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In this article, we present a low-cost multimodal tactile sensor capable of providing accelerometer, gyroscope, and pressure data using a seven-axis chip as a sensing element. This approach reduces the complexity of the tactile sensor design and collection of multimodal data. The tactile device is composed of a top layer (a printed circuit board (PCB) and a sensing element), a middle layer (soft rubber material), and a bottom layer (plastic base) forming a sandwich structure. This approach allows the measurement of multimodal data when force is applied to different parts of the top layer of the sensor. The multimodal tactile sensor is validated with analyses and experiments in both offline and real-time. First, the spatial impulse response and sensitivity of the sensor are analyzed with accelerometer, gyroscope, and pressure data systematically collected from the sensor. Second, the estimation of contact location from a range of sensor positions and force values is evaluated using accelerometer and gyroscope data together with a convolutional neural network (CNN) method. Third, the estimation of contact location is used to control the position of a robot arm. The results show that the proposed multimodal tactile sensor has the potential for robotic applications, such as tactile perception for robot control, human-robot interaction, and object exploration.

This article demonstrates the performance of an improved particle swarm optimization (PSO) algorithm with scalar checking and rotation axis fitting objectives using in-orbit data, which is obtained from two CubeSats missions, Aalto-1 and ESTCube-1, as well as simulation as reference. The improved algorithm uses sequential objectives refinement process to combine the two optimization objectives. This improvement addresses some challenges of magnetometer calibration when using in-orbit data. First, the change in the magnetic field vector direction at different points in orbit which is uncorrelated to the rotation of the spacecraft itself. Second, the uncertainty of the rotation axis information used as the reference, e.g., from gyroscope noise. Third, the available data set is heavily affected by the rotation mode of the spacecraft, which imposes some limitation in the rotation axis information needed by the algorithm. The improved PSO algorithm is applied on simulated data in order to analyze the calibration performance under different spacecraft tumbling rates and noise levels. In ideal condition (varying rotation axis during measurements and sufficient sampling rate relative to the spin rate), the rotation axis fitting objective can reach ∼0.1° of correction accuracy.

As the market for high-precision sensor devices continues to expand, there are increasing demands on sensor performance to fulfil both existing and new applications. This in turn drives improvements in device design, characterisation and manufacture, often requiring multi-disciplinary research. One such device, the InnaLabs Coriolis Vibratory Gyroscope (CVG), is the focus of such research in this work. This thesis focusses on the piezoelectric transducers at the core of this CVG system. A basic description of system-level operation is provided, and core sensor components are described in detail. A significant issue with the transducer’s solder attachment layer is investigated using designed experiments, leading to considerable improvements in quality and process simplifications. The topic of residual stresses in the soldered assembly is then investigated using the finite element technique, where the potential impacts on downstream processes (and hence final device performance) are also examined. Finally, the dynamic behaviour of the transducers in different modes is examined both experimentally and numerically, leading to increased understanding of component performance. This work aims to expand and improve understanding of transducer behaviour within CVG systems, thereby leading to future improvements in sensor performance.

This research introduces a closed-loop method to improve the zero-rate output (ZRO) stability of amplitude-modulated (AM) capacitive MEMS gyroscopes, even in absence of quadrature compensation electrodes. The method relies on the direct measurement and closed-loop compensation of the variation of the relative phase between the quadrature output, modulated by the drive carrier frequency, and the demodulation reference. The closed loop includes a phase meter, whose output regulates the phase of the lock-in amplifier inside the sense-mode, open-loop, demodulation chain. The proposed technique, tested on the pitch axis of a consumer-grade commercial monolithic 3-axis gyroscope, brings up to 300-fold stability improvements over temperature transients, without affecting noise and scale-factor performance. Stability limits depend on the phase meter resolution and on the lock-in granularity in regulating the phase. Overall, a mdps/K stability is obtained with a one-time calibration at ambient temperature and no post-acquisition processing. [2021-0049]

Nowadays, the amount of elder people living alone is increasing, with all the risks that it involves, maybe the most dangerous threat that they face is fall off with nobody around to help them. A fall at an advanced age usually leads to consequences like bones and hip fracture, which in addition to the low mobility that these people present, make to stand up impossible for them. This situation can get worse if after the fall a person loses consciousness, making it impossible to contact to a third party for help by means of a mobile phone or something similar. Different solutions have been developed in order to accomplish this problem, but some of them are not realistic enough, for example some video solutions invade our privacy, and those which are based on mobile phones expect the user to go everywhere with it. In this paper, it is proposed a low cost solution based on an 9-axis IMU (Inertial Measure Unit), which counts with an accelerometer, gyroscope and magnetometer that will give us the needed information to build a fall detector supported by machine learning. This system will include a gateway, which will be responsible of the data collection and the most complex computations., Hoy en día, la cantidad de personas mayores que viven solas va en aumento, con todos los riesgos que ello implica, quizás la amenaza más peligrosa a la que se enfrentan es caer sin nadie cerca que les ayude. Una caída a edad avanzada suele acarrear secuelas como fracturas de huesos y cadera, que además de la poca movilidad que presentan estas personas, les imposibilitan ponerse de pie. Esta situación puede empeorar si tras la caída la persona pierde el conocimiento, imposibilitando el contacto con un tercero para pedir ayuda a través de un teléfono móvil o similar. Se han desarrollado diferentes soluciones para solucionar este problema, pero algunas no son lo suficientemente realistas, por ejemplo, algunas soluciones de video invaden nuestra privacidad, y las que están basadas en teléfonos móviles esperan que el usuario vaya a todas partes con él. En este papel, Se propone una solución de bajo costo basada en una IMU (Unidad de Medida Inercial) de 9 ejes, la cual cuenta con un acelerómetro, giroscopio y magnetómetro que nos dará la información necesaria para construir un detector de caídas apoyado en aprendizaje automático. Este sistema incluirá una puerta de enlace, que será responsable de la recopilación de datos y los cálculos más complejos.

Accelerometer of the Microelectromechanical systems (MEMS) based inertial measurement units (IMUs) is key to inclination measurement in the industry 4.0. However, external vibration negatively impacts the precision of orientation angles during operation. Many inclinometer companies have demanded to develop a solution for vibration impact on accelerometer without other sensors' support because of economic problems. This article presents a new algorithm Orientation Axes Crossover Processing (OACP) on vibration optimization for MEMS accelerometer without sensor fusion. The proposed filter works on a principle based on the characteristics of vibration impact on whether the X-axis or Y-axis to optimally minimize the noise. A high accurate setup is built-up based on the Pan-Tilt Unit and a TUMAC vibrator for the verification of new filters, implemented into LSM9DS1 (3D accelerometer, 3D gyroscope). The new filter is able to work independently, and also fuse with the Low-pass filter or Kalman filter to enhance the dynamic response, only 0.163 seconds as maximum delay during vibration. The experimental results show that the proposed algorithm always accomplishes smaller variations than Low-pass filter, about 0.2 degrees in standard deviation. The compromise between vibration immunity and dynamic response is analyzed in detail to demonstrate the optimal performances of the concerned filters. The project was carried out at the `Sensor System' in Italy which is an industrial company in the inclinometer field.

A low-cost and miniature vibration recorder was developed to capture the vibration data of drilling motors for their health assessment. The recorder is installed in the rotor catch of a conventional drilling motor in such a way that no additional length is added to the bottom hole assembly. The recorder is fitted with two triaxial vibration accelerometers with different ranges, a rate gyroscope, a temperature sensor, and an integrated circuit (IC) for timestamps. The recorder can log data over the full operation cycle of a drilling motor, including vibration during surface activities and downhole operation. It allows the vibration recorders to be easily deployed to motor operations. The vibration recorder has been deployed to drilling motors in unconventional horizontal wells. The data analysis showed that the recorder captured vibration data from the installation of the recorder in maintenance bases until the return of the tools. Not only downhole drilling vibration data were successfully obtained, but also surface vibration data during shipment, and rig-side handling was recorded; the vibration recorders provided adequate information of a drilling motor to asset owners for maintenance and operation optimisation.

Photonic bandgap fiber-optic gyroscope has excellent environment adaptability and shows great prospect. The coupling between hollow-core photonic bandgap fiber coil and integrated-optic circuit is a crucial technology in photonic bandgap fiber-optic gyroscope. A low-loss low-back-reflection method for the coupling between a hollow-core photonic bandgap fiber and integrated-optic circuit is proposed. The end-face of the hollow-core photonic bandgap fiber only needs to be flat-cleaved with a general fiber cleaver. The optimal coupling angle is determined and experimentally verified to overcome the effect caused by the air gap between angle-cleaved integrated-optic circuit and flat-cleaved hollow-core photonic bandgap fiber end-face. Experimental results reveal that the coupling loss and back-reflection of the hollow-core photonic bandgap fiber with the integrated-optic circuit are better than ~3.2 dB and ~-43 dB, respectively. Compared with conventional butt coupling and fusion splicing, the coupling performance of the proposed method is significantly improved, which can achieve low-loss, low-back-reflection, and high reliability. The method provides a foundation for the coupling between hollow-core photonic bandgap fiber coil and integrated-optic circuit in fiber optic gyroscope.

Human Activity Recognition (HAR) systems are devised for continuously observing human behavior - primarily in the fields of environmental compatibility, sports injury detection, senior care, rehabilitation, entertainment, and the surveillance in intelligent home settings. Inertial sensors, e.g., accelerometers, linear acceleration, and gyroscopes are frequently employed for this purpose, which are now compacted into smart devices, e.g., smartphones. Since the use of smartphones is so widespread now-a-days, activity data acquisition for the HAR systems is a pressing need. In this article, we have conducted the smartphone sensor-based raw data collection, namely H-Activity , using an Android-OS-based application for accelerometer, gyroscope, and linear acceleration. Furthermore, a hybrid deep learning model is proposed, coupling convolutional neural network and long-short term memory network (CNN-LSTM), empowered by the self-attention algorithm to enhance the predictive capabilities of the system. In addition to our collected dataset ( H-Activity ), the model has been evaluated with some benchmark datasets, e.g., MHEALTH, and UCI-HAR to demonstrate the comparative performance of our model. When compared to other models, the proposed model has an accuracy of 99.93% using our collected H-Activity data, and 98.76% and 93.11% using data from MHEALTH and UCI-HAR databases respectively, indicating its efficacy in recognizing human activity recognition. We hope that our developed model could be applicable in the clinical settings and collected data could be useful for further research.

The problem of the active stabilization of ship motions is particularly important in the case of pleasure boats or in any case of passenger ships, since the commercial value of the ship is directly related to the comfort of the load transported in this case “people”, considered as stresses induced on them by the vessel movements, with particular attention to roll, given the ship geometric characteristics. Naval architects developed trough the years different solutions to reduce the roll of the ship, and consequentially to increase the passengers comfort, and the development of this solutions followed the progress of technology. Active fins have been the most used, but now the gyroscope solution is coming out with interesting solutions also for large yacht with displacement over 1000 t. The paper aimed at making a interactive comparison between the two systems: active fins and gyroscopes, trough the case study of a yacht of 77.77 m, in order to evaluate if, assuming the same capability to reduce the roll for each one of the two systems, there are other advantages or disadvantages from the point of view of the naval architecture, in particular the resistance of the hull. In fact the importance of the resistance on high Froude number hulls, like planning hulls it is well known, but the paper aimed at giving result useful for naval architects also on traditional displacement hulls, like the one considered here, in order to give also a contribution for preliminary design. The interactivity of the process has been realized using not a theoretical estimation of the gain resistance of the ship according to equations etc. but real tank tests on the hull, according to International Towing Tank Conference methodology, with and without appendages.

Train is one of the most popular transportation means in the world and card body improvements focus in reducing its weight. As such, composite material parts substitute car body metal parts based on their lightness among others. New trains will contain heterogeneous parts made of composite material as well as metal. Such heterogeneous joints, require Structural Health Monitoring, to ensure good structural health and correct position. Structural Health Monitoring is a significant tool to assess the health of the car body. Being in the form of wireless accelerometer sensing network, it can ideally be employed to perform the continuous health monitoring task. In this paper we present a dual wireless and telecommunication solution of accelerometers and gyroscopes sensing network, whereby the car body is assumed to be monitored with Wi-Fi enabled devices and the data be sent to a dedicated server by Long Term Evolution connectivity. We present the overall experimental setup of such a system, which extends from the sensing to storing the data to a database residing in the server. We provide initial results of the accelerometers and the gyroscopes in laboratory trials to examine the communication between the system components.

Bulk acoustic wave gyroscopes have been researched for potential benefits such as immunity to shock and vibration and the high Q factors achievable with the bulk modes. This paper outlines an approach to address mode matching in bulk acoustic wave (BAW) disk gyroscopes using electrostatic frequency tuning. Electrostatic frequency tuning is achieved by varying the potential difference between the body of the resonator and electrodes surrounding the disk resonator. Tuning of the frequencies of both drive and sense modes is demonstrated in this work as a means to achieving mode matching. The experimental results are also compared to COMSOL simulations reporting mode matching.

This paper reports on the experimental characterization of a vacuum packaged bulk acoustic wave disk gyroscope with T-shape anchors fabricated on a (100) single-crystal silicon substrate. Improvements in key device performance parameters are achieved by implementing mode matching using electrostatic frequency tuning to decrease the frequency split between two near-degenerate bulk acoustic modes from 4 Hz to 0.4 Hz. Gyroscopic operation is demonstrated by driving one of the secondary degenerate elliptical modes while sensing the response in the other elliptical mode, both demonstrating quality factors exceeding 1 million at an operating frequency of ~976 kHz. As a result, the mechanical sensitivity of the gyroscope is improved by a factor of 7.76 times for near mode-matched operation relative to the case with no tuning of the frequency spacing between the modes. Additionally, the angle random walk and bias instability were improved from 0.042 °/√h to 0.037 °/√h and 1.65 °/h to 0.95 °/h respectively, benchmarking favorably with respect to the state-of-the-art of BAW disk gyroscopes. [2021-0151]

The Navy is interested in obtaining alternate methods of navigation for Global Positioning System (GPS) denied environments, and one candidate is precision inertial navigation using atom interferometers. A good method of modeling the behavior of a group of atoms in an interferometer is to use the Wigner distribution. In atom interferometry, the distribution of a set of atoms starts with a well-defined distribution in position and momentum space (usually Gaussian), but their positions spread more rapidly than their momenta, forming an ellipse in phase (Wigner) space. However, this ellipse can rotate as it propagates, revealing new quantum phenomena. This project models the behavior of an atom in an interferometer and investigates the underlying physics of the Wigner ellipse rotation. Although no discoveries were made, the Wigner phase space model succinctly communicates the dynamics of the atoms inside the interferometer. Ensign, United States Navy Approved for public release. Distribution is unlimited.

Human activity recognition aims to classify the user activity in various applications like healthcare, gesture recognition and indoor navigation. In the latter, smartphone location recognition is gaining more attention as it enhances indoor positioning accuracy. Commonly the smartphone’s inertial sensor readings are used as input to a machine learning algorithm which performs the classification. There are several approaches to tackle such a task: feature based approaches, one dimensional deep learning algorithms, and two dimensional deep learning architectures. When using deep learning approaches, feature engineering is redundant. In addition, while utilizing two-dimensional deep learning approaches enables to utilize methods from the well-established computer vision domain. In this paper, a framework for smartphone location and human activity recognition, based on the smartphone’s inertial sensors, is proposed. The contributions of this work are a novel time series encoding approach, from inertial signals to inertial images, and transfer learning from computer vision domain to the inertial sensors classification problem. Four different datasets are employed to show the benefits of using the proposed approach. In addition, as the proposed framework performs classification on inertial sensors readings, it can be applied for other classification tasks using inertial data. It can also be adopted to handle other types of sensory data collected for a classification task.

To detect the joint angle of the manipulator accurately, a measuring method based on an IMU sensor is proposed. The sensor's attitude angles and corresponding rotation matrix are obtained according to the data of three-axis gyroscope and three-axis accelerometer. During the installation, the sensor's Z-axis direction is kept along with the motor's rotation axis direction, so that the angle of the sensor rotating around its Z-axis, which is the rotation angle of the motor, can be calculated by comparing the rotation relationship between the sensor's initial position and the sensor's position after the motor rotating. The largest source of result error derives from the inconsistent between the sensor's Z-axis direction and the motor's rotation axis direction. Consequently, an installation's error compensation method is designed to correct the sensor's Z-axis to the motor's rotation axis by rotating the related motor. The experiments show that the method can measure the joint angle of the manipulator accurately and calibrate the installation error effectively. The measurement result errors are confined

Accidental falls of patients cannot be completely prevented. However, timely fall detection can help prevent further complications such as blood loss and unconsciousness. In this study, the authors present a cost-effective integrated system designed to remotely detect patient falls in hospitals in addition to classifying non-fall motions into activities of daily living. The proposed system is a wearable device that consists of a camera, gyroscope, and accelerometer that is interfaced with a credit card-sized single board microcomputer. The information received from the camera is used in a visual-based classifier and the sensor data is analysed using the k-Nearest Neighbour and Naïve Bayes' classifiers. Once a fall is detected, an attendant at the hospital is informed. Experimental results showed that the accuracy of the device in classifying fall versus non-fall activity is 95%. Other requirements and specifications are discussed in greater detail.

With the recent technological advancement in low-cost wireless inertial motion trackers, measuring three-dimensional motion for biomechanics research becomes more facile. However, the methods of acceleration modeling in off-the-shelf filters do not hold for all movements in sports activities with significant and long-lasting accelerations. This paper presents a robust algorithm for orientation tracking in the presence of large active accelerations lasting longer than the maximum time the MEMS gyroscopes can solely keep track of the body orientation. We particularly model the uncertainty of active acceleration and take it into explicit account in an extended Kalman filter based orientation estimator for applying measurement updates accurately in dynamic motions such as sports activities. The proposed tracker also estimates the magnetic disturbances by using an uncertainty model to improve the heading estimation. Benchmarking the results with the Vicon Optical as ground truth and the MTw kit with a specific filter for body motion tracking shows the robustness of our method against variations of acceleration in different types of motion. Our tracker performs orientation estimation in real time with fast convergence during acceleration shocks and low root-mean-square error, particularly when experiencing large accelerations in periodic motions. Accepted version

Purpose–The study aims to develop a single wearable balance rehabilitation program apparatus using array processing methods for physical therapists and for patients with balance disorders. The device which will be attached to the patient’s torso in a sitting position on a vestibular ball uses a combination of a 3-axis gyroscopes and 3-axis accelerometers and detects the body fall out threshold angle. It monitors the number of times that the patient will be out of balance during rehabilitation sessions. The device would be capable of sending data to the physical therapist’s computer during the patient’s rehabilitation session. It will provide the physical therapist a remote for monitoring the progress or regress of the patient’s condition. The device will be helpful for the patient’s recovery from their balance problem and will reduce possible injuries.Method–The device will be used by a physical therapist during his rehabilitation program in a sitting position on a vestibular ball. The threshold angle set for the device were obtained from conducting tests on what angle the patient could possibly fall on while sitting on the vestibular ball. Results–Based on the conducted test, the standard acceptable threshold angle is 25.8 degrees. This threshold angle was validated by comparing it to a previous study about sitting balance. Using cross validation technique, the accuracy of the developed balance rehabilitation apparatus was found to be 96.67%. Conclusion–The device is a single wearable device with multiple sensors attached to the patient’s torso and can accurately measure the angles with the use of the combination of 3-axis gyroscopes and accelerometers. It can monitor the shift or tilting of the body of the subject and it prompts the patient when he is about to fall from the ball. Physical Therapists could evaluate the session of the patient from the recorded number of falls.Recommendations–Future researchers may employ the help of a physical therapist in testing the efficiency, accuracy and reliability of the device. They may ask assistance in establishing the acceptability of the device and its features as it relates to the field of physical therapy. If found feasible and ethically sound, future researchers may ask for the participation of people with balance problems in testing the said device.Research Implications–The study would be significant and beneficial to physical therapists. It will provide them with an apparatus useful for the implementation of their balance rehabilitation programs. For persons dealing with balance problems, this device will help them correct or improve their stability through numbers of sessions depending on the case of their balance disorder. The device will be helpful for the person’s recovery from their balance problem and will reduce the patient’s possible injuries.

This paper proposes a technique for developing parametric models of modally degenerate resonators from stimulus-response data. The technique complements traditional empirical frequency response estimates that are commonly used for testing MEMS resonators, however, the parametric models have distinct advantages when the modal frequency differences are close enough to frustrate estimates of quality factors, natural frequencies and mode orientations. The proposed technique also completely rejects parasitic coupling between the stimulus and pick-off electrodes. It is shown how a modification of the algorithm using demodulated measurement signals greatly reduces storage and computational requirements. [2020-0281]

Device fingerprinting aims to generate a distinctive signature, or fingerprint , that uniquely identifies individual computing devices. Fingerprints may be a privacy concern since apps and websites can use them to track user activity online. To protect user privacy, both Android and iOS have included a variety of measures to prevent such tracking. In this paper we present a new type of fingerprinting, factory calibration fingerprinting , that bypasses existing tracking protection. Our attack recovers embedded per-device factory calibration data from the accelerometer, gyroscope, and magnetometer sensors that are pervasive in modern smartphones by careful analysis of the sensor output alone. We discuss the factory calibration behaviour of each sensor and show that the calibration fingerprint is fast to generate, does not change over time or after a factory reset, and can be used to track users across apps and websites without any special permission from the user. We find the calibration fingerprint is very likely to be globally unique for iOS devices, with an estimated 67 bits of entropy for the iPhone 6S. In addition, we have analysed 146 Android device models from 11 vendors and found the attack also works on recent Google Pixel devices. For Pixel 4/4 XL, we estimate the calibration fingerprint provides about 57 bits of entropy. Following our disclosures, Apple deployed a mitigation in iOS 12.2 and Google in Android 11. We analyse Apple’s fix and show that the mitigation is imperfect although it is likely to be sufficient in most threat models.

The resilience of the built environment to extreme weather events is fundamental for the day-to-day operation of our transport network, with scour representing one of the biggest threats to bridges built over flowing water. Condition monitoring of the bridge using a structural health monitoring system enhances resilience by reducing the time needed to return the bridge to normal use by providing timely information on structural condition and safety. The work presented in this report discusses use of rotational measurements in structural health monitoring. Traditionally tiltmeters (which can be a form of DC accelerometer) are used to measure rotation but are known to be affected by dynamic movements, while gyroscopes react quickly to dynamic motion but drift over time. This review will introduce gyroscopes as a complementary sensor for accelerometer rotational measurements and use sensor fusion techniques to combine the measurements from both sensors to get an optimised rotational result. This method was trialled on a laboratory scaled model, before the system was installed on an in-service single-span skewed railway bridge. The rotational measurements were compared against rotation measurements obtained using a vision-based measurement system to confirm the validity of the results. An introduction to gyroscopes, field test measurement results with the sensors and their correlation with the vision-based measurement results are presented in this article.

Structural Health Monitoring (SHM) is an area of growing interest and worthy of new and innovative approaches. As constructions get more and more complex, SHM becomes indispensable and mandatory. This is especially true for the rapidly growing transportation domain, particular in rail industry where there is an urgent need to increase the reliability of rail infrastructure, car bodies and optimise maintenance since train traffic, train speed and tonnage carried on rail networks are significantly increasing. In this work, a low cost, wireless embedded system is proposed, using the acceleration principle, to periodically sense possible cracks in a surface; hence, perform smart and continuous SHM. Specifically, the wireless sensor unit is using a cost effective accelerometer and a gyroscope. Experiments in a simple structure by simulating cracks with pencil lead breaks were performed. In order to identify the simulated cracks, a new method using Generative Adversarial Networks is used and presented in our paper.

Current sensors used for inertial navigation are based on technology with inherent sensitivity limitations. Atom interferometry is a very promising replacement, which could yield many orders of magnitude of improvement in sensitivity, leading to more accurate navigation over longer periods of time relative to current technology. This research investigates the physics of atom interferometry through the construction and characterization of an atomic accelerometer/gyroscope combination. In contrast to current state-of-the-art atomic sensors, which use pulsed cold atom sources and pulsed laser beams, the apparatus investigated relies purely on continuous atomic and laser beams. These differences would result in a sensor that lends itself more readily to smaller sizing, lower power consumption, and reduced complexity. This change in approach to atomic interferometry also introduces challenges resulting from laser and atomic beam divergences and the velocity averaging due to both longitudinal and transverse temperature, which this dissertation shows how to overcome. The work contained herein explores many stages of construction of an atomic gyro including the demonstration and characterization of two-dimensional laser cooling of atoms, stimulated Raman transitions, and Ramsey and spin echo interference. The implications for future research are also outlined and discussed. Commander, United States Navy Approved for public release. distribution is unlimited

In this paper, recent developments in the design and fabrication of micromachined fused quartz hemi-toroidal shells are presented. The fabrication is based on micro glassblowing process, demonstrated to enable the realization of high-Q MEMS resonators and gyroscopes. The design optimization of the shell geometry is performed using parametric finite element analysis. The effect of geometric parameters on the scaling of the resonant frequencies and energy dissipation are discussed. Three variations of the micro-glassblowing process are studied in the paper, concluding that shell resonators with a broad operational frequency range without losing the symmetry and Q-factor are feasible. Finite element models are presented to simulate the presented glassblowing processes, which are used to predict the final geometry of shell resonators accurately. Operational frequency as low as 5 kHz and Q-factor as high as 1.7 million is demonstrated on the fabricated shell resonators. The proposed process modifications demonstrate a low-cost and scalable fabrication of 3D shells for resonators and gyroscopes, which can be used in inertial navigation and timing applications. [2019-0179].

This paper reports the developments toward an integrated, tri-axial, frequency-modulated, consumer-grade, and microelectromechanical system (MEMS) gyroscope. A custom low-power (160 μ A), low-phase-noise integrated circuit is designed specifically for frequency-modulated operation. Both yaw- and pitch-rate sensing systems are demonstrated by coupling the circuit with two novel micromachined structures fabricated with a 24- μ m-thick industrial process. In operation, both gyroscopes show a repeatable and stable scale factor, with less than 0.55% of part-to-part variability, obtained with no any calibration, and 35 ppm/ $^{\circ }$ C of variability over a 25–70 $^{\circ }$ C temperature range.

Introduction. The correction time reduction for the spatial orientation evaluation of a solid under the orientation system initiation is considered. Solid spatial orientation is measured by the integrated values from three orthogonal angular speed sensors. Difference between the actual spatial orientation and the orientation estimated by sensors is adjusted due to the data obtained from other sensors, such as accelerometers and magnetometers. Major existing algorithms deduct data acquired from accelerometers and magnetometers from the evaluation of angular rate through the correction factor thus correcting the spatial orientation assessment error. The higher the solid inclination angle in relation to horizon when the orientation system is switched on, the greater the spatial orientation error is. The algorithm presented herein corrects the spatial orientation evaluation in quaternion components without angular rate sensors which allows minimizing the spatial orientation assessment error within shorter time in comparison with the existing algorithms. Materials and Methods. To implement the correction algorithm, the MPU6050 sensor is used. It is made with microelectromechanical technology, and its body includes three orthogonally located angular velocity sensors and three orthogonally located accelerometers. The output data from MPU6050 sensor is processed by dsPIC33EP256MU806 microchip. The spatial orientation is calculated by the Rodrigues-Hamilton parameters in the quaternion components. The result is input to the Matlab software package which executes the program of visualizing the dependencies on the time of four quaternion components graphically. Research Results . In existing algorithms that use the Rodrigues-Hamilton parameters, at the initial initialization of the orientation system, it is suggested to increase the correction factor, or to use the trigonometric formulas to find the Euler angles and translate them into the RodriguesHamilton parameters. In the first case, the initial initialization time remains sufficiently long, in the second case, due to the use of Euler angles, a phenomenon of “gimbal lock” can be observed. The proposed algorithm performs the initial initialization in a time equivalent to the initialization time in the Euler angles parameters, but it applies only the RodriguesHamilton parameters. Discussion and Conclusions. Using the proposed algorithm will allow a minimum of 5-fold reduction in the initial initialization time of the spatial orientation quaternion. In consequence, the total time required for activating the system will be also reduced due to the fact that the initial initialization is necessary every time the orientation system is switched on. For the correct determination of the spatial orientation according to the proposed algorithm, the necessary condition is the absence of any acceleration on the body other than the gravitational acceleration because the initialization occurs only upon the accelerometer readings.

A method to increase the sensitivity of an intracavity differential phase measurement that is not made irrelevant by a larger increase of noise is explored. By introducing a phase velocity feedback by way of a resonant dispersive element in an active sensor in which two ultrashort pulses circulate, it is shown that the measurement sensitivity is elevated without significantly increasing the Petermann excess noise factor. This enhancement technique has considerable implications for any optical phase based measurement; from gyroscopes and accelerometers to magnetometers and optical index measurements. Here we describe the enhancement method in the context of past dispersion enhancement studies including the recent work surrounding non-Hermitian quantum mechanics, justify the method with a theoretical framework (including numerical simulations), and propose practical applications.

This paper presents yaw and pitch micro-electromechanical system gyroscopes embedding four active nanoelectromechanical (NEMS) piezoresistive gauges each, two of which are used for differential sensing of the Coriolis motion, and two of which are innovatively used to sense the drive motion and thus to close the drive oscillation loop. After presenting the devices design, this paper discusses the advantages of this particular implementation in terms of operating voltages, electrical equivalent model, and temperature behavior of the scale factor. In operation with voltages lower than 1.8 V without voltage boosting, the devices show sub mdps/ $\surd {\rm Hz}$ noise density within areas of about 1 mm2 per device at 0.2-mbar package pressure. Under temperature sweeps, a 3.7-fold better immunity of the scale factor stability is obtained, compared with a similar gyroscope embedding combs (and not NEMS) for drive detection. [2017-0050]

Magnetic orientation systems have widely been used by measuring the earth magnetic field and provide a pervasive source of directional information. However, to obtain the high precision, orientation systems must be compensated prior to use for the various errors of magnetometers such as the bias, misalignment and inconsistence in sensitivity, and the pitch and roll angles, especially in dynamic state. In this study, magnetic orientation system mainly consist of three single-axis magnetometers, a tri-axis accelerometer and a tri-axis gyroscope were developed. An error-separation method was introduced to calibrate magnetometers. Data from magnetometers, accelerometer and gyroscope were fused based on Kalman filtering. In addition, accelerometer and gyroscope were also calibrated before data fusion. Experimental results showed the heading error of magnetic orientation system was about 0.1° in a static state, and

This study presents a novel navigation method designed to support a real-time, efficient, accurate indoor localisation for mobile robot system. It is applicable for inertial measurement units (IMU) consisting of gyroscopes, accelerometers, and magnetic besides stereo vision (SV). The current indoor mobile robot localisation technology adopts traditional active sensing devices such as laser, and ultrasonic method which belongs to the signal of localisation and navigation method which has low efficiency complex structure, and poor anti-interference ability. Through dual Kalman filter (DKF) algorithm, the accumulated error of gyroscope can be reduced, while combining with SV, mobile robot binocular SV orientation of inertial location can be realised under the DKF mechanism, which is introduced. First, high precision posture information of mobile robot can be obtained using fusing Kalman filter algorithm of accelerometer, gyroscope and magnetometer data. Second, inertial measurement precision can be optimised using Kalman filtering algorithm combined with machine vision localisation algorithm. The results indicate that the method achieves the levels of accuracy location comparable with that of the IMU/SV fusion algorithm

Micro resonators and vibratory gyroscopes could reach their fundamental thermo-elastic damping (TED) limit in an ultravacuum condition where the viscous damping is eliminated. This article presents a reliable and repeatable high vacuum sealing process as a standalone approach for performance evaluation of dynamic micro devices. We demonstrated a micro-Torr vacuum level in a ceramic leadless chip carrier package and achieved the Q-factor over 2million on a quad mass gyroscope, approaching the TED limit of the device by effectively eliminating the viscous damping. The long-term vacuum stability was characterized over 1 year and demonstrated that the Q-factor does not degrade over time and even continues improving. The long-term ultrahigh vacuum condition is enabled by surface desorption prior to sealing, pumping of residual gases by passive getters, and defect-free solder reflow in the sealing area. The experimental results confirmed the reliability and repeatability of the proposed sealing procedure, which can be adapted for other Micro Electro-Mechanical Systems (MEMS) with ultrahigh vacuum requirements.

This paper presents a calibration method for consumer-grade accelerometers, gyroscopes, and magnetometers. Considering the calibration of consumer-grade sensors, it is essential that no specialized equipment is required to create reference signals. In addition, the less is required from the reference signals, the more suitable the method is on the field. In the proposed method, the novelty in the calibration of the gyroscopes lies in the exploitation of only the known net rotations between the positions in a multi-position calibration. For accelerometers and magnetometers, the innovation is that the direction of reference signals, the gravity and the magnetic field of the Earth, are estimated with calibration parameters. As a consequence, no precise absolute alignment of the sensors is needed in the calibration. The rotations need not be done about a constant axis. In the proposed method, the biases, scale factors, misalignments, and cross-coupling errors for all the sensors as well as hard iron and soft iron effect for magnetometers were modelled. In addition, the drift of the sensors during the calibration was estimated. As a result, all the sensors were calibrated at once to the same frame, exploiting only a cube and a jig and thus, the method is eligible in the field. To estimate the quality of the calibration results, 95% confidence intervals were calculated for the calibration parameters. Simulations were done to indicate that the calibration method is unbiased. acceptedVersion

We propose a simplified, fast, and operative simulation tool for the prediction of gas damping occurring in the microelectromechanical systems (MEMS) of arbitrarily complex geometry and motion, working in near vacuum in a pressure range around 1 mbar. The tool is based on precomputed lookup tables (distributed with the paper), providing dissipation for the elemental blocks of MEMS. Next, adopting a decoupling assumption, blocks are combined according to the topology of the device to be analyzed. Particular attention is devoted to the validation of working hypotheses using numerical data generated by a refined model, data taken from the literature for simple test devices, and new experimental results for industrial gyroscopes.

In this paper, we demonstrate the analysis of coupling between drive and sense systems of vibratory gyroscopes. Vibratory gyroscopes have attracted a lot of interest recently with the development of MEMS gyroscopes. These gyroscopes made their way through portable devices and smart phones. Novel gyroscope architectures have been proposed and analyzed in detail. However, in most of these analyses, coupling between the sense and drive systems was ignored. We analytically show that drive and sense systems are coupled together via Coriolis and centrifugal force. As a result, system resonances shift as the rotation rate increase for linear and torsional gyroscope systems. Starting from a simple gyro system, we calculated the sense and drive resonant frequency shifts in various configurations. Then, for more complex systems where analytical solution is difficult to obtain, we used commercially available FEM tools to determine corresponding frequency shift. In general, we found that the shift is small and can be ignored for linear vibratory gyroscopes where $Q$ of the sense system is less than 2500 for mode matched gyros. But for higher $Q$ systems, the frequency shift may affect the linearity of these gyroscopes. This sets a fundamental limit for the linearity of vibratory gyroscopes. Based on our calculations the non-linearity is above 1% for linear 2-DOF mode-matched vibratory gyroscopes where $Q$ is above 3000 and for torsional 2-DOF vibratory gyroscopes where $Q$ is above 600. Multi-DOF and ring vibratory gyroscopes are also examined. We find that the effect is less pronounced for Multi-DOF gyros, whereas there is a large effect on the linearity of ring gyroscopes.

Background The characterization of limb biomechanics has broad implications for analyzing and managing motion in aging, sports, and disease. Motion capture videography and on-body wearable sensors are powerful tools for characterizing linear and angular motions of the body, though are often cumbersome, limited in detection, and largely non-portable. Here we examine the feasibility of utilizing an advanced wearable sensor, fabricated with stretchable electronics, to characterize linear and angular movements of the human arm for clinical feedback. A wearable skin-adhesive patch with embedded accelerometer and gyroscope (BioStampRC, MC10 Inc.) was applied to the volar surface of the forearm of healthy volunteers. Arms were extended/flexed for the range of motion of three different regimes: 1) horizontal adduction/abduction 2) flexion/extension 3) vertical abduction. Data were streamed and recorded revealing the signal “pattern” of movement in three separate axes. Additional signal processing and filtering afforded the ability to visualize these motions in each plane of the body; and the 3-dimensional motion envelope of the arm. Results Each of the three motion regimes studied had a distinct pattern – with identifiable qualitative and quantitative differences. Integration of all three movement regimes allowed construction of a “motion envelope,” defining and quantifying motion (range and shape – including the outer perimeter of the extreme of motion – i.e. the envelope) of the upper extremity. The linear and rotational motion results from multiple arm motions match measurements taken with videography and benchtop goniometer. Conclusions A conformal, stretchable electronic motion sensor effectively captures limb motion in multiple degrees of freedom, allowing generation of characteristic signatures which may be readily recorded, stored, and analyzed. Wearable conformal skin adherent sensor patchs allow on-body, mobile, personalized determination of motion and flexibility parameters. These sensors allow motion assessment while mobile, free of a fixed laboratory environment, with utility in the field, home, or hospital. These sensors and mode of analysis hold promise for providing digital “motion biomarkers” of health and disease.

Orientador: Prof. Dr. Marcos Duarte Coorientador: Prof. Dr. Renato Naville Watanabe Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Biomédica, São Bernardo do Campo, 2019. Falls and injuries while walking are recurrent problems for people who suffer from foot drop. When this condition is caused by a lesion in the central nervous system, it is possible to restore part of the gait function by applying functional electrical stimulation during specific gait events. This study had the following goals: to create an open dataset of inertial, magnetic, foot-ground contact, and electromyographic signals from wearable sensors during walking at different speeds; and to develop a multiple regression method to estimate gait events based on the data from this open dataset. Employing wearable sensors, we acquired data from 22 healthy adults and one with foot drop walking at self-selected comfortable, fast, and slow speeds, and standing still. All data are publicly available at Figshare (DOI: 10.6084/m9.figshare.7778255). The novel algorithm we proposed is based on linear multiple regression. The open dataset contains 9,661 gait strides for the healthy subjects and 496 for the subject with the foot drop. The proposed algorithm for estimating the toe-off gait event showed a median accuracy across the healthy subjects and gait speeds of 88.8%, and an accuracy of 97.3% for the affected limb of the subject with foot drop. The open dataset we created will enable researchers to test algorithms for gait-event estimation against a common reference. The algorithm presents comparable performance to other existing algorithms concerning healthy subjects and a promissing result based on one subject with foot drop. It is potentially adjustable for real-time application. Quedas e lesões durante a caminhada são problemas recorrentes para pessoas que sofrem de pé equino. Quando esta condição é causada por uma lesão no sistema nervoso central, é possível restaurar parte da função da marcha aplicando estimulação elétrica funcional durante eventos específicos da marcha. Este estudo teve os seguintes objetivos: criar uma base de dados aberta de dados inerciais, magnéticos, eletromiográficos e de contato dos pés durante a caminhada em diferentes velocidades; e desenvolver um método de regressão múltipla para estimar os eventos de marcha com base nos dados deste conjunto de dados abertos. Empregando sensores vestíveis, adquirimos dados de 22 adultos saudáveis e um com pé equino caminhando nas velocidades confortável, rápida e lenta, e parados. Todos os dados estão disponíveis publicamente no Figshare (DOI: 10.6084/m9.figshare.7778255). O novo algoritmo que propusemos é baseado em regressão linear múltipla. O conjunto de dados aberto contém 9.661 passadas para os sujeitos saudáveis e 496 para o sujeito com pé equino. O algoritmo proposto para estimar o evento toe-off da marcha mostrou uma acurácia mediana de 88,8% entre os indivíduos saudáveis e as diferentes velocidades, e uma acurácia de 97,3% para o membro afetado do sujeito com pé equino. O conjunto de dados aberto que criamos permitirá que os pesquisadores testem algoritmos para estimativa de evento de marcha em comparação a uma referência comum. O algoritmo apresenta desempenho comparável a outros algoritmos existentes em relação a indivíduos saudáveis e um resultado promissor baseado em um sujeito com pé equino. É potencialmente ajustável a aplicações em tempo-real.

This paper studies whether low-grade inertial sensors can be adequate source of data for the accident characterization and the estimation of vehicle trajectory near crash. The paper presents outcomes of an experiment carried out in accredited safety performance assessment facility in which full-size passenger car was crashed and the recordings of different types of motion sensors were compared to investigate practical level of accuracy of consumer grade sensors versus reference equipment and cameras. Inertial navigation system was developed by combining motion sensors of different dynamic ranges to acquire and process vehicle crash data. Vehicle position was reconstructed in three-dimensional space using strap- down inertial mechanization. Difference between the com- puted trajectory and the ground-truth position acquired by cameras was on decimeter level within short time window of 750 ms. Experiment findings suggest that inertial sen- sors of this grade, despite significant stochastic variations and imperfections, can be valuable for estimation of veloc- ity vector change, crash severity, direction of impact force, and for estimation of vehicle trajectory in crash proximity.

A quaternion-based attitude unscented Kalman filter is formulated with quaternion errors parameterized by small angle approximations and is applied to a filter with a state vector consisting of the attitude quaternion and the gyro bias vector. The filter is evaluated using extensive Monte Carlo data in a simulated lost-in-space scenario of a low-Earth orbiting spacecraft processing only three-axis magnetometer and gyro measurements. The filter is found to be robust, accurate, and rapidly convergent in this scenario for small true gyro biases and small initial uncertainties in their values, often converging in only one half of an orbit period to an attitude accuracy of 0.1 degrees. The filter convergence is found to depend significantly on the value of the true gyro biases as well as the initial gyro bias covariances. Monte Carlo results also indicate that this unscented Kalman filter is significantly less robust than an extended Kalman filter with the same attitude approach, but performs slightly better than another unscented Kalman filter with a generalized Rodrigues parameter approach to quaternion errors.

This editorial provides a concise introduction to the methods and applications of inertial sensors. We briefly describe the main characteristics of inertial sensors and highlight the broad range of applications as well as the methodological challenges. Finally, for the reader’s guidance, we give a succinct overview of the papers included in this special issue.

Fall Detection Systems (FDSs) based on wearable technologies have gained much research attention in recent years. Due to the networking and computing capabilities of smartphones, these widespread personal devices have been proposed to deploy cost-effective wearable systems intended for automatic fall detection. In spite of the fact that smartphones are natively provided with inertial sensors (accelerometers and gyroscopes), the effectiveness of a smartphone-based FDS can be improved if it also exploits the measurements collected by small low-power wireless sensors, which can be firmly attached to the user&rsquo, s body without causing discomfort. For these architectures with multiple sensing points, the smartphone transported by the user can act as the core of the FDS architecture by processing and analyzing the data measured by the external sensors and transmitting the corresponding alarm whenever a fall is detected. In this context, the wireless communications with the sensors and with the remote monitoring point may impact on the general performance of the smartphone and, in particular, on the battery lifetime. In contrast with most works in the literature (which disregard the real feasibility of implementing an FDS on a smartphone), this paper explores the actual potential of current commercial smartphones to put into operation an FDS that incorporates several external sensors. This study analyzes diverse operational aspects that may influence the consumption (as the use of a GPS sensor, the coexistence with other apps, the retransmission of the measurements to an external server, etc.) and identifies practical scenarios in which the deployment of a smartphone-based FDS is viable.

This paper aims to design and implement a system capable of distinguishing between different activities carried out during a tennis match. The goal is to achieve the correct classification of a set of tennis strokes. The system must exhibit robustness to the variability of the height, age or sex of any subject that performs the actions. A new database is developed to meet this objective. The system is based on two sensor nodes using Bluetooth Low Energy (BLE) wireless technology to communicate with a PC that acts as a central device to collect the information received by the sensors. The data provided by these sensors are processed to calculate their spectrograms. Through the application of innovative deep learning techniques with semi-supervised training, it is possible to carry out the extraction of characteristics and the classification of activities. Preliminary results obtained with a data set of eight players, four women and four men have shown that our approach is able to address the problem of the diversity of human constitutions, weight and sex of different players, providing accuracy greater than 96.5% to recognize the tennis strokes of a new player never seen before by the system.

Axisymmetric resonators possess multiple pairs of nominally degenerate modes, each of which can be configured as a Corilois vibratory gyro. In this paper we report a technique to extract simultaneous angular rate measurements from the same resonator. Specifically, both of the n = 2 and n = 3 pairs of modes in a disk resonator are configured to yield measurements of angular rate. Although the short-term noise is uncorrelated between these rate measurements, the long-term drifts show very strong correlation. A technique is implemented to fuse the two measurements into a single estimate of rate with much lower drift thereby providing a technique for in-situ bias drift compensation.

This paper proposes a deterministic estimator for the estimation of the attitude of a rigid body. A deterministic estimator uses a minimal set of information and does not try to minimize a cost function or fit the measurements into a stochastic process. The proposed estimator obtains the attitude estimation utilizing only the properties of the rotational group SO(3). The information set required by the proposed estimator is a single vector information and rate gyro readings. For systems in which one of the rotational freedom is constrained, the proposed estimator provides an accurate estimate of the reduced attitude. The performance of the algorithm is verified on different experimental testbeds. � 1996-2012 IEEE.

Статтю присвячено розробці методології оцінювання характеристик магнітного поля Землі для певного регіону.У якості вимірювального пристрою запропоновано використовувати групу датчиків розміщених усерединіпланшетного комп’ютера або мобільного телефону. У роботі було використано типові датчики, які вимірюють кути тангажу, крену, рискання (гіроскопи); компоненти векторів напруженості магнітного поля (отримуються від магнітометрів); широту, довготу, висоту над рівнем моря (від глобальної системи супутникового позиціонування). Наведено результати оцінювання компонентів вектора інтенсивності магнітного поля для певної території. Найважливішими характеристиками магнітного поля є горизонтальні й вертикальні компоненти вектора напруженості, а також кути магнітного нахилу та схилення. Отримані результати були порівнянні з прогнозом характеристик магнітного поля за моделлю магнітного поля.

Wearable sensors have been successfully used for a few decades in different sporting applications and its use has been constrained mostly to research projects. However, its positive impact has been recently adding other directions towards education, commercial and servicing. The establishment of Sports Engineering as a discipline is playing an important role in Australian universities where relevant material and emerging technologies are required to be taught and in certain circumstances developed. Some of these technologies include the adoption of inertial sensors (accelerometers and gyroscopes). This paper shares the impact of inertial sensors in building engagement in different educational activities at secondary level, with the purpose of engaging them into Sports Engineering disciplines, and at tertiary level through teaching undergraduate and post-graduate programs.

Conference name:Proceedings of SPIE,Fiber Optic Sensors and Applications XIV Date of Conference: 11–12 April 2017 Thermally induced bias error is one of the main performance limits for the fiber optic gyroscopes (FOGs). We reviewed the thermal sensitivity of FOG in detail and created a simulation environment by the Finite Element Method (FEM). Thermal sensitivity analysis is based on Shupe and elastooptic effects. Elastooptical interactions are modeled by using the two different FEM simulations and homogenization-dehomogenization processes. FEM simulations are validated by comparing the results with a laboratory FOG setup. We report the changes in the error characteristics for practical quadruple winding patterns. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.