Accelerometers Research Papers - Academia.edu (original) (raw)

Gait recognition is a technique that identifies or verifies people based upon their walking patterns. Smartwatches, which contain an accelerometer and gyroscope have recently been used to implement gait-based biometrics. However, this prior work relied upon data from single sessions for both training and testing, which is not realistic and can lead to overly optimistic performance results. This paper aims to remedy some of these problems by training and evaluating a smartwatch-based biometric system on data obtained from different days. Also, it proposes an advanced feature selection approach to identify optimal features for each user. Two experiments are presented under three different scenarios: Same-Day, Mixed-Day, and Cross-Day. Competitive results were achieved (best EERs of 0.13% and 3.12% by using the Same day data for accelerometer and gyroscope respectively and 0.69% and 7.97% for the same sensors under the Cross-Day evaluation. The results show that the technology is sufficiently capable and the signals captured sufficiently discriminative to be useful in performing gait recognition.

- by
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- Biometrics, Neural Networks, Forest biometrics, Biometrics And Identity

Industrialised nations have dedicated significant investments toward the development of civil infrastructure. To preserve this investment, attention must be given to proper maintenance. Structural Health Monitoring (SHM) has emerged as a tool to support this task. Networks of smart sensors, built upon wireless communication, have the potential to significantly improve SHM. Numerous platforms for smart sensors have been developed, most of which utilise proprietary hardware/software. The Berkeley Mote, utilised in this study, was the first open hardware/software platform to be developed. However, the Berkeley Mote was designed for generic applications and therefore the available sensors are not optimised for use in civil infrastructure applications. Acceleration and strain are among the most important physical quantities to judge the health of a structure. Although commercially available sensor boards have accelerometers, their applicability towards civil infrastructure is limited. This paper presents the development of new acceleration and strain sensor boards based on the Berkely-Mote platform and provides experimental verification of their performance within civil infrastructure applications.

Over the last years, there has been an increasing research interest in the application of accelerometry data for many kinds of automated gait analysis algorithms. The need for more security on mobile devices is increasing with new functionalities and features made available. To improve the device security we propose an improved biometric gait recognition approach with a stable cycle detection mechanism and comparison algorithm. Unlike previous work on wearable gait recognition, which was based from simple average cycling methods to more complicated methods, this paper reports new techniques for which can improve the performance, by using simple approaches. Preprocessing, cycle detection and recognition-analysis were applied to the acceleration signal. The performance of the system was evaluated having 60 volunteers and 12 sessions each volunteer and resulted in an equal error rate (EER) of 5.7%.

- by Patrick Bours and +1
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- Mobile Computing, Gait Analysis, Accelerometers, Mobile Device

Ambient Assisted Living (AAL) technology is often proposed as a way to tackle the increasing cost of healthcare caused by population aging. However, the sensing technology for continuous respiratory monitoring at home is lacking. Known approaches of respiratory monitoring are based on measuring either respiratory effect, e.g. tracheal sound recording by a bio-acoustic sensor, or respiratory effort, e.g. abdomen movement measurement by a tri-axial accelerometer. This paper proposes a home respiration monitoring system using a tri-axial accelerometer. Three different methods to extract a single respiratory signal from the tri-axial data are proposed and analyzed. The performance of the methods is evaluated for various possible respiration conditions, defined by the sensor orientation and respiration-induced abdomen movement. The method based on Principal Component Analysis (PCA) performs better than selecting the best axis. The analytical approach called Full Angle shows worse results...

- by Ronald Aarts
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- Algorithms, Principal Component Analysis, Population Aging, Performance Evaluation
- by Mario del Cueto and +1
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- Psychology, Physical Activity, Adolescent, Down Syndrome

Phase velocity of a surface acoustic wave (SAW) varies when the electric field associated with the wave interacts with a conductive material located above the propagation plane. In this paper, we propose a general method to approximate the scattering matrix when the conductive structure has a specific geometry. This structure has reflective properties of SAW. As an example, we considered a previously reported SAW-MEMS microaccelerometer which mainly consists of a slotted beam. By applying this method, we obtained the relationship between acceleration and the reflection and transmission coefficients. The dynamic of the slotted beam was studied using the finite element method (FEM). It was observed that relatively small variations in the size of the microstructure could cause significant changes in the reflection and transmission coefficients. We also show that the slotted beam acts as an acoustic wave bandpass filter, and its response is similar to that of reflective gratings, but with linear phase.

- by Jaime Octavio Guerra-Pulido
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- Engineering, Microstructure, Finite element method, Reflection

The objective of this paper is to compare the performance of a new proposed Measurement Assisted Partial Re-sampling (MAPR) filter against the performance of the Extended Kalman filter and the Mixture Monte Carlo Localizer within the context of a navigation algorithm for a dynamic 6 DoF system. In this paper, an autonomous underwater vehicle (AUV) is used as the dynamic system. The performances of the above three filters in resolving a navigation solution are assessed by giving the AUV a sequence of trajectories that highlight the sensitivities of the navigation algorithm to noise. This paper demonstrates that the MAPR filter is capable of computing an estimate that, like the EKF, takes into account the dynamics of the system, but like all particle filters is also capable of estimating non-Gaussian distributions.

- by Karl Sammut
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- Vehicle Dynamics, Monte Carlo Methods, Kalman Filter, Navigation

Automatic identification of human activity has led to a possibility of providing personalised services in different domains i.e. healthcare, security and sport etc. With advancement in sensor technology, automatic activity recognition can be done in an unobtrusive and non-intrusive way. The placement of the sensor and wearability are ones of vital keys in the successful activity recognition of free space livings. Experiments were carried out to investigate the use of a single wrist-worn accelerometer for automatic activity classification. The performances of two classification algorithms namely Decision Tree C4.5 and Artificial Neural Network were compared using four different sets of features to classify five daily living activities. The result revealed that Decision Tree C4.5 has outperformed Neural Network regardless of the different sets of features used. The best classification result was achieved using the set containing the most popular and accurate features i.e. mean, minimum, energy and sample differences etc. The best accuracy of 94.13% was achieved using only wrist-worn accelerometer showing a possibility of automatic activity classification with no movement constrain, discomfort and stigmatisation caused by the sensor.

- by Saisakul Chernbumroong
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- Neural Network, Activity Recognition, Decision Trees, Accelerometers

The proposed system in this paper develop two way control ESP8266 Node MCU based robotic vehicle. The system can be developed with the help of Node MCU Wi-Fi ESP5266 module, accelerometer sensor, DC gear motor and L293D motor driver circuit. The proposed system utilizes android application developed with the help of MIT app. Inventor software. The two control robotic vehicle can be utilized in various fields that eases the day to day activities.

- by IJRASET Publication
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- Accelerometers, Node-MCU

A quad-beam polymer optical accelerometer, based in the modulation of the total losses as a function of the acceleration, is presented in this letter. Three waveguides are defined on the structure: two at the edges and the third in the middle of a movable seismic mass suspended by polymer springs. A displacement of the mass, caused by acceleration, increases the losses due to the misalignment between the waveguides. Optical simulations predict an extremely high optical sensitivity of 11 dB/g. The novelty of the proposed device is the use of polymer as a mechanical/optical material. The sensitivity of the accelerometer has been measured to be at least 6 dB/g, much higher than any previously reported optical accelerometer based on the same operation principle. These results confirm the validity of the proposed high-sensitivity low-cost polymer accelerometer.

- by Andreu Llobera
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- Optical Waveguides, Accelerometers, Acceleration, Predictive models

Accelerometers are often used to measure the output of secondorder systems, such as structural vibrations. Conditions under which these systems are well-posed are obtained. We also establish conditions under which these systems have... more

- by Jeong-Whan Lee
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- Algorithms, Dentistry, Biomedical Engineering, Health Care

Currently there are many research focused on using smartphone as a data collection device. Many have shown its sensors ability to replace a lab test bed. These inertial sensors can be used to segment and classify driving events fairly accurately. In this research we explore the possibility of using the vehicle's inertial sensors from the CAN bus to build a profile of the driver to ultimately provide proper feedback to reduce the number of dangerous car maneuver. Braking and turning events are better at characterizing an individual compared to acceleration events. Histogramming the time-series values of the sensor data does not help performance. Furthermore, combining turning and braking events helps better differentiate between two similar drivers when using supervised learning techniques compared to seperate events alone, albeit with anemic performance.

- by Mohan Trivedi
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- Sensors, Accelerometers, Can Bus, Acceleration

Accurate knowledge on the absolute or true speed of a vehicle, if and when available, can be used to enhance advanced vehicle dynamics control systems such as anti-lock brake systems (ABS) and auto-traction systems (ATS) control schemes. Current conventional method uses wheel speed measurements to estimate the speed of the vehicle. As a result, indication of the vehicle speed becomes erroneous and, thus, unreliable when large slips occur between the wheels and terrain. This paper describes a fuzzy rule-based Kalman filtering technique which employs an additional accelerometer to complement the wheel-based speed sensor, and produce an accurate estimation of the true speed of a vehicle. We use the Kalman filters to deal with the noise and uncertainties in the speed and acceleration models, and fuzzy logic to tune the covariances and reset the initialization of the filter according to slip conditions detected and measurement-estimation condition. Experiments were conducted using an actual vehicle to verify the proposed strategy. Application of the fuzzy logic rule-based Kalman filter shows that accurate estimates of the absolute speed can be achieved euen under sagnapcant brakang skzd and traction slip conditions.

- by Ka C Cheok
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- Fuzzy Logic, Vehicle Dynamics, Control Systems, Control system
- by Keith Friedman
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- Head and Neck, Retention, Accelerometers, SAE

Falls are a major cause of hospitalization and injury-related deaths among the elderly population. The detrimental effects of falls, as well as the negative impact on health services costs, have led to a great interest on fall detection systems by the health-care industry. The most promising approaches are those based on a wearable device that monitors the movements of the patient, recognizes a fall and triggers an alarm. Unfortunately such techniques suffer from the problem of false alarms: some activities of daily living are erroneously reported as falls, thus reducing the confidence of the user. This paper presents a novel approach for improving the detection accuracy which is based on the idea of identifying specific movement patterns into the acceleration data. Using a single accelerometer, our system can recognize these patterns and use them to distinguish activities of daily living from real falls; thus the number of false alarms is reduced.

- by Janet Light
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- Geriatrics, Biomechanics, Health Care, Patient Monitoring

An ambulatory monitoring system is developed for the estimation of spatio-temporal gait parameters. The inertial measurement unit embedded in the system is composed of one biaxial accelerometer and one rate gyroscope, and it reconstructs the sagittal trajectory of a sensed point on the instep of the foot. A gait phase segmentation procedure is devised to determine temporal gait parameters, including stride time and relative stance; the procedure allows to define the time intervals needed for carrying an efficient implementation of the strapdown integration, which allows to estimate stride length, walking speed, and incline.

- by Filippo Cavallo
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- Algorithms, Biomedical Engineering, Parameter estimation, Gait

This paper presents design and navigation control of an advanced level comeback CanSat which is going to be launched to an altitude of about 400 m using an amateur rocket from ground level. The CanSat uses advanced and ultra-light microcontroller, pressure and temperature sensors, 3-axis accelerometer, 3-axis gyro, camera, GPS, IR distance measuring sensor, and RF communication module to communicate with the ground station PC. Three actuators are considered in this work for flight and ground segments control. They are the motor driven propeller, elevator and rudder. For the flight segment, parachute and attitude control are used to control the CanSat descent rate, attitude and heading. For the ground segment control; both the propeller and the rear landing gear of the CanSat is used for heading toward a predefined location on the ground. The rear landing gear is connected to the rudder rotational axis. An indigenous navigation control and electronic circuit design with the test results also are presented in this paper.

- by mansur çelebi and +1
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- Gears, Global Positioning System, Microcontrollers, GPS

This paper presents a new triaxial accelerometer calibration method using a mathematical model of six calibration parameters: three gain factors and three biases. The fundamental principle of the proposed calibration method is that the sum of the triaxial accelerometer outputs is equal to the gravity vector when the accelerometer is stationary. The proposed method requires the triaxial accelerometer to be placed in six different tilt angles to estimate the six calibration parameters. Since the mathematical model of the calibration parameters is nonlinear, an iterative method is used. The results are verified via simulations by comparing the estimated gain factors and biases with the true gain factors and biases. The simulation results confirm that the proposed method is applicable in extreme cases where the gain factor is 1000 V/(m/s 2 ) and the bias is ±100 V, as well as the cases where the gain factor is 0.001 V/(m/s 2 ) and the bias is 0 V. The proposed calibration method is also experimentally tested with two different triaxial accelerometers, and the results are validated using a mechanical inclinometer. The experimental results show that the proposed method can accurately estimate gain factors and biases even when the initial guesses are not close to the true values. In addition, the proposed method has a low computational cost because the calculation is simple, and the iterative method usually converges within three iteration steps. The error sources of the experiments are discussed in this paper.

The aim of this study is, in its first part, the description of the dynamic behavior of metal
plates, with the computation of natural frequencies and mode shapes; the problem has
been approached with different methods, each of them highlighting a particular
perspective.
The main points of part I are:
• The presentation of the theoretical background of the vibrating plate, to
understand the phenomenon, the main physical quantities involved, and the
mathematical equations ruling vibrations.
• An analytical computation, through equations previously demonstrated, of
natural frequencies and mode shapes for a set of different cases.
• A Finite Elements study, both for confirming the previous point, and to
provide results for cases that are too complex for the closed-form solution.
• The detailed description of the design, building and set up procedure of the
laboratory test rig to verify the model, and the discussion of the obtained
results.
• The definition of a didactic experience, to be conducted by students in the
DEXPILAB laboratories, with the relative operative procedure and safety
norms.
A practical application of this first study has been carried out in the second part of the
thesis, where it has been used to design, and build, the top soundboard of a string
instrument, a guitar, providing it with the desired acoustic properties.
In particular, this second part consists of:
• A description of the physics of the instrument, highlighting the link between the
way it is designed and built, and the dynamic properties that one should achieve.
• The modelling, through FEM, of the instrument soundboard to understand the
importance of the reinforcement ribs pattern in the dynamic behavior.
• The practical construction of a braced soundboard, tuned step by step with a
specific technique, and simultaneously analyzed with laboratory measurements.

- by Pedro Sanches
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- Design, Sensors and Sensing, Stress physiology, Stress

In recent days numerous individuals have experienced the ill effects Of medical issues like heart related, cardiovascular, malignancy and various illnesses. Epilepsy is like a complex network disease, those who have seizures, which are controlled, and those who struggle on a daily basis. Many epilepsy patients cannot call for help during a seizure, because of the unconscious so it can lead to injuries, medical Complications and loses memory during the seizure attack. The seizures happen because of electrical activity in the brain, causing a sudden change in behavior at times seizures appear to be unique and on what part of the cerebrum they influence. This paper proposes a methodology for epilepsy individual which uses sensor to evaluate the parameters of the patients like temperature, fall of the patient, shaken of the hand and sound of the patient. The patient's status can be seen on PC through IOT so that the specialist/attendants can occasionally screen the patient's epilepsy.

With the increase of vehicles and cars of different kind and the large movement that occurs every day on the roads it was natural to observe an increase in traffic accidents, but the real dilemma lies in how to make the rescue process efficient. The problem that we want to solve is the response of ambulances towards accidents and the lengthy registration process of patients in hospitals. In the above two scenarios, the manual process of calling the ambulance leads to delay in rescue of patients from an accident and the delay in registration of patient leads to delay in medication or treatment of the patient. We want to make the process more efficient by automating accident detection for increasing the efficiency of the ambulance rescue process and by sending the details of the patient before the patient reaches the hospitals for faster treatment of patients. Along with this, alert messages will be sent to the family or friends of the patients to notify them as soon as an accident is detected.

Orientation estimation is very important for development of unmanned aerial systems (UAS). Kalman filters are widely used; however they assume linearity and Gaussian statistics. While these assumptions work well for high-quality, high-cost sensors, they do not work as well for low-cost, lowquality sensors. In these cases, complementary filters are used since no assumptions are made with regards to linearity and statistics. This paper gives a review of the different types of complementary filters being developed. Basic examples are shown with details about how they are derived and simulations that show how they work. Guidelines are then given about when complementary filters are best used for UAS navigation.

- by Calvin Coopmans
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- Gaussian processes, Frequency-domain analysis, Reliability, Accelerometers

Knowledge of velocity is crucial to certain industrial applications involving high-bandwidth modeling and control. In conventional approaches, the velocities obtained from encoders or tachometers are quite noisy, and low-pass filters are usually engaged to generate usable velocity signals. The low-pass filter, however, causes significant phase lag that can severely affect both modeling and control accuracy in the mid-and high-frequency ranges. In this paper, two approaches using a combination of an encoder and an imperfect accelerometer are proposed to estimate velocities with high bandwidth. The two approaches, namely the two-channel approach and the observer-based approach, estimate velocities by applying proper frequency weightings to the encoder and accelerometer signals. The encoder mainly contributes to the low-frequency components of velocity estimation, and the accelerometer mainly contributes to the high-frequency components of velocity estimation. An adaptive mechanism for estimating the accelerometer gain is also presented. The effectiveness of the two velocity estimation approaches is verified experimentally with respect to a one-degree-of-freedom robot performing both rigid contact modeling and control. Extension to 3-D applications is discussed.

- by Wen-Hong Zhu
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- Engineering, Motion control, Low Frequency, Parameter estimation

Instantaneous horizontal velocity is the most important factor influencing on sprint performance in track and field. It can be either determined directly by radar or derived as a product of step length and step frequency. The second approach also helps to enhance the biomechanics of sprinting. This paper presents a low-cost wireless framework containing an inertial measurement unit. The developed system derives information about step parameters from an accelerometer and a gyroscope measurement results and fulfills a real-time analysis of sprinter's activity. The on-body unit is mounted on the low back and doesn't impact on the running style, in contrast to foot-mounted sensors. The developed system doesn't require a time-consuming installation and can be applied during daily workouts.

- by Alexander Kuznietsov
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- Biomechanics, Wireless Sensor Networks, Sensors, Telemetry

Human localization is a very valuable information for smart environments. State-of-the-art Local Positioning Systems (LPS) require a complex sensor-network infrastructure to locate with enough accuracy and coverage. Alternatively, Inertial Measuring Units (IMU) can be used to estimate the movement of a person, by detecting steps, estimating stride lengths and the directions of motion; a methodology that is called Pedestrian Dead-Reckoning (PDR). In this paper, we use low-performance Micro-Electro-Mechanical (MEMS) inertial sensors attached to the foot of a person. This sensor has triaxial orthogonal accelerometers, gyroscopes and magnetometers. We describe, implement and compare several of the most relevant algorithms for step detection, stride length, heading and position estimation. The challenge using MEMS is to provide location estimations with enough accuracy and a limited drift. Several tests were conducted outdoors and indoors, and we found that the stride length estimation errors were about 1%. The positioning errors were almost always below 5% of the total travelled distance. The main source of positioning errors are the absolute orientation estimation. 1

- by Jorge Guevara
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- Signal Processing, Wireless Sensor Networks, Inertial navigation, Accelerometers

The Kalman Filter is very useful in prediction and estimation. In this paper, the Kalman Filter is implemented for Inertial Measurement Unit (IMU) on the ATMega8535. The sensors used in this system are accelerometer MMA7260QT and gyroscope GS-12. The system chooses the arbitrary sampling time and then it is evaluated for possible using smaller value. As the Kalman Filter operation needs matrix calculation, the formula is converted into several ordinary equations. The parameter being investigated in this paper is measurement covariance matrix. This parameter influences the way the Kalman Filter responses to noise. Bigger value makes the Kalman Filter less sensitive to noise and the estimation is too smooth, thus it does not give real angle estimation. Using smaller value makes the Kalman Filter more sensitive to noise. This makes the estimated angle still suffers from noise and it is likely that the Kalman Filter is useless. This paper recommends 0.0001 to 0.001 for the measurement covariance noise parameter. This paper also recommended a pipeline configuration if the control algorithm needs more space in a sampling time.

- by Hany Ferdinando
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- Microcontrollers, Kalman Filter, Sensors, Noise

In this paper, we present a novel procedure for the on-the-field autocalibration of triaxial micro accelerometers, which requires neither any equipment nor a controlled environment and allows increasing the accuracy of this kind of microsensor. The procedure exploits the fact that, in static conditions, the modulus of the accelerometer output vector matches that of the gravity acceleration. The calibration model incorporates the bias and scale factor for each axis and the cross-axis symmetrical factors. The parameters are computed through nonlinear optimization, which is solved in a very short time. The calibration procedure was quantitatively tested by comparing the orientation produced by MEMS with that measured by a motion capture system. Results show that the MEMS output, after the calibration procedure, is far more accurate with respect to the output obtained using factory calibration data and almost one order of magnitude more accurate with respect to using traditional calibration models. in 2000. He is currently an Associate Professor with the Department of Computer Science, University of Milano, where he teaches courses on intelligent systems and robotics and is the Director of the Applied Intelligent Systems Laboratory. He has coauthored more than 40 peer-reviewed journal papers and is the holder of several patents. His research interests include quantitative human motion analysis and modeling, statistical learning from data, and applications to vision, graphics, and medical imaging.

- by iuri frosio
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- Microsystems, Calibration, Accelerometers, Motion Capture

The lack of widespread adoption of condition monitoring systems (CMS) in wind turbines is due, in part, to the high total cost of ownership. After the initial purchase, there is installation, Information Technology (servers/database/software support) and knowledge creation cost. Knowledge creation refers to the ability of the CMS to provide the operator with actionable information. Presented is a CMS architecture which reduces the total cost of ownership by reducing hardware cost (MEMS based sensor and local processing), reducing IT cost by deploying to a compute cloud, and reducing the cost of knowledge creation by incorporating advanced digital signal processing and decision support algorithms into the CMS application.

- by Eric Bechhoefer
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- Computer Architecture, Information Technology, Signal Processing, Vibrations

This paper presents a study of tool life, surface finish and vibration while machining nodular cast iron using ceramic tool. A series of cutting tests have been carried out to verify the change in surface finish of the workpiece due to increasing tool wear. The tests have been done under various combinations of speed, feed and depth of cut. The effects of vibration on the flank wear both in the direction of main cutting force and radial cutting force have been investigated. The vibration was measured using two accelerometers attached to the tool holder and the parameters used to make the correlation with surface roughness were the amplitude and acceleration of the signals.

- by Husni Husni
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- Materials Engineering, Mechanical Engineering, Wearable Computing, Vibrations

This paper presents an extended Kalman filter for real-time estimation of rigid body orientation using the newly developed MARG (Magnetic, Angular Rate, and Gravity) sensors. Each MARG sensor contains a three-axis magnetometer, a three-axis angular rate sensor, and a three-axis accelerometer. The filter represents rotations using quaternions rather than Euler angles, which eliminates the long-standing problem of singularities associated with attitude estimation. A process model for rigid body angular motions and angular rate measurements is defined. The process model converts angular rates into quaternion rates, which are integrated to obtain quaternions. The Gauss-Newton iteration algorithm is utilized to find the best quaternion that relates the measured accelerations and earth magnetic field in the body coordinate frame to calculated values in the earth coordinate frame. The best quaternion is used as part of the measurements for the Kalman filter. As a result of this approach, the measurement equations of the Kalman filter become linear, and the computational requirements are significantly reduced, making it possible to estimate orientation in real time. Extensive testing of the filter with synthetic data and actual sensor data proved it to be satisfactory. Test cases included the presence of large initial errors as well as high noise levels. In all cases the filter was able to converge and accurately track rotational motions.

- by João Luís Marins
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- Earth, Convergence, Nonlinear filters, Magnetic field

The importance of the road infrastructure for the society could be compared with importance of blood vessels for humans. To ensure road surface quality it should be monitored continuously and repaired as necessary. The optimal distribution of resources for road repairs is possible providing the availability of comprehensive and objective real time data about the state of the roads. Participatory sensing is a promising approach for such data collection.

- by Leo Selavo
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- Algorithms, Mobile Computing, Sensors, Data acquisition

Due to the need for accurate navigation in minimally invasive surgery, many methods have been introduced to the operating room for attitude (orientation) tracking, position tracking or both. Integrated inertial and magnetic sensing is one promising method for attitude estimation. The estimated attitude can further be used for position tracking by incorporating other aided reference positioning systems. When an integrated inertial and magnetic sensor is used for tracking attitude, it usually has the assumptions that the sensor is quasi-static and the surrounding magnetic field is steady. For practical hand-held surgical instruments, perturbations exist due to intended and unintended (e.g., tremor) motion and due to distortion of the surrounding magnetic field. We consider the problem of estimating the gravity and magnetic field in the inertial-sensor frame with small perturbations. The dynamics of the gravity and magnetic field is studied under perturbations, their relationships to gyroscope measurements are analyzed, and Kalman filters are formulated to reduce these perturbations. The estimated gravity and magnetic values (outputs of the Kalman filters) are subsequently used in an extended Kalman filter for attitude estimation. In this filter, the prediction model is given by the system dynamics, formulated using quaternions, and the observation model is given by vector analysis of the estimated gravity and magnetic field. Experiments are performed to validate the algorithms under clinically realistic motions. The complete system demonstrates an improvement in the accuracy of the attitude estimate in the presence of small perturbations, and satisfies the specified accuracy requirement of one degree.

- by Hongliang Ren
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- Mechanical Engineering, Surgery, Inertial navigation, System Dynamics

A sigma-point Kalman filter is derived for integrating GPS measurements with inertial measurements from gyros and accelerometers to determine both the position and the attitude of a moving vehicle. Sigma-point filters use a carefully selected set of sample points to more accurately map the probability distribution than the linearization of the standard extended Kalman filter, leading to faster convergence from inaccurate initial conditions in position/attitude estimation problems. The filter formulation is based on standard inertial navigation equations. The global attitude parameterization is given by a quaternion, while a generalized three-dimensional attitude representation is used to define the local attitude error. A multiplicative quaternion-error approach is used to guarantees that quaternion normalization is maintained in the filter. Simulation results are shown to compare the performance of the sigma-point filter with a standard extended Kalman filter approach.

- by John Crassidis
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- Aerospace Engineering, Inertial navigation, Convergence, Global Positioning System

Currently the fracture or limb lengthening of any long bone is monitored using pain measures, radiographs and limb weight bearing. All these qualitative measures are inaccurate; radiographs provide little information of the fracture site due to un-calcified callus tissue. Excessive fracture movement (1 mm+ [1]) can lead to delayed healing (up to 7 weeks longer [2]) and mal-alignment (up to 19% of cases, [3]). However, if removed too early, there is a real risk of re-fracture due to insufficient callus stiffness (up to 8 % of cases, [4]). Furthermore, there has been some speculation as to whether mal-aligned tibia can lead to the development of osteoarthritis due to load changes in the knee. Ideally, identifying excessive movement of the fracture early can allow the fracture to be easily manipulated by adjusting the fixator.
An accurate method of quantitatively measuring fracture movement in vivo is needed to address this problem. The aim of this study is to investigate whether MEMS accelerometers can be used to accurately monitor movement directly in an externally fixed tibia fracture in vitro.

- by David Cheneler
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- MEMS, Accelerometers, Bone fracture

Falling is one of the leading causes of serious health decline or injury-related deaths in the elderly. For survivors of a fall, the resulting health expenses can be a devastating burden, largely because of the long recovery time and potential comorbidities that ensue. The detection of a fall is, therefore, important in care of the elderly for decreasing the reaction time by the care-givers especially for those in care who are particularly frail or living alone. Recent advances in motion-sensor technology have enabled wearable sensors to be used efficiently for pervasive care of the elderly. In addition to fall detection, it is also important to determine the direction of a fall, which could help in the location of joint weakness or post-fall fracture. This work uses a waist-worn sensor, encompassing a 3D accelerometer and a barometric pressure sensor, for reliable fall detection and the determination of the direction of a fall. Also assessed is an efficient analysis framework suitable for on-node implementation using a lowpower micro-controller that involves both feature extraction and fall detection. A detailed laboratory analysis is presented validating the practical application of the system.

- by Louis Atallah
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- Movement, Reaction Time, Accelerometers, Feature Extraction

This paper is mainly focused on piezoresistive 1 accelerometer performance improvement. Thus a new model 2 of this sensor is derived to enhance its various parameters, 3 such as precision, sensitivity, and reliability. Moreover, applying 4 this model, a new design of piezoresistive accelerometer can 5 be achieved. The developed model is validated by simulations 6 and confirmed by experimental tests to verify its effectiveness in 7 industrial applications. The comparison study showed that the 8 best choice of damping rate to reduce the measurement error 9 and increase the precision corresponds to the rate chosen in this 10 paper. The results have also demonstrated that a more reliable 11 sensor can be designed compared with the existing designs. 12

- by Saad Salah
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- Accelerometers

The need exists for high-sensitivity, low-noise vibration sensors for various applications, such as geophysical data collection, tracking vehicles, intrusion detectors, and underwater pressure gradient detection. In general, these sensors differ from classical accelerometers in that they require no direct current response, but must have a very low noise floor over a required bandwidth. Theory indicates a capacitive micromachined silicon vibration sensor can have a noise floor on the order of 100 ng/ p Hz over 1-kHz bandwidth, while reducing size and weight tenfold compared to existing magnetic geophones. With early prototypes, we have demonstrated Brownian-limited noise floor at 1.0 g/ p Hz; orders of magnitude more sensitive than surface micromachined devices such as the industry standard ADXL05.

- by Jonathan Bernstein
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- Microelectromechanical systems, Micromachining, Noise, Si

This paper describes a complementary Kalman filter design to estimate orientation of human body segments by fusing gyroscope, accelerometer, and magnetometer signals from miniature sensors. Ferromagnetic materials or other magnetic fields near the sensor module disturb the local earth magnetic field and, therefore, the orientation estimation, which impedes many (ambulatory) applications. In the filter, the gyroscope bias error, orientation error, and magnetic disturbance error are estimated. The filter was tested under quasi-static and dynamic conditions with ferromagnetic materials close to the sensor module. The quasi-static experiments implied static positions and rotations around the three axes. In the dynamic experiments, three-dimensional rotations were performed near a metal tool case. The orientation estimated by the filter was compared with the orientation obtained with an optical reference system Vicon. Results show accurate and drift-free orientation estimates. The compensation results in a significant difference (p 0 01) between the orientation estimates with compensation of magnetic disturbances in comparison to no compensation or only gyroscopes. The average static error was 1.4 (standard deviation 0.4) in the magnetically disturbed experiments. The dynamic error was 2.6 root means square.

- by Chris T M Baten
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- Algorithms, Biomedical Engineering, Biomechanics, Biomagnetism

An attitude determination algorithm suitable for micro aerial vehicle (MAV) applications is developed. The algorithm uses Earth's magnetic and gravity field vectors as observations. The magnetic field vector measurements are obtained from a magnetometer triad. The gravity field vector is measured by fusing information from an accelerometer triad with GPS/WAAS (wide area augmentation system) velocity measurements. Two linearization and estimator designs for implementing the algorithm are discussed. Simulation and experimental flight test results validating the algorithm are presented.

- by D. Gebre-Egziabher
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- Aerospace Engineering, Earth, Global Positioning System, Magnetic field

In this paper we consider the design and the experimental validation of an attitude and heading reference system for a miniature aerial robot prototype based on measurements obtained from a low cost off-the-shelf inertial measurement unit. Different estimation algorithms to process the raw inertial data are implemented and validated in real indoor flight tests by employing, as a reference, the accurate attitude estimation obtained from a vision based motion tracking system. The proposed experiments allow to accurately evaluate the performance of the different estimation algorithms and the effects of disturbances, such as vehicle accelerations, vibrations and non ideal magnetic fields, in a typical scenario of application for the considered unmanned vehicle prototype.

- by Elisabetta Farella
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- Calibration, Accelerometers, Estimation, Attitude Control

Long term continuous monitoring of electrocardiogram (ECG) in a free living environment provides valuable information for prevention on the heart attack and other high risk diseases. This paper presents the design of a real-time wearable ECG monitoring system with associated cardiac arrhythmia classification algorithms. One of the striking advantages is that ECG analog front-end and on-node digital processing are designed to remove most of the noise and bias. In addition, the wearable sensor node is able to monitor the patient's ECG and motion signal in an unobstructive way. To realize the real-time medical analysis, the ECG is digitalized and transmitted to a smart phone via Bluetooth. On the smart phone, the ECG waveform is visualized and a novel layered hidden Markov model is seamlessly integrated to classify multiple cardiac arrhythmias in real time. Experimental results demonstrate that the clean and reliable ECG waveform can be captured in multiple stressed conditions and the real-time classification on cardiac arrhythmia is competent to other workbenches.

- by Zhenzhou Shao
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- Algorithms, Analytical Chemistry, Cardiovascular disease, Electrocardiography

Artifact removal from physiological signals is an essential component of the biosignal processing pipeline. The need for powerful and robust methods for this process has become particularly acute as healthcare technology deployment undergoes transition from the current hospital-centric setting toward a wearable and ubiquitous monitoring environment. Currently, determining the relative efficacy and performance of the multiple artifact removal techniques available on real world data can be problematic, due to incomplete information on the uncorrupted desired signal. The majority of techniques are presently evaluated using simulated data, and therefore, the quality of the conclusions is contingent on the fidelity of the model used. Consequently, in the biomedical signal processing community, there is considerable focus on the generation and validation of appropriate signal models for use in artifact suppression. Most approaches rely on mathematical models which capture suitable approximations to the signal dynamics or underlying physiology and, therefore, introduce some uncertainty to subsequent predictions of algorithm performance. This paper describes a more empirical approach to the modeling of the desired signal that we demonstrate for functional brain monitoring tasks which allows for the procurement of a "ground truth" signal which is highly correlated to a true desired signal that has been contaminated with artifacts. The availability of this "ground truth," together with the corrupted signal, can then aid in determining the efficacy of selected artifact removal techniques. A number of commonly implemented artifact removal techniques were evaluated using the described methodology to validate the proposed novel test platform.

- by Kevin Sweeney
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- Engineering, Electronic Engineering, Algorithms, Signal Processing

Understanding the mobility of people with physical disabilities is important for rehabilitation decision making. This paper presents a smartphone-based approach to mobility monitoring. The BlackBerry-based system is clipped to the person's belt. This approach uses an accelerometer signal to identify changes-of-state caused by starting/stopping and postural change. Our finding suggests that a smartphone integrated with an accelerometer could detect changes from static or dynamic movement (i.e., starting to walk, standing still, slowing down), which compares favorably with previous studies using body-fixed accelerometers. This approach is part of the larger framework of Wearable Mobility Monitoring Systems (WMMS).

- by Natalie Baddour and +1
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- Decision Making, Biomechanics, Accelerometers, Physical disability

This paper describes gait recognition using a body often used. Therefore, there is still a space for improvement worn sensor. An accelerometer sensor (placed in the trousers in mobile user authentication. pocket) is used for collecting gait features. From the acceleration Gait (walking manner of a person) as a biometric has gained signal of the person, cycles have been detected and analysed for

- by Patrick Bours
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- Biosensors, Biometrics, Machine Vision, Authentication

Abstract This thesis investigates, how placement variations of electronic devices influence the possibility of using sensors integrated in those devices for context recognition. The vast majority of context recognition research assumes well defined, fixed sensor locations. Although this might be acceptable for some application domains (eg in an industrial setting), users, in general, will have a hard time coping with these limitations.

- by Kai Kunze
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- Ubiquitous Computing, MEMS sensor, Activity Recognition, Accelerometers

A method was developed for rotating a Smartphone accelerometer coordinate system from an offset to a predetermined three-dimensional position to improve accelerometer-based activity identification. A quaternion-based rotation matrix was constructed from an axis-angle pair, produced via algebraic manipulations of the gravity acceleration components in the device's body-fixed frame of reference with the desired position of the vector. The rotation matrix is constructed during quiet standing and then applied to all subsequent accelerometer readings thereafter, transforming their values in this new fixed frame. This method provides a consistent accelerometer orientation between people, thereby reducing Smartphone orientation variability that can adversely affect activity classification algorithms.

- by Mario Tundo
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- Engineering, Computer Science, Quaternion, Gravity