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<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.

Virtual reality is rapidly expanding its capabilities and accessibility to consumers. The application of virtual reality in training for precision tasks has been limited to specialized equipment such as a haptic glove or a haptic stylus, but not studied for handheld controllers in consumer-grade systems such as the HTC Vive. A straight-line precision steadiness task was adopted in virtual reality to emulate basic linear movements in industrial operations and disability rehabilitation. This study collected the total time and the error time for the straight-line task in both virtual reality and a physical control experiment for 48 participants. The task was performed at four different gap widths, 4mm, 5mm, 6mm, and 7mm, to see the effects of virtual reality at different levels of precision. Average error ratios were then calculated and analyzed for strong associations to various factors. The results indicated that a combination of Environment x Gap Width factors significantly affected average error ratios, with a p-value of 0.000. This human factors study also collected participants’ ratings of user experience dimensions, such as difficulty, comfort, strain, reliability, and effectiveness, for both physical and virtual environments in a questionnaire. The results indicate that the ratings for difficulty, reliability, and effectiveness were significantly different, with virtual reality rating consistently rating worse than the physical environment. An analysis of questionnaire responses indicates a significant association of overall environment preference (physical or virtual) with performance data, with a p-value of 0.027. In general, virtual reality yielded higher error among participants. As the difficulty of the task increased, the performance in virtual reality degraded significantly. Virtual reality has great potential for a variety of precision applications, but the technology in consumer-grade hardware must improve significantly to enable these applications. Virtual reality is difficult to implement without previous experience or specialized knowledge in programming, which makes the technology currently inaccessible for many people. Future work is needed to investigate a larger variety of precision tasks and movements to expand the body of knowledge of virtual reality applications for training purposes.

abstract: A literature search revealed that previous research on the Attentional Blink (AB) has not examined the role of salience in AB results. I examined how salience affects the AB through multiple forms and degrees of salience in target 1 (T1) and target 2 (T2) stimuli. When examining increased size as a form of salience, results showed a more salient T2 increased recall, attenuating the AB. A more salient T1 did not differ from the control, suggesting the salience (increased size) of T2 is an important factor in the AB, while salience (increased size) of T1 does not affect the AB. Additionally, the differences in target size (50% or 100% larger) were not significantly different, showing size differences at these intervals do not affect AB results. To further explore the lack of difference in results when T1 is larger in size, I examined dynamic stimuli used as T1. T1 stimuli were presented as looming or receding. When T1 was presented as looming or receding, the AB was attenuated (T2 recall at lag 2 was significantly greater). Additionally, T2 recall was significantly worse at lags three and four (showing a larger decrease directly following the attenuated AB). When comparing looming and receding against each other, at lag 2 (when recall accuracy at its lowest) looming increased recall significantly more than receding stimuli. This is expected to be due to the immediate attentional needs related to looming stimuli. Overall, the results showed T2 salience in the form of size significantly increases recall accuracy while T1 size salience does not affect the AB results. With that, dynamic T1 stimuli increase recall accuracy at early lags (lag 2) while it decreases recall accuracy at later lags (lags 3 and 4). This result is found when the stimuli are presented at a larger size (stimuli appearing closer), suggesting the more eminent need for attention results in greater effects on the AB. / Dissertation/Thesis / Doctoral Dissertation Human Systems Engineering 2019

Master of Science

<p>Flying an airplane is a complex operation. Pilots must be able to manipulate the three-dimensional flight characteristics, maintain situational awareness, aircraft configurations, interpret charts, and handle communications with air traffic control. This requires maximum cognitive and psychomotor skills. The National Transportation Safety Board (NTSB) has added reducing fatigue-related accidents is on their top ten most wanted list. According to the NTSB (2019), fatigue “degrades a person’s ability to stay awake, alert, and attentive to the demands of safely controlling a vehicle, vessel, aircraft, or train” (p.18). Additionally, the Federal Aviation Administration (FAA) has called on stakeholders, including the academic community, to reduce the number of accidents in the general aviation sector (Federal Aviation Administration, 2018). After a review of extant literature, most fatigue research in aviation pertains to airline and military operations (Keller, Mendonca, & Cutter, 2019; Levin, Mendonca, Keller, & Teo, 2019; Mendonca, Keller, Lu, 2019). However, collegiate aviation students have differences such as class scheduling, maturity, and regulations. Thus, making collegiate aviation pilots a unique population. Therefore, the purpose of this study was threefold: 1) To investigate the causes and symptoms of fatigue among collegiate aviation students. 2) To investigate whether there is a statistically significant association between enrollment status and a participant’s willingness to fly fatigued. 3) To investigate whether a participant’s age and flight hours predict their willingness to fly while fatigued. The researcher used a mixed-methods online-based survey to answer the research questions. The researcher used convenience and judgment sampling to distribute the survey to eight collegiate aviation programs in the United States. A total of 248 (n = 248) participants participated in the survey. The results of the survey indicated that participants cited excessive workload, stress, and sleep-related issues (disturbances and poor quantity) as the most common causes of fatigue. Participants cited drowsiness, loss of concentration, and physical/mental discomfort, including irritation, as symptoms of fatigue. The results also indicated that there was a statistically significant association between enrollment status and a participant’s willingness to fly while fatigued; students from higher enrollment statuses are more willing to fly fatigued. Lastly, the results indicated that age might be used as a predictor for a participant’s willingness to fly while fatigued. Conversely, flight hours cannot be used as a predictor for a participant’s willingness to fly while fatigued.</p>

Objective: The human–machine interface (HMI) is a crucial part of every automated driving system (ADS). In the near future, it is likely that—depending on the operational design domain (ODD)—different levels of automation will be available within the same vehicle. The capabilities of a given automation level as well as the operator’s responsibilities must be communicated in an appropriate way. To date, however, there are no agreed-upon evaluation methods that can be used by human factors practitioners as well as researchers to test this. Methods: We developed an iterative test procedure that can be applied during the product development cycle of ADS. The test procedure is specifically designed to evaluate whether minimum requirements as proposed in NHTSA’s automated vehicle policy are met. Results: The proposed evaluation protocol includes (a) a method to identify relevant use cases for testing on the basis of all theoretically possible steady states and mode transitions of a given ADS; (b) an expert-based heuristic assessment to evaluate whether the HMI complies with applicable norms, standards, and best practices; and (c) an empirical evaluation of ADS HMIs using a standardized design for user studies and performance metrics. Conclusions: Each can be used as a stand-alone method or in combination to generate objective, reliable, and valid evaluations of HMIs, focusing on whether they meet minimum requirements. However, we also emphasize that other evaluation aspects such as controllability, misuse, and acceptance are not within the scope of the evaluation protocol.

Customers today demand products of high quality, and industries must cope with issues related to that to stay competitive. Therefore, an endeavor to achieve zero defects and to work with zero defect manufacturing (ZDM) is common in industries today. ZDM aims to reduce the number of failures within a manufacturing process and thus only producing faultless products. Since defected items result in unexpected work, extra costs, claims and unsatisfied customers, it is important to avoid that in order to secure the company’s market share. Even though it implies challenges, companies must work with ZDM and quality tools to stay competitive. However, there is a gap between the literature of ZDM and how to accomplish ZDM in practice, which makes it hard for companies to apply the method. Hence, this thesis aims to address this gap and present how the human factors and quality contribute to the goal of zero defects. When working with a manually driven manufacturing setting, human factors must be considered as an important aspect. Mistakes will occur as long as humans work with the products, but the prerequisites for doing right must be as good as possible to be able to decrease the number of mistakes. Another factor to consider is the internal quality of different processes to ensure that customer demands are achieved through all stages. This study focused on finding suggestions for improvements towards zero defects in manual assembly and to present general improvement actions. The thesis is based on three main fields: ZDM, quality and human factors. The findings are connected both to literature searches made within these fields, but also through a case study at the focal company. In the analysis chapter, the reader is provided with information about how the specified problem areas are linked together and to the three main fields. By combining the literature search with a case study at a focal company, findings could be detected, collected and analyzed. Four areas could be identified in the analysis and highlighted in the discussion of the research questions. The highlighted areas were further used as a foundation to establish suggestion within the important areas. These acts as practical guidelines for how to reach zero defects in an existing production with the goal of minimizing the implementation gap of ZDM.

Non-technical skills (NTS) are cognitive and interpersonal skills that are relevant to task completion such as situation awareness, decision-making, teamwork, and leadership. NTS in clinical environments, such as surgery, have been identified to contribute to patient safety and team performance, which in turn affects clinical outcomes. Assessment tools of these skills in surgery exist; however, current evaluations are limited in that they require trained raters, are subjective, are time-intensive, and are checklist-based. Therefore, there is a need for objective measurement of NTS that addresses the limitations of the rating-based techniques. The purpose of this Ph.D. dissertation work is to identify physiological and behavioral metrics that measure NTS objectively and investigate the application of objective metrics to measure intraoperative NTS of surgeons. Through a scoping review of engineering, behavioral science, and medical literature, behavioral and physiological metrics that quantified NTS constructs of surgeons were identified. The synthesized literature was used to build a framework integrating objective metrics to NTS constructs. To develop an objective model of surgeons’ NTS, subjective and objective behavioral data of surgeons were collected in the operating room and prediction models were created. Results found that objective metrics such as communication, speech, and proximity features can be used to predict subjective NTS. Furthermore, objective task features (e.g., time and number of incidents during an operation) has the potential to also model subjective NTS, and these task features can be predicted by the behavioral metrics; thus, triangulation is obtained with the three NTS metrics: subjective score, objective behavioral metrics, and task performance metrics. The relationship between the two objective metrics shows the possibility of achieving a fully objective model of surgeons’ NTS. The consolidation of current objective measurement techniques can provide a foundation in further understanding NTS beyond assessments based on observed behaviors, and the developed models can be expanded and implemented for real-time NTS assessment of clinical teams to improve patient care.

In couple relationships, the phenomenon of accepting influence is both an observable action, seen in couples compromising and respecting each other, as well as an approach to the relationship, one’s perception that their partner is someone worthy of sharing power with. This study utilizes a life course perspective to examine the mediated relationship between childhood experiences, partners accepting influence, and relationship satisfaction in a sample of military couples. An actor partner interdependence mediation model was fit in Amos to examine the relationships. Civilian spouses’ childhood experiences were related to their perception their partner accepts influence and service members’ perception their partner accepts influence; this was then related to both partners’ relationship satisfaction. Accepting influence is a potential leverage point for improving relationship satisfaction in military couples who may be at an increased risk due to the nature of military life.