Researchers have successfully increased physical activity with self-monitoring, goal setting, and feedback. Goal attainment is a crucial part of what makes goal setting successful; however, it is often unreported in the literature or implied that goals were not reached consistently. A potential way to achieve this consistency is to create an action plan, or a detailed account of exactly how and when the individual will engage in the desired physical activity to reach his or her goal. This study evaluated whether making a detailed action plan would allow individuals to reach their physical activity goals more consistently than when using goal setting and self-monitoring alone. Action planning increased goal attainment for all participants but only resulted in increased physical activity for 2 of 3 participants. Future research should replicate this study to validate these findings and further explore methods for improving the success of goal setting as an intervention.

This thesis addresses the hypothesis that a single, waist-mounted triaxial accelerometer (TA) can be used to monitor human movement patterns in unsupervised, freeliving subjects over extended periods, and that it can be used to quantitatively measure parameters that can provide clinical insight into the health status of the subject. A rigorous theoretical and experimental understanding of the signals obtained from a TA is developed. The effect of the placement of the TA device on the waist is explored and a model relating device position to TA signal is developed for a range of postures and activities. A classification framework for movement identification using the signals from a waist-mounted TA is presented. This framework is based on a hierarchical binary processing tree and is designed for real time use. An implementation of this framework for monitoring housebound patients is presented. Algorithms for detecting falls, distinguishing between activity and rest, classifiying transitions between different postural orientations, and for identifying periods of standing, sitting, lying and walking are developed. In evaluation studies performed in controlled laboratory conditions, every algorithm performed with better than 90% accuracy. Once movements are identified, movement-specific parameters sensitive to changes in functional status are extracted from the signal. A two stage methodology for employing the accelerometry system in monitoring free-living subjects is introduced. The first stage involved monitoring specific movements through a directed routine. The second stage involved monitoring of free movement. Signals obtained from the directed routine are used to extract clinically relevant, movement-specific parameters. Signals obtained from the period of free movement are monitored for falls and other abnormal events. General parameters of movement, including energy expenditure, are also measured. The system was evaluated in a series of field studies in laboratory and home environments, in supervised and unsupervised settings, using cohorts of healthy subjects. A pilot trial was conducted in which six healthy elderly subjects wore the TA device for a period of up to three months. The technical performance and useability of the system were evaluated. Clinically significant parameters were measured and the effects of age and health status on the measured parameters were evaluated.

As a promising alternative to laboratory constrained video capture systems in studies of human movement, inertial sensors (accelerometers and gyroscopes) are recently gaining popularity. Secondary quantities such as velocity, displacement and joint angles can be calculated through integration of acceleration and angular velocities. However, it is broadly accepted that this procedure is significantly influenced by cumulative errors due to integration, arising from sensor noise, non-linearities, asymmetries, sensitivity variations and bias drifts. In this study, new methods for improving foot motion from inertial sensors are explored and assessed. / Sensor devices have been developed previously, for example, to detect postural changes that determine potential elderly fallers, and monitor a person’s gait. Recently, a gait variable known as minimum toe clearance (MTC) has been proposed to describe age-related declines in gait with better success as a predictor of falls risk. The MTC is the minimum vertical distance between the lowest point on the shoe and the ground during the mid-swing phase of the gait cycle. It is therefore of our interest to design a cost effective but accurate solution to measure toe clearance data which can then be used to identify the individuals at risk of falling. In this study, hardware, firmware and software features from off-the-shelf inertial sensors and wireless motes are evaluated and their configuration optimized for this application. A strap-down method, which consists of the minimizing of the integration drift due to cumulative errors, is evaluated off-line. Analysis revealed the necessity of band-pass filtering methods to correct systematic sensor errors that dramatically reduce the accuracy in estimating foot motion. / Cumulative errors were studied in the frequency domain, employing content of inertial sensor foot motion evaluated against a ’gold standard’ video-based device, namely the Optotrak Certus NDI. In addition, the effectiveness of applying band-pass filtering to raw inertial sensor data is assessed, under the assumption that sensor drift errors occur in the low frequency spectrum. The normalized correlation coefficient ρ of the Fast Fourier Transform (FFT) spectra corresponding to vertical toe acceleration from inertial sensors and from a video capture system as a function of digital band-pass filter parameters is compared. The Root Mean Square Error (RMSE) of the vertical toe displacement is calculated for 5 healthy subjects over a range of 4 walking speeds. The lowest RMSE and highest cross correlation achieved for the slowest walking speed of 2.5km/h was 3.06cmand 0.871 respectively, and 2.96cm and 0.952 for the fastest speed of 5.5km/h.

<p>In this master thesis, control algoritms using arm side sensors are investigated for an industrial robot. The sensors can be position encoders placed after the gearbox and accelerometers on the robot arms. Control strategies are discussed and evaluated for different models of the robot, after which chosen strategies are applied to a realistic model. </p><p>Control algoritms using arm side sensors (LQ, dual-loop and PD-PID) are compared to a PID-controller that only uses measurements of motor position for feedback control. The comparison are done with respect to disturbance rejection, oscillation damping, robustness and tracking performance of a reference trajectory. </p><p>Results from tests with the realistic robot modell shows that disturbance rejection was improved a factor 2 to 5 while tracking performance was improved a factor 4 to 5 according to maximum deviation from the reference path. At the same time good re-sults are achieved regarding oscillation damping and robustness.</p>

<p>This thesis approaches the problem of estimating the arm angles of an industrial robot with flexibilities in joints and links. Due to cost-cutting efforts in the industrial robots industry, weaker components and more cost-effective structures have been introduced which in turn has led to problems with flexibilities, nonlinearities and friction. In order to handle these challenging dynamic problems and achieve high accuracy this study introduces state observers to estimate the tool position.The observers use measurements of the motor angles and an accelerometer and the different evaluated observers are based on an Extended Kalman Filter and a deterministic variant. They have been evaluated in experiments on an industrial robot with two degrees of freedom. The experimental verification shows that the state estimates can be highly accurate for medium frequency motions, ranging from 3-30Hz. For this interval the estimate were also robust to model inaccuracies.The estimation of low-frequency motions was relatively poor, due to problemswith drift for the accelerometer, and it also showed a significant dependence on the accuracy of the model. For industrial robots it is mainly the medium frequency motions which are hard to estimate with existing techniques and these observers therefore carries great potential for increased precision.</p>

<p>Volvo Powertrain i Köping tillverkar växellådor till tunga fordon, som lastbilar och bussar. Varje tillverkad växellåda provkörs innan den levereras till kund, det vill säga till något av de bolag inom koncernen som slutmonterar växellådan i fordonet.</p><p>Provkörningen innehåller ett antal olika automatiserade funktionstester, exempelvis test av oljetryck och test av mjukvaran i växellådans styrbox. Förutom dessa genomförs även ett manuellt kvalitetstest. Den person som provkör växellådan försöker höra eventuella missljud. Ett typiskt fel som upptäcks på detta sätt är ojämnheter på kugghjulen, exempelvis att en av kuggarna har blivit skadad under tillverkningen. En nackdel med att manuellt lyssna efter fel är att nivån för vad som är acceptabelt blir subjektiv. Det är dessutom svårt att på detta sätt avgöra exakt var i växellådan felet sitter, vilket kan leda till att fel komponent byts ut och kasseras vid justering. Efter varje justering krävs en ny provkörning och växellådan kan inte godkännas förrän rätt komponenten är utbytt.</p><p>Målet med examensarbetet har varit att utveckla ett system som kan detektera fel automatiskt genom att mäta ljud och vibrationer i växellådan. Det är också önskvärt att direkt kunna isolera felkällan till en specifik del av växellådan. Genom att veta på vilket kugghjul felet sitter underlättas justeringen av växellådan, vilket både sparar tid och minskar kassationskostnader.</p><p>Arbetet har delats in tre huvuddelar: analys, utveckling av mjukvara och utveckling av mätsystem. Första delen var en matematisk analys av hur bidraget från olika rörliga delar i växellådan kan isoleras ur ljud- och vibrationssignaler. För att åstadkomma detta beräknas ett antal tidsmedelvärden på sensorsignalen.</p><p>Andra delen innebar att utveckla den programvara som sköter felanalysen och validera den. Den tredje delen var att bygga och testa själva mätsystemet och ta fram programvara som styr mätningen och kommunicera med växellådans datorsystem. Feldetekteringssystemet behöver vara snabbt och kunna diagnostisera fel från korta mätserier. Det innebär en extra utmaning eftersom långa mätserier är att föredra speciellt om felen som ska detekteras är små.</p><p>Resultaten från försöken är lovande och möjligheterna för att utveckla ett komplett system är goda. I undersökningen har felaktiga lådor detekterats och en god felisolering har uppnåtts. I det nuvarande utvecklingsfasen detekterar och isolerar diagnosprogrammet kuggfel på alla axlar.</p><p>Ytterligare provkörning av växellådor med samma typ av fel behövs dock för att verifiera metoden. Analysprogrammet bör också byggas ut till att omfatta fler typer av fel än de som hittills varit möjligt att arbeta med. Även lagerfel kan detekteras med den utvecklade metoden men det har inte kunnat utvärderas på grund av bristande data.</p><p>Vi rekommenderar att företaget färdigställer testsystemet då utsikterna för att kunna införa ett automatiskt, kostnadseffektivt och väl fungerande kvalitetskontrollsystem är mycket goda.</p> / <p>Volvo Powertrain in Köping, Sweden produces gearboxes for heavy vehicles such as trucks and busses. Each produced gearbox is tested before delivery. The test run includes a variety of automated function tests, i.e. test of oil pressure. Besides the automated tests a manual quality test is performed. The test person is listening, in order to detect jarring sounds. A typical fault that is detected in this test is gear defects. A disadvantage with manual defect detection is that the acceptance level is subjective. It is also hard to determine which gear that is damaged, sometimes resulting in the wrong gear being replaced and rejected. After a disassembly the gearbox needs to be tested and it can not pass until the damaged gear is replaced.</p><p>The goal of this thesis work has been to develop a system that can detect defects automatic through sound and vibration measurements of the gearbox. It is also desirable to be able to isolate the source of a defect to a specific gear. With the knowledge of which gear is defective, the reparation of the gearbox is facilitated. This would save time and reduce the defective work expense.</p><p>The work has been divided into three main parts: analysis, software development and development of measurement system. The first part was a mathematical analysis of how to isolate the contribution from each moving part from the sound or vibration signal respectively. In order to achieve this, a number of time averages is calculated from the sensor signals.</p><p>The second part was to develop the software that handles the signal processing and diagnosis. The third part was to build and test the measurement system and develop programs which control the measurements and communicate with the gearbox control system. The defect detection system needs to be fast and able to diagnose defects on short series of measurement. The results from the experiments are promising and the potential to develop a complete system is good. The current defect detection system detects and isolates gear defects on all shafts in the gearbox. Additional test runs of gearboxes with similar defects are needed in order to validate the method. Defective bearings are also detectable with the method presented, but this has not been evaluated since appropriate data has been unavailable.</p>

<p>Denna rapport behandlar utveckling av en tvåhjulig balanserande robot. En PID-regulator är implementerad i en mikrokontroller, som även AD-omvandlar en sensorsignal, samt styr motorer via H-bryggor med pulsbreddsmodulering. I rapporten förklaras framtagning av diskret PID-regulator, processorkort, motorkort, val av komponenter och sensor för att mäta robotens vinkel mot ett vertikalplan.</p><p>Roboten kan balansera stillastående, men behöver kompletteras ytterligare med hjulåterkoppling för att kunna balansera medan den kör. Roboten balanserar med mätdata från en mekanisk golvavkännare (potentiometer). Andra sorters sensorer diskuteras också, t ex accelerometer, gyro och optisk sensor.</p> / <p>This report explain the development of a two wheel balancing robot. A PID-regulator is implemented in a microcontroller, which also AD-converts a sensor signal, and generate pulse width modulated signals to drive H-bridges. It is discussed how to develop a discretisized PID regulator, microcontroller and H-bridge circuit boards, as well as how to chose components and suitable sensors for measuring the robots angle against a vertical plane.</p><p>The robot is able to balance on its own when standing still, but it need to have feedback from its wheel position if it should be able to maintain balancing when moving. The robot use a mechanical floor feeler (potentiometer). Other sensors are also discussed, e g accelerometer, rate gyro and optical sensor.</p>

<p>This master thesis is a study on how a rategyro triad, an accelerometer triad, and a magnetometer triad can be integrated into a navigation system, estimating a vehicle’s attitude, i.e. its roll, tipp, and heading angles. When only a rategyro triad is used to estimate a vehicle’s attitude, a drift in the attitude occurs due to sensor errors. </p><p>When an accelerometer triad and a magnetometer triad are used, an error in the vehicle’s heading, appearing as a sine curve, depending on the heading, occurs. By integrating these sensor triads, the sensor errors have been estimated with a filter to improve the estimated attitude’s accuracy. </p><p>To investigate and evaluate the navigation system, a simulation model has been developed in Simulink/Matlab. The implementation has been made using a Kalman filter where the sensor fusion takes place. Simulations for different scenarios have been made and the results from these simulations show that the drift in the vehicle’s attitude is avoided.</p>

<p>This report describes the manufacture and control of a flying platform. The report describes the basic and fundamental theories required to get the platform flying. It touches on subjects such as A/D-conversion. PWM-control and PID-control. The sensors used in the platform are a gyro and an accelerometer. The platform is controlled from a ground station through a wireless link. The wireless link is an Xbee-module that implements the ZigBee-protocol. The microprocessor used is the Atmega 128 by Atmel.</p><p>An indirect complementary filter is used to get the angle of the platform. For the platform to be able to balance a more thourough analysis of the gyro is required. This sensor proved to be more difficult to handle than first anticipated. Every component except the gyro worked as expected. Every algorithm and method reported in this work have been implemented and tested in software.</p>

<p>This master’s thesis work was performed at Volvo Powertrain in Köping, Sweden, which manufactures gearboxes and integrated transmission systems for heavy vehicles. The thesis is a continuation of a previous master’s thesis performed at the Köping factory in 2009. After manufacturing and assembly, each gearbox is manually validated to ensure the gearbox quality and functionality. When validating the gearbox gears, the operator shifts the gearbox in a predefined manner and listens for irregularities. If an error sound is heard the operator must then locate the source of error. With numerous of cog wheels rotating at the same time this task requires extensive knowledge and experience of the operator. The main objective is to develop an automatic diagnostic system for detection of cog errors and assist the operator in the process of locating the faulty component.</p><p>The work consists of two parts. In the first part the automatic diagnostic system is developed and a database of gearbox recordings is stored. The amounts of logged non-faulty gearboxes are significantly much larger (50) than the logged faulty gearboxes (1). Therefore, when determining thresholds needed for the diagnosis, the data obtained from the non-faulty gearboxes are used. Two statistical methods are presented to extract the thresholds. The first method uses an extremevalue distribution and the other method a Gaussian distribution. When validated, both methods did successfully detect on cog faults. In the second part an investigation is made of how shaft imbalance can be detected and implemented in the developed system.</p><p>Volvo Powertrain continually follows-up all faults found at the validation station to ensure the quality of their work and eliminate the sources of error. During system testing one logged gearbox was found faulty. The automatic diagnostic system did successfully detect and locate the faulty component which later also was confirmed when the gearbox was dismounted. With only one detected error it is difficult to conclude the system performance and further testing is required. However, during the testing no false detections were made.</p>