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Ett sätt att formellt beskriva och mäta hälsotillståndet på en integrationsplattformOlsson, Simon January 2019 (has links)
An integration platform is a platform that is used to integrate data between two incompatible systems. The architecture is fully adapted to the customers’ requirements and therefore looks different between systems. In order to be able to describe and judge the state of the health of an integration platform, there are many factors to consider. This research has been designed to find out which general factors that should be considered in the assessment and description of the health status of an integration platform. A thorough and detailed research and analysis has been made about the general factors that previous researches has highlighted as important. After that, a big analysis of the detected problems was made in comparison to the general factors to draw parallels, conclusions and common denominators if the detected errors depend on the general factors or not. The goal of this was to confirm the validity of the previous research and see if any new factors appear in this integration platform. Two prototypes have been produced to present an overall picture of the actual health status of the integration platform. These two prototypes are developed using assessment in the systems that using the integration platform. These two prototypes have used several factors and parameters in their assessment. A baseline was developed to represent a value that estimate the normal state of the investigated platform. The estimated baseline is an estimate of the normal state within which response time is assumed to be working. This was made to have a value to compare both current and historical health status in the integration platform. Percentiles were also developed to produce an average value. The 50th percentile was used as a general average value and the 90th percentile is used to illustrate and detect severe deviations. The result of the two prototypes is, respectively, an assessment of the actual health status of the integration platform. For more correctness and more detailed assessment of the actual health state, each subsystem in the researched system should be assessed individually because different subsystems affect each other and the health status different. This can lead to misleading picture of the actual health state of the integration platform. This research has combined all the subsystems in the research system in order to be able to describe and measure the actual state of the integration platform.
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Utvärdering av IMU-sensorers precision vid mätning av handledens vinkelhastigheter : Jämförande studie med ett optiskt spårningssystem / Evaluation of the Precision of IMU-sensors Measuring Wrist Angular Velocity : Comparative study with Optical Motion TrackingWingqvist, Jenny, Lantz, Josephine January 2019 (has links)
Belastningsskador hos arbetare är ett ökande problem hos olika företag och det har visat sig finnas en tydlig koppling mellan dessa skador och handledens vinkelhastigheten. Det är därför av stort intresse att kunna mäta dessa vinkelhastigheter på ett noggrant och smidigt sätt. Syftet med denna rapport är att utvärdera precisionen av IMU-sensorers förmåga att beräkna vinkelhastigheten av handleden. Detta görs genom att jämföra data från IMU-sensorer med data från ett optiskt spårningssystem (OTS), vilket klassas som en gold standard inom detta område. Ett experiment bestående av åtta övningar utfördes: tre standard rörelser (flexion och rotation i takterna 40, 90 och 140 slag per minut) och fyra simulerade arbeten (målning, pappersvikning, datorarbete och hårföning). Grad av överensstämmelse ges av 1,96 standardavvikelser (SD) för standardrörelserna (10 deltagare) vilka var -31,8 grader/s och 34,2 grader/s, medan för de simulerade arbetena var det -35,1 grader/s och 34,2 grader/s. Det lägsta medelvärdet av medelkvadratavvikelse (RMSD) var 15,7 grader/s och erhölls vid 40 BPM medan den högsta medelvärdet var 93,9 grader/s och erhölls vid målningsövningen. Medelvärdet av korrelationskoefficienten mellan IMU-sensorer och OTS varierade mellan 0,97 och 0,42 och korrelationskoefficienterna av deltagarnas 50:e percentiler av vinkelhastigheten var 0,95 för standardrörelserna och 0,96 för de simulerade arbetena. Medelvärdet av absoluta differensen mellan sensorer och OTS var givet i percentiler (10:e, 50:e och 90:e). Det största spannet för 50:e percentilen gavs vid 140 BPM (18,3 ± 24,6) och det minsta spannet vid 40 BPM (3,5 ± 4,7). Trots att det fanns mindre differenser mellan metodernas mätningar av vinkelhastighet, anser vi att IMU-sensorer har potential att användas för att mäta vinkelhastigheter hos handledens och med vidare utveckling kan den nuvarande differensen minimeras. / Musculoskeletal disorders (MSDs) are increasingly frequent amongst workers and there is a clear connection between work injuries and wrist angular velocities. One of the biggest issues therefore is the currently limited availability of means to measure these angular velocities. The aim of this study is to validate the usability of the IMU sensors to measure angular velocities. This is done by comparing the data from the IMU:s with the data obtained with the optical motion tracking system (OTS), which is considered gold standard within this field of studies. An experiment consisting of eight exercises was conducted: three standard movements (flexion and rotation in the pace 40, 90 and 140 repetitions per minute) and four simulated practical work tasks (painting, folding paper, computer exercise and using a hairdryer). The limits of agreement for the standard movements (10 subjects) were -31,8 degrees/s and 34,2 degrees/s, whereas for the simulated practical work tasks they were -35,1 degrees/s and 28,2 degrees/s. The lowest mean value of the root mean square deviation (RMSD) value was 15,7 degrees/s which represents the 40 BPM task whilst the highest mean value was 93,9 degrees/s which correspond to the painting task. The mean value of the correlation coefficients between the IMU:s and the OTS ranged between 0,97 and 0,42 and the correlation coefficient between the subjects 50:th percentiles of the angular velocity, was 0,95 for the standard movements whilst for the practical work tasks it was 0,96. The mean value of the absolute difference between the sensors and the OTS was given in percentiles (10th, 50th and 90th). The largest range within the 50th percentile occurred during the 140 BPM task (18,3 ± 24,6) and the smallest range during the 40 BPM task (3,5 ± 4,7). Although the measured angular velocities vary to a certain extent between the two methods, we conclude that the IMU sensors present the potential to work as measuring units for wrist angular velocities and with further development the current differences can be minimized. / Forte dnr: 2017-01209 "Enkel och tideffektiv metod att mät, analysera och presentera biomekaniskbelastning för hand-handled"
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