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.

A realtime wireless motion tracking system is developed. The system is capable of tracking the orientations of multiple wireless sensors, using a semi-distributed implementation to reduce network bandwidth and latency, to produce real-time animation of rigid body models, such as the human skeleton. The system has been demonstrated to be capable of full-body posture tracking of a human subject using fifteen devices communicating with a basestation over a single, low bandwidth, radio channel. The thesis covers the theory, design, and implementation of the tracking platform, the evaluation of the platform’s performance, and presents a summary of possible future applications.

abstract: Head movement is a natural orienting behavior for sensing environmental events around us. Head movement is particularly important for identifying through the sense of hearing the location of an out-of-sight, rear-approaching target to avoid danger or threat. This research aims to design a portable device for detecting the head movement patterns of common marmoset monkeys in laboratory environments. Marmoset is a new-world primate species and has become increasingly popular for neuroscience research. Understanding the unique patterns of their head movements will improve its values as a new primate model for uncovering the neurobiology of natural orienting behavior. Due to their relatively small head size (5 cm in diameter) and body weight (300-500 g), the device has to meet several unique design requirements with respect to accuracy and workability. A head-mount wireless tracking system was implemented based on inertial sensors that are capable of detecting motion in the Yaw, Pitch and Roll axes. The sensors were connected to the encoding station, which transmits wirelessly the 3-axis movement data to the decoding station at the sampling rate of ~175 Hz. The decoding station relays this information to the computer for real-time display and analysis. Different tracking systems, based on the accelerometer and Inertial Measurement Unit is implemented to track the head movement pattern of the marmoset head. Using these systems, translational and rotational information of head movement are collected, and the data analysis focuses on the rotational head movement in body-constrained marmosets. Three stimulus conditions were tested: 1) Alert, 2) Idle 3) Sound only. The head movement patterns were examined when the house light was turned on and off for each stimulus. Angular velocity, angular displacement and angular acceleration were analyzed in all three axes. Fast and large head turns were observed in the Yaw axis in response to the alert stimuli and not much in the idle and sound-only stimulus conditions. Contrasting changes in speed and range of head movement were found between light-on and light-off situations. The mean peak angular displacement was 95 degrees (light on) and 55 (light off) and the mean peak angular velocity was 650 degrees/ second (light on) and 400 degrees/second (light off), respectively, in response to the alert stimuli. These results suggest that the marmoset monkeys may engage in different modes of orienting behaviors with respect to the availability of visual cues and thus the necessity of head movement. This study provides a useful tool for future studies in understanding the interplay among visual, auditory and vestibular systems during nature behavior. / Dissertation/Thesis / Masters Thesis Bioengineering 2015

<p>Surface electromyography (sEMG) has been used to monitor muscle activity and predict fatigue in the workplaces. However, objectively measuring fatigue is challenging in complex work with unpredictable work cycles, where sEMG may be influenced by the dynamically changing posture demands. The sEMG is affected by various variables and substantial change in mean power frequencies (MPF), and a decline over 8-9% is primarily considered musculoskeletal fatigue. These MPF thresholds have been frequently used, and there were limited efforts to test their appropriateness in determining musculoskeletal fatigue in live workplaces (which predominantly consist of complex tasks). In addition, the techniques that consider both muscular and postural measurements that incorporate dynamic posture changes observed in complex work have not yet been explored. The overall objective of this work is to leverage both postural and muscular cues to identify musculoskeletal fatigue in complex tasks/jobs (i.e., tasks involving different levels of exertions, durations, and postures). The work was completed in two studies.</p> The first study aimed to (1) predict subjective fatigue using objective measurements in non-repetitive tasks, (2) determine whether the musculoskeletal fatigue thresholds in non-repetitive tasks differed from the previously reported threshold, and (3) utilize the empirically calculated thresholds to test their appropriateness in determining musculoskeletal fatigue in live surgical workplaces. The findings showed that the multi-modal measurements indicate better sensitivity than single-modality (sEMG) measurements in detecting decreases in MPF, a predictor of fatigue. In addition, the results showed that the thresholds in dynamic non-repetitive tasks, like surgery, are different than the previously reported 8% threshold. Additionally, implementing muscle-specific thresholds increased the likelihood of more accurately reporting subjective fatigue. The second study aimed to develop a multi-modal fatigue index to detect musculoskeletal fatigue. A controlled laboratory study was performed to simulate the non-repetitive physical demands at different postures. A series of experiments were conducted to test the effectiveness of various metrics/models to identify subjective fatigue in complex tasks. Next, the composite fatigue index (CFI) function was developed using the time-synced integration of both muscular signals (measured with sEMG sensors) and postural signals (measured with Inertial Measurement Unit (IMU) sensors). The variables from sEMG (amplitude, frequency, and the number of muscles showing signs of fatigue) and IMU (the prevalence of static and demanding postures and the number of shoulders in static/demanding posture) sensors were integrated to generate the CFI function. The prevalence of static/demanding postures was developed using the cumulative exposures to static/demanding postures based on the material fatigue failure theory. The single value fatigue index was obtained using the resultant CFI function, which incorporates both muscular and postural variables, to quantify the muscular fatigue in dynamic non-repetitive tasks. The findings suggested that the propagation of musculoskeletal fatigue can be detected using the multi-modal composite fatigue index in complex tasks. The resultant CFI function was then applied to surgery tasks to differentiate the fatigued and non-fatigued groups. The findings showed that the multi-modal fatigue assessment techniques could be utilized to incorporate the muscular and postural measurements to identify fatigue in complex tasks beyond single-modality assessment approaches.

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.