Motivado pelo fato de que a escolha correta da forma preênsil para mãos robóticas antropomórficas representa aspectos relevantes no planejamento de estratégias de manipulação de objetos, este trabalho: desenvolve um algoritmo de pegas de objetos compatíveis com a tarefa a ser realizada e um método computacional de ajuste de superelipsóides a superfícies de objetos sintéticos 3D para modelar as primitivas resultantes do estágio de segmentação manual do objeto. Essa representação volumétrica contempla as atrativas propriedades de um modelo compacto, controlável e intuitivo, capaz de modelar uma ampla variedade de geometrias simétricas básicas a partir de 11 parâmetros. Tendo em vista que a acomodação de superelipsóides a nuvens de pontos caracteriza desafios típicos de mínimos quadrados, um breve estudo sobre o método numérico de Levenberg-Marquardt, utilizado na minimização da função objetivo adotada, se mostrou necessário para maximizar a sua eficiência. O desempenho e a eficiência do programa computacional desenvolvido foram demonstrados na modelagem experimental de cinco primitivas organizadas em diferentes configurações. As pequenas distorções, consideradas aceitáveis para a proposta do trabalho, evidenciaram a robustez da representação de formas elementares empregando superelipsóides sem deformações. Encerrada a etapa de modelagem das primitivas, um método de auto-aprendizagem supervisionada interpreta as informações de forma e tamanho de tais formas básicas para sugerir a pega de uma das primitivas que compõem o objeto e a forma preênsil compatível com a tarefa desejada. / Motivated by the fact that the correct choice of prehensile form for anthropomorphic robotic hand describes relevant aspects in planning strategies of object manipulation, this work develops an algorithm of grasping objects to match the task requirements and a computational method capable of fitting superellipsoids to surfaces of synthetic 3D objects to model the resulting primitives from the manual segmentation stage of the object. This volumetric representation describes the attractive properties of a compact, controllable and intuitive model, which is capable of modeling a wide variety of standard geometric solids by using eleven parameters. Since the superellipsoid fitting process characterizes typical least squares problems, a brief review about Levenberg-Marquardt numerical method, employed for the adopted objective function minimization, was necessary to maximize its efficiency. The performance and efficiency of the developed program were demonstrated in the experimental modeling of five symmetrical primitives shapes organized in several configurations. The small distortions, considered acceptable to the work proposal, confirm the robustness of representing elementary shapes employing superellipsoids without deformations. After finishing the primitive modeling stage, a supervised learning method interprets the size and shape information of such basic shapes to suggest the grasp of one constituent single parts and the task-compatible prehensile form.

Multitasking in background noise may involve greater cognitive processing demands than multitasking in quiet due to an increase in perceptual demands (Rabbitt, 1968; Pichora-Fuller & Schneider, 2000). This study investigated the effect of background noise in the listening environment on the ability of young adults with normal hearing and older adults with sensorineural hearing loss to perceive speech while performing a secondary task. A dual task paradigm, which included word recognition and visual serial recall, was used to examine ability to divide limited processing resources between two tasks. The number of digits to be recalled was varied in order to test the hypothesis that background noise would degrade multitasking abilities to a greater degree than in quiet for more difficult tasks. Participants included 37 native English speakers between 19-25 years of age with pure-tone thresholds better than or equal to 20 dB HL and 10 English speakers between 58-85 years of age with pure-tone thresholds greater than or equal to 25 dB HL in both ears. The results showed that background noise can have negative effects on the ability to multitask for both younger adults with normal hearing and older adults with hearing loss; however, this effect was greater for the older adults with hearing loss, especially when task demands were increased.

Introduction: The prefrontal cortex (PFC) is highly susceptible to age-related deterioration. As such, executive function deficits are commonly observed when older adults process two attention-demanding tasks simultaneously. Everyday tasks such as walking and talking on the phone involve executive functions and the integration of cognitive-motor pathways. However, less is known about this relationship as cognitive demands increase. Methods: Twenty healthy older adults (M = 71.8 years, SD = 6.4) performed four auditory cognitive tasks of increasing demand, including a simple reaction time (SRT), go/no-go (GNG), n-back (NBK), and double number sequence (DNS) task with or without self-paced walking (i.e., single- versus dual-task). Using a blocked design, prefrontal hemodynamic changes (i.e., oxy- [∆HbO2] and deoxyhemoglobin [∆HbR]) were measured using functional near-infrared spectroscopy (fNIRS) and performance was assessed using measures of response time (s), accuracy (% correct) and gait speed (m/s). Results: Prefrontal activation decreased between the single- and dual-tasks across all task demands. Behaviourally, the SRT response times were significantly faster than GNG and NBK. Accuracy decreased between single- and dual-tasks and with increasing demand, but the NBK and DNS tasks were not significantly different. An interaction between task and demand was observed for gait speed such that the DNS dual-task was significantly slower than the single-task. Conclusion: Neural findings support an automatic locomotor control strategy in that cerebral oxygenation decreased between single- and dual-tasks and gait speed was maintained up until the most demanding cognitive task. However, decreased prefrontal activation was inefficient at supporting response time and accuracy performance which may indicate that cognitive performance is differentially affected by cognitive demand and deficits in executive functioning.

Children with varying exceptionalities including ADHD, Autism Spectrum Disorder, and other learning disabilities often struggle with attention deficits. The persistence of alternative non-behavioral approaches in classrooms to address this deficit presents the need for more research and education about these interventions. Specifically, the fidget spinner is a newer intervention which currently has no empirical evidence to support its use in the classroom setting. The purpose of this study was to examine the effects of fidget spinners on increasing engagement and academic comprehension in a whole classroom environment. A multiple baseline across participants design was used with six children with varying diagnoses who struggled with attention deficits. Results showed that fidget spinners were ineffective at increasing engagement or academic comprehension and that self-monitoring was effective at increasing both engagement and academic performance.

The purpose of the present study was to compare the number of perseverations on fused (no delay) versus unfused (0.5 msec delay) CV-DL tasks with measures on a battery of executive functions across three groups: Schizophrenics (SCZ), Manic-Depressives (MD), and normal controls (NC).

BACKGROUND: Age-related deterioration in the nervous system results in the decline of motor and cognitive abilities, which both have been identified as contributing to fall risk in older adults. Dual-task gait, which involves walking while performing a secondary cognitive task, is a common way to assess the interactions between cognitive and motor function. Previous work has established associations between the cost of the cognitive load on gait parameters (e.g., velocity) and fall risk in older adults. However, to date, no study has explored the potential value of combining a direct measure of performance on the cognitive component of the dual-task with the gait measures in fall risk prediction modeling. RESEARCH QUESTIONS: Does including measures of performance on the cognitive task in dual-task walking with the gait velocity measures enhance the capacity to predict fall risk. Is this predictive capacity different in models employing dual-task gait velocity versus models including the cost of the cognitive load on gait velocity? METHODS: Thirty-two community-dwelling older adults (76 years ± 3.44) were classified as fallers (n = 17) and non-fallers (n = 15) based on self-report of having at least one fall in the past 12 months. They completed single-task and dual-task walking on a pressure-sensing electronic walkway system. A progressively enhanced series of logistic regression models were performed commencing with gait velocity during the dual-task (Loaded Gait Velocity, LGV) as the covariate in predicting fall risk. This model was subsequently augmented by adding a measure of cognitive performance covariate and then further augmented with the addition of the interaction variable between the LGV and the cognitive performance variables. This stepped series of modelling was then repeated with the dual-task cost gait velocity (DTCGV, difference in gait velocity between single and dual-task). RESULTS: With the addition of the cognitive measures (CM) and the interaction variables between the GV and CM variables, in both the LGV and DTC_GV models, the Nagelkerke’s R square increased as did the models’ respective sensitivity. Notably, the model including the LGV, CM and the interaction variables achieved 88.2% sensitivity, 80% specificity, with an overall classification accuracy of 84.4%. DISCUSSION: This study is the first to show that the ability to identify fallers and non-fallers is enhanced by using both gait and cognition measures as well as interaction variables between gait and cognition measures. Further, our findings suggest that the added value of the cognitive measures is best realized with LGV rather than DTCGV. It reasons that because DTC already encompasses the cost of the cognitive load on the motor performance (gait velocity), combining it with cognitive metrics does not enhance its predictive capacity. This work suggests there is clinical utility of including cognitive performance measures in fall risk modeling as well as it provides further evidence of the interplay between cognitive and motor function in fall risk. / Graduate

This research introduces the concept of transferability into the usability construct and creates the Usability Paradigm for Multiple Device System (UPMDS) to conceptualize and quantify the usability in multiple device scenarios. This study fills the literature gap that no effective method exists in measuring transferability and in quantifying usability in a multiple device context. This study also answers the research questions regarding the impact of task complexity, user experience, and device order on the total usability of the system. Study one follows a systematic approach to develop, validate, and apply a new questionnaire tailored specifically to measure the transferability within a multiple device system. The System Transferability Questionnaire (STQ) is obtained after validation with 15 question items. In a software usability study, the STQ demonstrated excellent internal reliability and validity. Results show that the STQ is effective in capturing four factors regarding transferability, which are transfer experience (TE), overall experience (OE), consistency perception (CP) and functionality perception (FP). Validation results show good convergent, discriminant, criterion and nomonlogical validity. Study two adopts a systematic tool to consolidate usability constructs into a total usability score. The study utilizes principal component analysis (PCA) to determine the weight of the four usability components (satisfaction, transferability, effectiveness, and efficiency), which is used when obtaining the total usability score. Results show slightly different weights for the four components. This quantitative tool can be applied in different usability context in which multiple devices are involved. Usability specialists are encouraged to adjust the tool based on different usability scenarios. Study three investigates the impact of task complexity, user experience, and device order on the total system usability. Results show that the total usability score is not affected by task complexity, user experience or device order. However, lower physical task complexity leads to longer performance time and lower errors from the users. High experienced users have significantly lower errors made in tasks. The machine order also has divergent results. When the mini-lathe machine was used first, users had better transferability results but poorer performance outcomes as compared to when the drill press was used first.

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Threat perception is an important issue in today's world. As the line between hostile and non-hostile entities is blurred, it becomes more important for individuals to clearly distinguish between those who would present danger and those who would not. This series of experiments tested whether observers engaged in a dual-task paradigm perceived a greater amount of threat from target stimuli than they did when they were engaged in the threat task alone. The first experiment revealed that observers rated targets as more threatening when they were engaged in the additional task than when they only rated the targets themselves. Response time to the targets was also slower when a secondary task was present. This difference was more pronounced when the secondary task was presented via the auditory channel. Participants also rated overall workload higher when performing a secondary task, with the highest ratings being associated with the dual-task auditory condition. In the second experiment, the design crossed sensory modality with the presence or non-presence of threat. Inter-stimulus interval was also manipulated. The presence of threat was associated with faster response times, though when both tasks had threat components, response time was not the fastest. Additionally, when images came first in the stimulus pairs, observers were slower to respond to the first stimulus than when the sounds were presented first. Results supported the conclusion that additional task loading can affect the perception of threat. The modality of the additional task seems to also play a role in threat assessment performance. Results also led to the conclusion that threat-related visual stimuli are more challenging to process than threat-related auditory stimuli. Future research can now investigate how different types of tasks affect the threat perception task. Implications for better training of soldiers and for the design of automated systems are presented.

Using a single-subject multiple baseline design across participants, this study examined the impact of computer-assisted biofeedback to promote engagement of students diagnosed as having autism spectrum disorder. The study was conducted in a public school classroom setting. Specifically the on-task behavior during an individualized academic activity was investigated. Three 9-10 year old children participated in the study. In the baseline phase, data was collected on speed to engagement and percentage of time on-task during an academic activity. A 15-second momentary time sampling procedure was used for a 5 minute session each day of the week for a five week period to measure the participant's engagement. In the intervention phase, the participants completed a three to four minute computer-assisted biofeedback session prior to the academic activity and collection of data on engagement. In addition, data were collected on performance level of the academic activity. Data were also collected on educator and parent perception of generalization of self-regulation of behavior. The data suggest: (a) speed to engagement increased when using a computer-assisted biofeedback program for all participants; (b) time on-task improved over baseline conditions for all participants; (c) academic achievement was impacted by computer-assisted biofeedback for one participant; and (d) educators perceived a generalization of self-regulation of behavior, while parents did not indicate any generalization of self-regulation of behavior occurred in the home environment.