förbättra befintliga aktivitetsidentifierare genom att tillföra förmågan att tolka immateriella beteenden hos människan, såsom stress, motivation och fokus. Att kunna urskilja lagaktiviteter inom ett mänskligt lag är grundläggande för en robot som ska vara till stöd för laget. Dolda markovmodeller har tidigare visat sig vara mycket effektiva för just aktivitetsidentifiering och har därför använts i detta arbete. För att en robot ska kunna ha möjlighet att ge ett effektivt stöd till ett mänskligtlag måste den inte bara ta hänsyn till rumsliga parametrar hos lagmedlemmarna utan även de psykologiska. För att tyda psykologiska parametrar hos människor förespråkar denna masteravhandling utnyttjandet av mänskliga kroppssignaler. Signaler så som hjärtfrekvens och hudkonduktans. Kombinerat med kroppenssignalerar påvisar vi möjligheten att använda systemdynamiksmodeller för att tolka immateriella beteenden, vilket i sin tur kan stärka människo-medvetenheten hos en robot. / <p>The thesis work was conducted in Stockholm, Kista at the department of Informatics and Aero System at Swedish Defence Research Agency.</p> robotics Artificial Intelligence AI System Dynamics Wireless Body Area Network WBAN sensors Psychology physiology human behavior Human-Robot-Interaction HRI robot Human-Team awareness human-robot RapidMiner Vensim JaHMM hidden markov models HMM eclipse rcp ARFF recognizer classification cross-validation human behavior stress detection Galvanic Skin Response Heart Rate Skin Temperature Finger Temperature Electrocardiogram ECG GSR ST Pupil Diameter PD Patient monitoring GPS Data acquisition dataset data set MODERE Yerkes-Dodson SD model SD Confusion matrix spatial MOUT Java Agent robotic agent Machine Learning activity recognition team oriented robot Evaluation Decoding Learning Forward Algorithm Backward Algorithm Baum-Welch feedback loop Situation Awareness SA Shared Mental Models SMM

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