The e-OPRA Implant System (Integrum AB, Sweden) is a system which employs permanently accessible implantable neuromuscular electrodes in combination with osseointegrated attachment of the prosthesis to the skeleton, in order to create a more natural control of advanced robotic upper-limb prostheses. The system enables the possibility of sensory feedback, via a cuff electrode to the ulnar nerve which allows for direct neurostimulation of the nerve. This work proposes a method using electroencephalography (EEG) to quantitatively evaluate the cognitive workload of a person controlling a prosthesis, and how said workload changes when sensory feedback is enabled. Based on previous studies on EEG and cognitive workload, the proposed methods include collecting EEG data from subjects who are performing a grasping task while listening to a selection of sounds and counting the number of times a specific tone is presented. The data is analysed using both event related potentials (ERPs) as well as spectral analysis. The method was used in a trial run consisting of two healthy subjects, and one transhumeral amputee implanted with the e-OPRA system. Although the subject group was not large enough to draw any statistical conclusions, the trial run and the results from it suggest that the methods could be used in a larger study to evaluate the cognitive workload of amputees implanted with the e-OPRA system.

This research evaluated mental schema accuracy, user experience, and training methods of computer based tasks using educational software. Aims were to investigate the impact of mental schemas on individuals’ usability of technology and analyze the impact of training and user experience in terms of mental schemas and performance. Study one investigated schema accuracy as a predictor of perceived usability and mental workload; by analyzing the accuracy of users’ mental schema through task correctness. Task was found to be a significant predictor of the measures of usability, along with various demographic variables. When considering the effect of tasks, schema accuracy was a significant predictor of perceived usability and mental workload for task two (online quiz). Perceived usability showed lower values indicating higher perceptions of usability for task two and mental workload had lower values indicating reduced mental workload for task two. Significant, positive correlations were found between perceived usability and mental workload. Findings show schema accuracy as a preliminary measure of users’ subjective usability of non-problem solving tasks, based on the type of task tested and demographic data of students. Study two examined experience level (experienced and un-experienced) effects mental schema accuracy, robustness, completion time, and errors using three computer-based tasks. Experienced participants showed lower values for number of errors and robustness than un-experienced users. Significant, positive correlations were found between schema accuracy and completion time, and errors and completion time. The findings support the use of experience to analyze the impact of mental schemas and performance measures. Study three explored the change in training methods (no-training, paper, or video) on user changes in mental schema accuracy, robustness, completion times and errors. Training improved robustness, specifically paper-based training. Performance results showed that students who spent small periods of time using the software more times a week had made fewer errors and had more robust schemas. Demographic experience categories found that participants who spent more time using the software had fewer errors. Significant, positive correlations were found between schema accuracy and robustness. These results show that training improves mental schema robustness and reduces the number of errors while completing computer based tasks.

A recent trend in consumer and military electronics has been to allow operators the option to control the system via novel control methods. The most prevalent and available form of these methods is that of vocal control. Vocal control allows for the control of a system by speaking commands rather than manually inputting them. This has not only implications for increased productivity but also optimizing safety, and assisting the disabled population. Past research has examined the potential costs and benefits to this novel control scheme with varying results. The purpose of this study was to further examine the relationship between modality of input, operator workload, and expertise. The results obtained indicated that vocal control may not be ideal in all situations as a method of input as participants experienced significantly higher amounts of workload than those in the manual condition. Additionally, expertise may be more specific than previously thought as participants in the vocal condition performed nearly identical at the task regardless of gaming expertise. The implications of the findings for this study suggest that vocal control be further examined as an effective method of user input, especially with regards to expertise and training effects.

Displays are a useful tool for users and operators to understand information quickly. Configural displays are effective in supporting focus and divided attention tasks through the use of emergent features. Emergent features are highly salient and are generally used to support divided attention task However, due to the salience of emergent features, a potential performance costs to focused attention tasks arises with configural displays. To address this cost, semantic mapping has been used to map salience techniques to information needed by focus attention tasks to increase their saliency (Bennett & Walters, 2001; Bennett et al., 2000). Semantic mapping is the process of mapping the domain constrains to the display, which in turn is mapped to the users capabilities and limitations to understand that domain data. The objective of this dissertation is to extend the use of semantic mapping to address potential performance costs of configural displays for hierarchical domains using the scenario-based training (SBT) instructor domain. Two studies were conducted to examine the effects of salience application and salience type on data extraction accuracy and response time performances at low-level, mid-level, high-level, and a remediation task. The first study examined the effects of one salience technique mapped to the display. This study employed a 2(low or mid application) X 3(baseline, color techniques, and alphanumeric techniques) mixed model design in which 63 participants completed 3 blocks of 32 trails each using displays with the salience techniques mapped to either low- or mid-level data. Results from the first study showed that salience type had a significant impact on multi-level data extraction performance, but interactions were not found. The second study changed the manipulation of application and mapped two salience techniques display at the same time, using either the same technique or a combination of different techniques. The same experimental design was utilized and 65 participants completed study 2. Results of study 2 showed that different application resulted in greater improvements of performance and specific salience combinations were found better support data extraction performance. Across study analyses were also performed and revealed that more salience is not better than less salience. Instead it is the specific mapping of salience type and application which improves performance the most. Overall, these findings have major implications for theories of semantic mapping, attention and performance, and display design of hierarchical domains.

Throughout the many years of research examining the various effects of automation on operator performance, stress, workload, etc., the focus has traditionally been on the level of automation, and the invocation methods used to alter it. The goal of the current study is to instead examine the utilization of various types of automation with the goal of better meeting the operator’s cognitive needs, thus improving their performance, workload, and stress. The task, control of a simulated unmanned robotic system, is designed to specifically stress the operator’s visual perception capabilities to a greater degree. Two types of automation are implemented to support the operator’s performance of the task: an auditory beep aid intended to support visual perception resources, and a driving aid automating control of the vehicle’s navigation, offloading physical action execution resources. Therefore, a comparison can be made between types of automation intended to specifically support the mental dimension that is under the greatest demand (the auditory beep) against those that do not (the driving automation). An additional evaluation is made to determine the benefit of adaptively adjusting the level of each type of automation based on the current level of task demand, as well as the influence of individual differences in personality. Results indicate that the use of the auditory beep aid does improve performance, but also increases Temporal Demand and Effort. Use of driving automation appears to disengage the operator from the task, eliciting a vigilance response. Adaptively altering the level of automation to meet task demands has a mixed effect on performance and workload (reducing both) when the auditory beep automation is used. However, adaptive driving automation is clearly detrimental, iv causing an increase in workload while decreasing performance. Higher levels of Neuroticism are related to poorer threat detection performance, but personality differences show no indication of moderating the effects of either of the experimental manipulations. The results of this study show that the type of automation implemented within an environment has a considerable impact on the operator, in terms of performance as well as cognitive/emotional state

There are two theoretical approaches to the nature of attentional resources. One proposes a single, flexible pool of cognitive resources; the other poses there are multiple resources. This study was designed to systematically examine whether there is evidence for multiple resource theory using a counting task consisting of visual, auditory, and tactile signals using two experiments. The goal of the first experiment was the validation of a multi-modal secondary loading task. Thirty-two participants performed nine variations of a multi-modal counting task incorporating three modalities and three demand levels. Performance and subjective ratings of workload were measured for each of the nine conditions of the within-subjects design. Significant differences were found on the basis of task demand level, irrespective of modality. Moreover, the perceived workload associated with the tasks differed by task demand level and not by modality. These results suggest the counting task is a valid means of imposing task demands across multiple modalities. The second experiment used the same counting task as a secondary load to a primary visual monitoring task, the system monitoring component of the Multi-Attribute Task Battery (MATB). The experimental conditions consisted of performing the system monitoring task alone as a reference and performing system monitoring combined with visual, auditory, or tactile counting. Thirty-one participants were exposed to all four experimental conditions in a within-subjects design. Performance on the primary and secondary tasks was measured, and subjective workload was assessed for each condition. Participants were instructed to maintain performance on the primary task, irrespective of condition, which they did so effectively. Secondary task performance for the visual-auditory and visual-tactile conditions was significantly better than for the visual-visual dual task condition. Subjective workload ratings were also consistent with the performance measures. These results clearly indicate that there is less interference for cross-modal tasks than for intramodal tasks. These results add evidence to multiple resource theory. Finally, these results have practical implications that include human performance assessment for display and alarm development, assessment of attentional reserve capacity for adaptive automation systems, and training.

The purpose of this study is to extend previous findings of Mouloua, Parasuraman, and Molloy (1993), Parasuraman, Mouloua, and Molloy (1996), Hilburn, Parasuraman, and Mouloua (1996), and Oakley, Mouloua, and Hancock (2003) by: 1) examining the effect of repeated adaptive function allocation to manual control of minimal length (5 minutes) to reduce of human error and minimize workload; 2) explore the placement or timing of adaptive function allocation intervals (approximately 20 minutes of automation control to reduce the human operators' monitoring decrement between intervals, maintain adaptive recovery performance levels, and improve response times); 3) examine different levels of automation reliability (30%, 60%, and 90% reliable); 4) explore factors that may be manipulated to reduce automation-induced monitoring inefficiency, increase detection of automation malfunctions, improve situation awareness, reduce response/reaction times, and reduce workload in a simulated complex aviation system. The study was a 2 (non-adaptive control vs. adaptive group) x 3 (30%, 60%, and 90% automation reliability condition) x 4 (repeated 25 minute session) mixed factorial design. Fifty-four undergraduate participants' (i.e., 27 participants per group; 9 participants per condition; at least 18 yrs. of age) percentage of detected malfunctions, response times, and subjective workload were gathered from the Multi-Attribute Task Battery and the NASA TLX. Results indicated a significant improvement in detection of malfunctions and response times during adaptive-function allocation to manual control but without adaptive recovery. There was a significant effect for workload found between baseline measures and experimental sessions by group in the first session but not across experimental sessions. Theoretical and practical implications, limitations and future research are discussed.

This research generated a model that will help to predict, prevent, control and mitigate the occurrence of task related factors that negatively influence stress, fatigue, and workload; thus enhancing human performance. Past research efforts involving stress, fatigue and workload identified factors that influence a change in performance (Lan, Ji and Looney, 2003, and Hancock & Warm, 1989). Also, while some mathematical models have been developed within each respective area, however, there is no evidence of an integrated model describing the combined affect of stress, fatigue and workload. To respond to this research gap, a quantitative model representing the state of stress, fatigue and workload experienced under task conditions was developed. This model was derived using fuzzy set theory with data inputs from both objective and subjective measures such as heart rate, NASA TLX, blood pressure and a variety of additional factors. The resultant mathematical model included both subjective and objective measures that can be collected in an occupational environment. Control rooms at the flight centers for large space craft were utilized to validate the quantitative model developed in this research. Data was gathered during launch simulation exercises. Fuzzy Set Theory was applied to develop the mathematical model to describe the changes in stress, fatigue and workload. FST provides a means to model many real-world environments.

This thesis deals with the development of an Airspace Sector Occupancy Model (ASOM). The model determines the occupancy of Air Traffic Control Center (ARTCC) sectors for a given geometry of sectors and flight schedules, and can be used to study the impact of alternative flight schedules on the workload imposed on the sectors. Along with complimentary airspace analysis models, this can serve as an advisory tool to approve flight plans in the Free Flight Scenario, or to reschedule flights around a Special Use Airspace (SUA). ASOM is developed using Matlab 5.2, and can be run on an IBM compatible PC, Macintosh, or Unix Workstation. The computerized model incorporates the powerful features of graphics and hierarchical modeling inherent in Matlab, to design an effective tool for analyzing air traffic scenarios and their respective sector occupancies. / Master of Science

<p>  </p> <p>Some of the variability found in measures of mental workload (see e.g. Singleton et al. 1973; Wierwille and Connor 1983; Steelman-Allen et al. 2011; Casner and Gore 2010) may be due to the effort applied to the task by participants, rather than by the independent variable of interest. If true, capturing and removing the variation due to ‘applied effort’ could improve the ability of studies to detect effects of interest. </p> <p>While introducing participants to two sub-tasks derived from Multi-Attribute Task Battery II (Santiago-Espada et al. 2011), the study investigated the influence of applied effort on MATB-II performance measures of mental workload while holding other effects constant. Two groups of participants each completed easy and hard trials of MATB-II-derived sub-tasks. Treatment group of participants was offered an additional reward if they achieved a sufficiently high performance.</p> <p>The treatment group performed better by just under 4% in both easy and hard trials which provides a suggestion about the size of the effect of applied effort in this study. </p> <p>Additionally pilot error analysis was performed using Tracking task results. Error probability distributions did not fit known distributions and did not show consistent difference between treatment and control groups. Novel method of distribution “tails” comparison showed significant difference in extreme error durations, extents and delays between treatment and control groups.</p> <p>Measuring or controlling for applied effort can improve the ability of researchers to determine the effects of interventions on workload measures by reducing the amount of variability that is captured as error. Also, “tails” method seems to be a viable tool in comparing probability  </p>