A medical study on wireless inertial measurement technology as a tool for identifying patients at risk of death or imminent clinical deterioration

This paper provides a system description and preliminary results for an ongoing clinical study currently being carried out at the Mid-Western Regional Hospital, Nenagh, Ireland. The goal of the trial is to determine if wireless inertial measurement technology can be employed to identify elderly patients at risk of death or imminent clinical deterioration. The system measures cumulative movement and provides a score that will help provide a robust early warning to clinical staff of clinical deterioration. In addition the study examines some of the logistical barriers to the adoption of wearable wireless technology in front-line medical care.

Algorithms for indoor localization based on IEEE 802.15.4-2011 UWB and inertial sensors

In this thesis, extensive experiments are firstly conducted to characterize the performance of using the emerging IEEE 802.15.4-2011 ultra wideband (UWB) for indoor localization, and the results demonstrate the accuracy and precision of using time of arrival measurements for ranging applications. A multipath propagation controlling technique is synthesized which considers the relationship between transmit power, transmission range and signal-to-noise ratio. The methodology includes a novel bilateral transmitter output power control algorithm which is demonstrated to be able to stabilize the multipath channel, and enable sub 5cm instant ranging accuracy in line of sight conditions. A fully-coupled architecture is proposed for the localization system using a combination of IEEE 802.15.4-2011 UWB and inertial sensors. This architecture not only implements the position estimation of the object by fusing the UWB and inertial measurements, but enables the nodes in the localization network to mutually share positional and other useful information via the UWB channel. The hybrid system has been demonstrated to be capable of simultaneous local-positioning and remote-tracking of the mobile object. Three fusion algorithms for relative position estimation are proposed, including internal navigation system (INS), INS with UWB ranging correction, and orientation plus ranging. Experimental results show that the INS with UWB correction algorithm achieves an average position accuracy of 0.1883m, and gets 83% and 62% improvements on the accuracy of the INS (1.0994m) and the existing extended Kalman filter tracking algorithm (0.5m), respectively.

Validation of fixed speed induction generator models for inertial response using wind farm measurements

This paper outlines the use of phasor measurement unit (PMU) records to validate models of fixed speed induction generator (FSIG)-based wind farms during frequency transients. Wind turbine manufacturers usually create their own proprietary models which they can supply to power system utilities for stability studies, subject to confidentiality agreements. However, it is desirable to confirm the accuracy of supplied models with measurements from the particular installation, in order to assess their validity under real field conditions. This is prudent due to possible changes in control algorithms and design retrofits, not accurately reflected or omitted in the supplied model. One important aspect of such models, especially for smaller power systems with limited inertia, is their accuracy during system frequency transients. This paper, therefore, assesses the accuracy of FSIG models with regard to frequency stability, and hence validates a subset of the model dynamics. Such models can then be used with confidence to assess wider system stability implications. The measured and simulated response of a wind farm using doubly fed induction generator (DFIG) technology is also assessed.

Application of Visual-Inertial SLAM for 3D Mapping of Underground Environments

The underground scenarios are one of the most challenging environments for accurate and precise 3d mapping where hostile conditions like absence of Global Positioning Systems, extreme lighting variations and geometrically smooth surfaces may be expected. So far, the state-of-the-art methods in underground modelling remain restricted to environments in which pronounced geometric features are abundant. This limitation is a consequence of the scan matching algorithms used to solve the localization and registration problems. This paper contributes to the expansion of the modelling capabilities to structures characterized by uniform geometry and smooth surfaces, as is the case of road and train tunnels. To achieve that, we combine some state of the art techniques from mobile robotics, and propose a method for 6DOF platform positioning in such scenarios, that is latter used for the environment modelling. A visual monocular Simultaneous Localization and Mapping (MonoSLAM) approach based on the Extended Kalman Filter (EKF), complemented by the introduction of inertial measurements in the prediction step, allows our system to localize himself over long distances, using exclusively sensors carried on board a mobile platform. By feeding the Extended Kalman Filter with inertial data we were able to overcome the major problem related with MonoSLAM implementations, known as scale factor ambiguity. Despite extreme lighting variations, reliable visual features were extracted through the SIFT algorithm, and inserted directly in the EKF mechanism according to the Inverse Depth Parametrization. Through the 1-Point RANSAC (Random Sample Consensus) wrong frame-to-frame feature matches were rejected. The developed method was tested based on a dataset acquired inside a road tunnel and the navigation results compared with a ground truth obtained by post-processing a high grade Inertial Navigation System and L1/L2 RTK-GPS measurements acquired outside the tunnel. Results from the localization strategy are presented and analyzed.

Lorentz-violating dilatations in momentum space and some extensions on nonlinear actions of Lorentz-algebra-preserving systems

We work on some general extensions of the formalism for theories which preserve the relativity of inertial frames with a nonlinear action of the Lorentz transformations on momentum space. Relativistic particle models invariant under the corresponding deformed symmetries are presented with particular emphasis on deformed dilatation transformations. The algebraic transformations relating the deformed symmetries with the usual (undeformed) ones are provided in order to preserve the Lorentz algebra. Two distinct cases are considered: a deformed dilatation transformation with a spacelike preferred direction and a very special relativity embedding with a lightlike preferred direction. In both analysis we consider the possibility of introducing quantum deformations of the corresponding symmetries such that the spacetime coordinates can be reconstructed and the particular form of the real space-momentum commutator remains covariant. Eventually feasible experiments, for which the nonlinear Lorentz dilatation effects here pointed out may be detectable, are suggested.

Investigation of the Impacts of Large-Scale Wind Power Penetration on the Angle and Voltage Stability of Power Systems

The complexity of power systems has increased in recent years due to the operation of existing transmission lines closer to their limits, using flexible AC transmission system (FACTS) devices, and also due to the increased penetration of new types of generators that have more intermittent characteristics and lower inertial response, such as wind generators. This changing nature of a power system has considerable effect on its dynamic behaviors resulting in power swings, dynamic interactions between different power system devices, and less synchronized coupling. This paper presents some analyses of this changing nature of power systems and their dynamic behaviors to identify critical issues that limit the large-scale integration of wind generators and FACTS devices. In addition, this paper addresses some general concerns toward high compensations in different grid topologies. The studies in this paper are conducted on the New England and New York power system model under both small and large disturbances. From the analyses, it can be concluded that high compensation can reduce the security limits under certain operating conditions, and the modes related to operating slip and shaft stiffness are critical as they may limit the large-scale integration of wind generation.

Development of motion analysis protocols based on inertial sensors

The aim of this thesis was to describe the development of motion analysis protocols for applications on upper and lower limb extremities, by using inertial sensors-based systems. Inertial sensors-based systems are relatively recent. Knowledge and development of methods and algorithms for the use of such systems for clinical purposes is therefore limited if compared with stereophotogrammetry. However, their advantages in terms of low cost, portability, small size, are a valid reason to follow this direction. When developing motion analysis protocols based on inertial sensors, attention must be given to several aspects, like the accuracy of inertial sensors-based systems and their reliability. The need to develop specific algorithms/methods and software for using these systems for specific applications, is as much important as the development of motion analysis protocols based on them. For this reason, the goal of the 3-years research project described in this thesis was achieved first of all trying to correctly design the protocols based on inertial sensors, in terms of exploring and developing which features were suitable for the specific application of the protocols. The use of optoelectronic systems was necessary because they provided a gold standard and accurate measurement, which was used as a reference for the validation of the protocols based on inertial sensors. The protocols described in this thesis can be particularly helpful for rehabilitation centers in which the high cost of instrumentation or the limited working areas do not allow the use of stereophotogrammetry. Moreover, many applications requiring upper and lower limb motion analysis to be performed outside the laboratories will benefit from these protocols, for example performing gait analysis along the corridors. Out of the buildings, the condition of steady-state walking or the behavior of the prosthetic devices when encountering slopes or obstacles during walking can also be assessed. The application of inertial sensors on lower limb amputees presents conditions which are challenging for magnetometer-based systems, due to ferromagnetic material commonly adopted for the construction of idraulic components or motors. INAIL Prostheses Centre stimulated and, together with Xsens Technologies B.V. supported the development of additional methods for improving the accuracy of MTx in measuring the 3D kinematics for lower limb prostheses, with the results provided in this thesis. In the author’s opinion, this thesis and the motion analysis protocols based on inertial sensors here described, are a demonstration of how a strict collaboration between the industry, the clinical centers, the research laboratories, can improve the knowledge, exchange know-how, with the common goal to develop new application-oriented systems.

Dynamic stabilization of Rayleigh-Taylor instability of ablation fronts in inertial confinement fusion

One of the most important problems in inertial confinement fusion is how to find a way to mitigate the onset of the Rayleigh-Taylor instability which arises in the ablation front during the compression. In this thesis it is studied in detail the possibility of using for such a purpose the well-known mechanism of dynamic stabilization, already applied to other dynamical systems such as the inverted pendulum. In this context, a periodic acceleration superposed to the background gravity generates a vertical vibration of the ablation front itself. The effects of different driving modulations (Dirac deltas and square waves) are analyzed from a theoretical point of view, with a focus on stabilization of ion beam driven ablation fronts, and a comparison is made, in order to look for optimization.

Movement Analysis by means of inertial sensors: from bench to bedside

in the everyday clinical practice. Having this in mind, the choice of a simple setup would not be enough because, even if the setup is quick and simple, the instrumental assessment would still be in addition to the daily routine. The will to overcome this limit has led to the idea of instrumenting already existing and widely used functional tests. In this way the sensor based assessment becomes an integral part of the clinical assessment. Reliable and validated signal processing methods have been successfully implemented in Personal Health Systems based on smartphone technology. At the end of this research project there is evidence that such solution can really and easily used in clinical practice in both supervised and unsupervised settings. Smartphone based solution, together or in place of dedicated wearable sensing units, can truly become a pervasive and low-cost means for providing suitable testing solutions for quantitative movement analysis with a clear clinical value, ultimately providing enhanced balance and mobility support to an aging population.

Three-dimensional joint kinematics of swimming using body-worn inertial and magnetic sensors

Wearable inertial and magnetic measurements units (IMMU) are an important tool for underwater motion analysis because they are swimmer-centric, they require only simple measurement set-up and they provide the performance results very quickly. In order to estimate 3D joint kinematics during motion, protocols were developed to transpose the IMMU orientation estimation to a biomechanical model. The aim of the thesis was to validate a protocol originally propositioned to estimate the joint angles of the upper limbs during one-degree-of-freedom movements in dry settings and herein modified to perform 3D kinematics analysis of shoulders, elbows and wrists during swimming. Eight high-level swimmers were assessed in the laboratory by means of an IMMU while simulating the front crawl and breaststroke movements. A stereo-photogrammetric system (SPS) was used as reference. The joint angles (in degrees) of the shoulders (flexion-extension, abduction-adduction and internal-external rotation), the elbows (flexion-extension and pronation-supination), and the wrists (flexion-extension and radial-ulnar deviation) were estimated with the two systems and compared by means of root mean square errors (RMSE), relative RMSE, Pearson’s product-moment coefficient correlation (R) and coefficient of multiple correlation (CMC). Subsequently, the athletes were assessed during pool swimming trials through the IMMU. Considering both swim styles and all joint degrees of freedom modeled, the comparison between the IMMU and the SPS showed median values of RMSE lower than 8°, representing 10% of overall joint range of motion, high median values of CMC (0.97) and R (0.96). These findings suggest that the protocol accurately estimated the 3D orientation of the shoulders, elbows and wrists joint during swimming with accuracy adequate for the purposes of research. In conclusion, the proposed method to evaluate the 3D joint kinematics through IMMU was revealed to be a useful tool for both sport and clinical contexts.

Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs

Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as a fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range-based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranges and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1:3m for mean accuracy and 2:2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

Fine-grained indoor positioning and tracking systems

Indoor positioning has attracted considerable attention for decades due to the increasing demands for location based services. In the past years, although numerous methods have been proposed for indoor positioning, it is still challenging to find a convincing solution that combines high positioning accuracy and ease of deployment. Radio-based indoor positioning has emerged as a dominant method due to its ubiquitousness, especially for WiFi. RSSI (Received Signal Strength Indicator) has been investigated in the area of indoor positioning for decades. However, it is prone to multipath propagation and hence fingerprinting has become the most commonly used method for indoor positioning using RSSI. The drawback of fingerprinting is that it requires intensive labour efforts to calibrate the radio map prior to experiments, which makes the deployment of the positioning system very time consuming. Using time information as another way for radio-based indoor positioning is challenged by time synchronization among anchor nodes and timestamp accuracy. Besides radio-based positioning methods, intensive research has been conducted to make use of inertial sensors for indoor tracking due to the fast developments of smartphones. However, these methods are normally prone to accumulative errors and might not be available for some applications, such as passive positioning. This thesis focuses on network-based indoor positioning and tracking systems, mainly for passive positioning, which does not require the participation of targets in the positioning process. To achieve high positioning accuracy, we work on some information of radio signals from physical-layer processing, such as timestamps and channel information. The contributions in this thesis can be divided into two parts: time-based positioning and channel information based positioning. First, for time-based indoor positioning (especially for narrow-band signals), we address challenges for compensating synchronization offsets among anchor nodes, designing timestamps with high resolution, and developing accurate positioning methods. Second, we work on range-based positioning methods with channel information to passively locate and track WiFi targets. Targeting less efforts for deployment, we work on range-based methods, which require much less calibration efforts than fingerprinting. By designing some novel enhanced methods for both ranging and positioning (including trilateration for stationary targets and particle filter for mobile targets), we are able to locate WiFi targets with high accuracy solely relying on radio signals and our proposed enhanced particle filter significantly outperforms the other commonly used range-based positioning algorithms, e.g., a traditional particle filter, extended Kalman filter and trilateration algorithms. In addition to using radio signals for passive positioning, we propose a second enhanced particle filter for active positioning to fuse inertial sensor and channel information to track indoor targets, which achieves higher tracking accuracy than tracking methods solely relying on either radio signals or inertial sensors.