Smoothness is a hallmark of healthy movement and has the potential to be used as a marker of recovery in rehabilitation settings. While much past research has focused on shoulder and elbow movements (reaching), little is known about movements of the wrist despite its importance in everyday life and its impairment in many neurological and biomechanical disorders. Our current lack of knowledge regarding wrist movement prevents us from improving current models, diagnosis, and treatment of wrist disorders. In particular, while movement smoothness is a well-known characteristic of reaching movements and may potentially be used to diagnose and monitor recovery from neurological impairments, little is known about the smoothness of wrist rotations. Therefore, because the smoothness of wrist rotations has not been characterized, it cannot be used as a marker for diagnosis and evaluation. This study examines the smoothness of wrist rotations in comparison to the known baseline of reaching movements. Subjects were asked to perform wrist and reaching movements under a variety of conditions, including different speed and direction. To measure movement smoothness, this study used an established metric of speed profile number of maxima and presents a novel method for characterizing smoothness by fitting a minimum-jerk trajectory to real movement data.The results show that 1) wrist rotations are significantly less smooth than reaching movements (p≤0.0016), 2) smoothness decreases significantly as speed decreases (p<0.0001), and 3) wrist movements exhibit a pattern of smoothness that varies significantly between targets and outbound/inbound movement directions (p<0.0001). Potential causes for results 1 and 3 are presented and tested by simulation or reference to prior studies, because these findings were previously unknown. The decrease in smoothness with speed (result 2) has been found in prior studies of smoothness in reaching and finger movements. The reasoning behind the first result is explored by testing whether the difference in smoothness between wrist and reaching movements was due to differences in mechanical, muscular, neural, or protocol-related properties. The reasoning behind the third result is explored by testing whether the difference in wrist direction was due to anisotropy in musculoskeletal dynamics or anisotropy in movement duration. The simulations show that the wrist’s bandwidth is greater than that of the arm, and that there is nonvoluntary power in the bandwidth of the wrist that would be low-pass filtered in reaching movements, indicating that at least some of the difference in smoothness between wrist and reaching movements is due to differences in mechanical properties. Differences in muscular, neural, or protocol-related properties (signal-dependent noise, proprioceptive acuity, and the speed requirements of the task, respectively) do not appear to be the cause of the difference in smoothness between wrist and reaching movements. Differences in wrist smoothness between movement directions appears to be related to differences in movement duration between directions.

This thesis studies real-time reference ramping of human input for remotely operated vehicles and its effect on system control, power usage, and user experience. The implementation, testing, and evaluation were done on the remotely operated Blueye Pioneer underwater drone. The developed method uses minimum jerk trajectories for transitioning between varying target velocities with a constant end jerk target. It has a low computational cost and runs in real-time on the Blueye Pioneer underwater drone. The presented method produces a well-defined reference with continuous position, velocity, and acceleration states that can be used in the feedback loop. Experiments and simulations show that the method produces a smoother and more predictable motion path for the user. The motions are better suited for video recordings and remote navigation, compared to the direct usage of human input velocity. The smoother reference reduces the controller tracking error, the peak control input, and the energy usage. The introduced acceleration reference state is used for feedforward control on the system. It improves the feeling of controlling the drone by reducing the system lag, the position tracking error, and the rise time for velocity changes.

The purpose of this thesis is to evaluate Rapid Control Prototyping which is apart of the Model-Based Design concept that makes it possible to convenientlytest prototype control algorithms directly on the real system. The evaluation ishere done by designing two different controllers, a gain-scheduled P controllerand a linear Model Predictive Controller (mpc), for the lowering of the forks of aforklift.The two controllers are first tested in a simulation environment. The thesis con-tains two different simulation models: one physical where only minor parameteradjustments are done and one estimated black-box model. After evaluating thecontrollers in a simulation environment they are tested on a real forklift with areal-time target machine.The designed controllers have different strengths and weaknesses as one is non-linear and single variable, the P controller, and the other linear and multivariable,thempc. The P controller has a smooth movement in all situations without be-ing slow, unlike thempc. The disadvantage of the P controller compared to thempcis that there is no guarantee that the P controller will keep the speed limit,whereas thempcapproach gives such a guarantee.The better performance of the P controller outweighs the speed limit guaranteeand thus a conclusion is drawn that the nonlinearities of the system has a largereffect than the multivariable aspect. Also, another conclusion drawn is that work-ing with Model-Based Design and Rapid Control Prototyping makes it possibleto test many different ideas on a real forklift without spending a lot of time onimplementation. / Syftet med detta examensarbete är att utvärdera Rapid Control Prototyping vil-ket är en del av modellbaserad utveckling som gör det möjligt att enkelt testamodeller av styralgoritmer direkt på det riktiga systemet. Utvärderingen är gjordgenom att testa två olika regulatorer, en P-regulator med parameterstyrning ochen linjär modelbaserad prediktionsregulator (mpc), för sänkningen av gafflarnapå en truck.De två regulatorerna testas först i en simuleringsmiljö. I arbetet används två olikasimuleringsmodeller: en fysikalisk där endast mindre parameterjusteringar görsoch en estimerad black-box modell. Efter att regulatorerna utvärderas i simule-ringsmiljön testas de även på en riktig truck med hjälp av automatisk kodgenere-ring och exekvering på en dedikerad hårdvaruplattform.De konstruerade regulatorerna har olika för- och nackdelar eftersom en är olinjäroch envariabel, P-regulatorn, och en är linjär men flervariabel,mpc:n. P-regulatornhar en mjuk rörelse i alla lägen utan att bli för långsam, till skillnad frånmpc:n.Nackdelen med P-regulatorn, jämfört medmpc:n är att det inte finns någon ga-ranti för att P-regulatorn håller hastighetsbegränsningen sommpc:n gör.P-regulatorns bättre prestanda överväger garantin om att hålla hastighetsbegräns-ningen och därför dras slutsatsen att olinjäriteterna i systemet överväger effekter-na av det faktum att det också är flervariabelt. En annan slutsats är att modell-baserad utveckling och Rapid Control Prototyping gör det möjligt att testa fleraolika idéer på en riktig gaffeltruck utan att spendera för mycket tid på implemen-tationen.

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Cette thèse porte sur la modélisation et vérification des signatures en ligne. La première partie a pour thème principal la modélisation biomécanique des mouvements de la main. Un modèle basé sur le critère de Minimum de Secousse (MS) a été choisi parmi plusieurs théories du contrôle moteur. Ensuite, le problème de la segmentation des trajectoires en traits qui correspondent au modèle cinématique choisi a été étudié, ce qui a conduit à la mise au point d'une méthode de segmentation itérative. Le choix du modèle et de la méthode de segmentation sont basé sur le compromis entre la qualité de reconstruction et la compression. Dans la deuxième partie, le modèle polynomial issu du critère de MS est volontairement dégradé. Les zéros non-Réels des polynômes sont jetés et les effets de cette dégradation sont étudiés dans une perspective de vérification biométrique. Cette dégradation est équivalente à la technique connue sous le nom d’Infinity Clipping, initialement appliqué à des signaux de parole. Pour les signatures en ligne, comme pour la parole, la préservation de l'information essentielle a été observée sur des tâches de vérification de signature. En fait, en utilisant seulement la distance de Levenshtein sur la représentation dégradée, un taux d'erreur comparable à ceux des méthodes plus élaborées a été obtenu. En outre, la représentation symbolique issue de l’Infinity Clipping permet d’établir une relation conceptuelle entre le nombre de segments obtenus par la segmentation itératif basée sur le MS et la complexité de Lempel-Ziv. Cette relation est potentiellement utile pour l'analyse des signatures en ligne et pour l’amélioration des systèmes de reconnaissance / This thesis deals with the modelling and verification of online signatures. The first part has as main theme the biomechanical modelling of hand movements associated to the signing gesture. A model based on the Minimum Jerk (MJ) criterion was chosen amongst the several available motor control theories. Next, the problem of signature trajectory segmentation into strokes that better fit the chosen kinematic model is studied, leading to the development of an iterative segmentation method. Both the choice of the model and the segmentation method are strongly based on the tradeoff between reconstruction quality and compression. On the second part, the polynomial model provided by the MJ criterion is intentionally degraded. The non-Real zeroes of the polynomials are discarded and the effects of this degradation are studied from a biometric verification perspective. This degradation is equivalent to the signal processing technique known as Infinity Clipping, originally applied to speech signals. On signatures, as for speech, the preservation of essential information was observed on signature verification tasks. As a matter of fact, using only the Levenshtein distance over the infinitely clipped representation, verification error rates comparable to those of more elaborate methods were obtained. Furthermore, the symbolic representation yielded by the infinity clipping technique allows for a conceptual relationship between the number of polynomial segments obtained through the Minimum Jerk-Based iterative segmentation and the Lempel-Ziv complexity. This relationship is potentially useful for the analysis of online signature signals and the improvement of recognition systems