Container vessel motions need to be small when loading and offloading cargo while moored to wharfs. Waves and their reflections from structures can induce ship motions. These motions are characterized by six degrees of freedom, including translations of surge, sway, and heave and rotations of pitch, roll, and yaw. Monitoring and quantifying these motions offer a reference for design and selection of the mooring system and wharf types. To measure the six degrees of freedom motions of a container ship moored to a dock, a 1:50 scale model is moored to two types of dock, solid wall dock and pile supported dock. Irregular waves of TMA spectrum with various periods, heights, and directions are generated in the wave basin to induce the motions of the model container ship. Optical motion capturing cameras are used to measure and quantify the six degree of freedom motions. Results of the effects of wave period, significant wave height, and wave direction on the motion characteristics of the model container ship moored at the solid dock and a pile supported dock are described in detail. A numerical simulation called aNySIM is applied to numerically predict the motion characteristics of the container ship moored to a solid wall dock only. The physical model experimental results of solid dock are also compared with the numerical simulation. These comparisons indicate that the motion characteristics of the model container ship represent similar trends for both rotations and translations. The experimental and numerical prediction values of motions of the ship moored to a solid wall dock display the same tendencies while differing in magnitude.

There is a need for objective methods for wrist angular velocity measurements for accurate risk assessments because there is a high frequency of musculoskeletal disorder in workers. The goal of this project was to validate the accuracy of inertial measurement unit sensors to measure the angular velocity. More specifically, the purpose of this master thesis project was to apply an alternative algorithm to compute the markers velocity, other than the one from the optical system that Jenny Wingqvist, and Josephine Lantz used. The project used an experimental data of 10 participants from the previous project done by Jenny Wingqvist and Josephine Lantz. To validate the accuracy, the data of angular velocity of the sensors was compared with the data of angular velocity of markers. The lowest mean value of the root mean square differences value was 23.5 degrees/s during flexion and deviation standard movements at 40 BPM (Beats Per Minute) and the maximum value was 110.5 degrees/s at 140 BPM. The mean value of the correlation coefficients between markers and sensors angular velocities in standard movements of flexion and deviation were 0.85, 0.88, and 0.89 at 40 BPM, 90 BPM, and 140 BPM, respectively. The smallest and the largest mean value of the absolute difference in 50th percentile was found in 40 BPM (19.4±11.3), and 140 BPM (51.2±28.5) respectively. The decorrelation coefficient between the subjects 50th percentile of the angular velocity was 0.91 for the standard movements. The upper limit of agreement for the standard movements was 78.36 degrees/s, while the lower limit of agreement was -13.76 degrees/s.  The results show that the error was too large, so there is a need of further research to measure the wrist angular velocity using IMU sensors.

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"

Repetitive tasks, awkward hand/wrist postures and forceful exertions are known risk factors for work-related musculoskeletal disorders (WMSDs) of the hand and wrist. WMSD is a major cause of long work absence, productivity loss, loss in wages and individual suffering. Currently available assessment methods of the hand/wrist motion have the limitations of being inaccurate, e.g. when using self-reports or observations, or expensive and resource-demanding for following analyses, e.g. when using the electrogoniometers. Therefore, there is a need for a risk assessment method that is easy-to-use and can be applied by both researchers and practitioners for measuring wrist angular velocity during an 8-hour working day. Wearable Inertial Measurement Units (IMU) in combination with mobile phone applications provide the possibility for such a method. In order to apply the IMU in the field for assessing the wrist velocity of different work tasks, the accuracy of the method need to be examined. Therefore, this laboratory experiment was conducted to compare a new IMU-based method with the traditional goniometer and standard optical motion capture system. The laboratory experiment was performed on twelve participants. Three standard hand movements, including hand/wrist motion of Flexion-extension (FE), Deviation, and Pronationsupination (PS) at 30, 60, 90 beat-per-minute (bpm), and three simulated work tasks were performed. The angular velocity of the three methods at 50th and 90th percentile were calculated and compared. The mean absolute error and correlation coefficient were analysed for comparing the methods. Increase in error was observed with increase in speed/bpm during the standard hand movements. For standard hand movements, comparison between IMUbyaxis and Goniometer had the smallest difference and highest correlation coefficient. For simulated work tasks, the difference between goniometer and optical system was the smallest. However, for simulated work tasks, the differences between the compared methods were in general much larger than the standard hand movements. The IMU-based method is seen to have potential when compared with the traditional measurement methods. Still, it needs further improvement to be used for risk assessment in the field. / Upprepade uppgifter, besvärliga hand- / handledsställningar och kraftfulla ansträngningar är kända riskfaktorer för arbetsrelaterade muskuloskeletala störningar (WMSD) i hand och handled. WMSD är en viktig orsak till lång frånvaro, produktivitetsförlust, löneförlust och individuellt lidande. För närvarande tillgängliga bedömningsmetoder för hand / handledsrörelser har begränsningarna att vara felaktiga, t.ex. när du använder självrapporter eller observationer, eller dyra och resurskrävande för följande analyser, t.ex. när du använder elektrogoniometrarna. Därför finns det ett behov av en riskbedömningsmetod som är enkel att använda och som kan användas av både forskare och utövare för att mäta handledens vinkelhastighet under en 8-timmars arbetsdag. Wearable Inertial Measuring Units (IMU) i kombination med mobiltelefonapplikationer ger möjlighet till en sådan metod. För att kunna använda IMU i fältet för att bedöma handledens hastighet för olika arbetsuppgifter måste metodens noggrannhet undersökas. Därför genomfördes detta laboratorieexperiment för att jämföra en ny IMU-baserad metod med den traditionella goniometern och det vanliga optiska rörelsefångningssystemet. Laboratorieexperimentet utfördes på tolv deltagare. Tre standardhandrörelser, inklusive hand / handledsrörelse av Flexion-extension (FE), Deviation och Pronation-supination (PS) vid 30, 60, 90 beat-per-minut (bpm) och tre simulerade arbetsuppgifter utfördes. Vinkelhastigheten för de tre metoderna vid 50: e och 90: e percentilen beräknades och jämfördes. Det genomsnittliga absoluta felet och korrelationskoefficienten analyserades för att jämföra metoderna. Ökning av fel observerades med ökning av hastighet/bpm under standardhandrörelserna. För standardhandrörelser hade jämförelsen mellan IMUbyaxis och Goniometer den minsta skillnaden och högsta korrelationskoefficienten. För simulerade arbetsuppgifter var skillnaden mellan goniometer och optiskt system den minsta. För simulerade arbetsuppgifter var dock skillnaderna mellan de jämförda metoderna i allmänhet mycket större än de vanliga handrörelserna. Den IMUbaserade metoden anses ha potential jämfört med traditionella mätmetoder. Ändå behöver det förbättras för att kunna användas för riskbedömning på fältet.