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Using healthy adult participants, seven measures of heart rate variability were obtained simultaneously from four devices in five behavioral conditions. Two devices were ECG-based and two utilized photoplethysmography. The 140 numerical values (measure, condition, device) are presented. The comparative operational reliability of the four devices was assessed, and it was found that the two ECG-base devices were more reliable than the photoplethysmographic devices. The interchangeability of devices was assessed by determining the between-device Limits of Agreement. Intraclass correlation coefficients were determined and used to calculate the standard error of measurement and the Minimal Detectable Difference. The Minimal Detectable Difference, MDD, quantifies the smallest statistically significant change in a measure and is therefore critical when HRV measures are used longitudinally to assess treatment response or disease progression.

Perfusion deficits in patients with mild traumatic brain injury (TBI) from a military population were characterized by dynamic susceptibility contrast perfusion imaging. Relative cerebral blood flow (rCBF) was calculated by a model-independent deconvolution approach from the tracer concentration curves following a bolus injection of gadolinium diethylenetriaminepentaacetate (Gd-DTPA) using both manually and automatically selected arterial input functions (AIFs). Linear regression analysis of the mean values of rCBF from selected regions of interest showed a very good agreement between the two approaches, with a regression coefficient of R = 0.88 and a slope of 0.88. The Bland–Altman plot also illustrated the good agreement between the two approaches, with a mean difference of 0.6 ± 12.4 mL/100 g/min. Voxelwise analysis of rCBF maps from both approaches demonstrated multiple clusters of decreased perfusion (p

To describe the initial neuroradiology findings in a cohort of military service members with primarily chronic mild traumatic brain injury (TBI) from blast by using an integrated magnetic resonance (MR) imaging protocol.This study was approved by the Walter Reed National Military Medical Center institutional review board and is compliant with HIPAA guidelines. All participants were military service members or dependents recruited between August 2009 and August 2014. There were 834 participants with a history of TBI and 42 participants in a control group without TBI (not explicitly age- and sex-matched). MR examinations were performed at 3 T primarily with three-dimensional volume imaging at smaller than 1 mm(3) voxels for the structural portion of the examination. The structural portion of this examination, including T1-weighted, T2-weighted, before and after contrast agent administrtion T2 fluid attenuation inversion recovery, and susceptibility-weighted images, was evaluated by neuroradiologists by using a modified version of the neuroradiology TBI common data elements (CDEs). Incident odds ratios (ORs) between the TBI participants and a comparison group without TBI were calculated.The 834 participants were diagnosed with predominantly chronic (mean, 1381 days; median, 888 days after injury) and mild (92% [768 of 834]) TBI. Of these participants, 84.2% (688 of 817) reported one or more blast-related incident and 63.0% (515 of 817) reported loss of consciousness at the time of injury. The presence of white matter T2-weighted hyperintense areas was the most common pathologic finding, observed in 51.8% (432 of 834; OR, 1.75) of TBI participants. Cerebral microhemorrhages were observed in a small percentage of participants (7.2% [60 of 834]; OR, 6.64) and showed increased incidence with TBI severity (P.001, moderate and severe vs mild). T2-weighted hyperintense areas and microhemorrhages did not collocate by visual inspection. Pituitary abnormalities were identified in a large proportion (29.0% [242 of 834]; OR, 16.8) of TBI participants.Blast-related injury and loss of consciousness is common in military TBI. Structural MR imaging demonstrates a high incidence of white matter T2-weighted hyperintense areas and pituitary abnormalities, with a low incidence of microhemorrhage in the chronic phase.

The Integrated Neuropsychiatric Assessment System is a portable platform for cognitive neurodynamic research and for clinical evaluations. It provides simultaneous acquisition of heart rate variability, quantitative electroencephalography and event related potentials during a neuropsychological assessment. The analysis protocol includes measures derived from dynamical systems theory including analysis of causal networks, event-dependent interregional synchronization and small world modeling.

A definitive diagnosis of mild traumatic brain injury (mTBI) is difficult due to the absence of biomarkers in standard clinical imaging. The brain is a complex network of interconnected neurons and subtle changes can modulate key networks of cognitive function. The resting state default mode network (DMN) has been shown to be sensitive to changes induced by pathology. This study seeks to determine whether quantitative measures of the DMN are sensitive in distinguishing mTBI subjects. Resting state functional magnetic resonance imaging data were obtained for healthy (n=12) and mTBI subjects (n=15). DMN maps were computed using dual-regression Independent Component Analysis (ICA). A goodness-of-fit (GOF) index was calculated to assess the degree of spatial specificity and sensitivity between healthy controls and mTBI subjects. DMN regions and neuropsychological assessments were examined to identify potential relationships. The resting state DMN maps indicate an increase in spatial coactivity in mTBI subjects within key regions of the DMN. Significant coactivity within the cerebellum and supplementary motor areas of mTBI subjects were also observed. This has not been previously reported in seed-based resting state network analysis. The GOF suggested the presence of high variability within the mTBI subject group, with poor sensitivity and specificity. The neuropsychological data showed correlations between areas of coactivity within the resting state network in the brain with a number of measures of emotion and cognitive functioning. The poor performance of the GOF highlights the key challenge associated with mTBI injury: the high variability in injury mechanisms and subsequent recovery. However, the quantification of the DMN using dual-regression ICA has potential to distinguish mTBI from healthy subjects, and provide information on the relationship of aspects of cognitive and emotional functioning with their potential neural correlates.

Reaching-to-grasp is essential for the performance of activities of daily living. Pathologies such as stroke, spinal cord injury, cerebral palsy, etc. limit individuals from being able to perform meaningful upper extremity movements, leading to a reduced quality of life. Robotic aided therapy is gaining prevalence as a rehabilitation tool because it can provide consistent and quantitative therapy. Such systems are dependent upon models to generate trajectories that dictate their movements. Time scaled polynomial techniques have been extensively used for robotic model development and trajectory generation. However, this approach is limited because it cannot support functional therapy tasks. This is largely due to the influence of cognitive complexity not completely considered with regards to the activity performed. We examine the influence of task cognitive complexity as manifested through the geometric properties of each object on the movement trajectories and kinematic dependent variables tasks through a motion analysis study using healthy subjects (N=8). We then compare the predicted results from several robotic trajectory models with the actual motion analysis data. Our results show that there are differences present, between the trajectory data and kinematic properties for each task, that are specific to the geometric properties of each object. In addition, the predicted results from the robotic trajectory models do not fully correlate with the actual movement information. This study is important as it will help provide some insight with regards to factors that need to be considered during the development of future robotic trajectory models and controllers for upper extremity functional rehabilitation tasks.

Mycoprotein is a meat alternative made from Fusarium venenatum. Mycoprotein, as well as other meat alternatives, are used to replace meat by health and environmental conscious consumers, however these products are not direct nutritional replacements for meat, and their health effects are not fully understood. Mycoprotein is high in protein, fibre and low in saturated fat, which make it an interesting meat alternative with potential benefits to health beyond meat displacement.\ud \ud The work in this thesis compares the effects of substituting a high red and processed meat diet with mycoprotein on gut and cardiometabolic health. The original aim was to investigate whether the putative mechanisms linking red and processed meat consumption to colorectal cancer risk might be attenuated by replacing meat with mycoprotein.\ud \ud In a dietary intervention study in healthy male adults, I show that substituting red and processed meat with mycoprotein positively influences gut health, by lowering intestinal genotoxicity, and by increasing the relative abundance of beneficial gut bacteria.\ud \ud In a secondary analysis of the dietary intervention study data, I also show that mycoprotein consumption may improve cardiometabolic disease risk related endpoints.\ud \ud Finally, using nationally representative data, I show that at a population level, displacement of meat with mycoprotein and other meat alternatives would influence nutritional intake and potentially nutritional status in the UK population. Notably, it would allow consumers to achieve the dietary guidelines around fibre but raises addressable concerns about certain nutrients.\ud \ud This work is timely, given the current focus on agricultural systems in the context of climate change. My data supports arguments around the potential healthfulness of choosing mycoprotein, which may help reduce uncertainty amongst potential consumers and thereby increase public confidence in mycoprotein as a replacement for meat. The findings may be of interest to the nutrition and public health community who have struggled to increase fibre consumption in the population and have concerns about the high meat content of the western diet. The findings may also be of interest to those working in the burgeoning meat alternative space. Mycoprotein has considerable potential as part of a healthier, greener food future.