The effect of accelerometer location on the classification of single-site forearm mechanomyograms

<p>Abstract</p> <p>Background</p> <p>Recently, pattern recognition methods have been deployed in the classification of multiple activation states from mechanomyogram (MMG) signals for the purpose of controlling switching interfaces. Given the propagative properties of MMG signals, it has been suggested that MMG classification should be robust to changes in sensor placement. Nonetheless, this purported robustness remains speculative to date. This study sought to quantify the change in classification accuracy, if any, when a classifier trained with MMG signals from the muscle belly, is subsequently tested with MMG signals from a nearby location.</p> <p>Methods</p> <p>An arrangement of 5 accelerometers was attached to the flexor carpi radialis muscle of 12 able-bodied participants; a reference accelerometer was located over the muscle belly, two peripheral accelerometers were positioned along the muscle's transverse axis and two more were aligned to the muscle's longitudinal axis. Participants performed three classes of muscle activity: wrist flexion, wrist extension and semi-pronation. A collection of time, frequency and time-frequency features were considered and reduced by genetic feature selection. The classifier, trained using features from the reference accelerometer, was tested with signals from the longitudinally and transversally displaced accelerometers.</p> <p>Results</p> <p>Classification degradation due to accelerometer displacement was significant for all participants, and showed no consistent trend with the direction of displacement. Further, the displaced accelerometer signals showed task-dependent de-correlations with respect to the reference accelerometer.</p> <p>Conclusions</p> <p>These results indicate that MMG signal features vary with spatial location and that accelerometer displacements of only 1-2 cm cause sufficient feature drift to significantly diminish classification accuracy. This finding emphasizes the importance of consistent sensor placement between MMG classifier training and deployment for accurate control of switching interfaces.</p

Quantitative estimates of stimulation-induced perfusion response using two-photon fluorescence microscopy of cortical microvascular networks

Functional hyperemia, or the increase in focal perfusion elicited by neuronal activation, is one of the primary functions of the neurovascular unit and a hallmark of healthy brain functioning. While much is known about the hemodynamics on the millimeter to tenths of millimeter-scale accessible by MRI, there is a paucity of quantitative data on the micrometer-scale changes in perfusion in response to functional stimulation. We present a novel methodology for quantification of perfusion and intravascular flow across the 3D microvascular network in the rat somatosensory cortex using two-photon fluorescence microscopy (2PFM). For approximately 96% of responding microvessels in the forelimb representation of the primary somatosensory cortex, brief (~2 s) forepaw stimulation resulted in an increase of perfusion 20 ± 4% (mean ± sem). The perfusion levels associated with the remaining 4% of the responding microvessels decreased 10 ± 9% upon stimulation. Vessels irrigating regions of lower vascular density were found to exhibit higher flow (p b 0.02), supporting the notion that local vascular morphology and hemodynamics reflect the metabolic needs of the surrounding parenchyma. High dispersion (~77%) in perfusion levels suggests high spatial variation in tissue susceptibility to hypoxia. The current methodology enables quantification of absolute perfusion associated with individual vessels of the cortical microvascular bed and its changes in response to functional stimulation and thereby provides an important tool for studying the cellular mechanisms of functional hyperemia, the spatial specificity of perfusion response to functional stimulation, and, broadly, the micrometer-scale relationship between vascular morphology and function in health and disease

Amyloid-β-dependent compromise of microvascular structure and function in a model of Alzheimer's disease

The majority of patients with Alzheimer’s disease have cerebral amyloid angiopathy, thus showing deposition of amyloid-β peptides in the walls of leptomeningeal and cortical arterioles. These deposits are believed to result from impaired clearance of parenchymal amyloid-β peptides. In the current work, we examined the changes in cortical microvascular structure and function in situ in TgCRND8, a transgenic mouse model of Alzheimer’s disease. In contrast to venules, cortical arterioles were shown to increase in tortuosity and decrease in calibre with amyloid-β peptide accumulation. These structural changes were accompanied by progressive functional compromise, reflected in higher dispersion of microvascular network transit times, elongation of the transit times, and impaired microvascular reactivity to hypercapnia in the transgenic mice. Moreover, inhibition of amyloid-β peptide oligomerization and fibrillization via post-weaning administration of scyllo-inositol, a naturally occurring stereoisomer of myo-inositol, rescued both structural and functional impairment of the cortical microvasculature in this Alzheimer’s disease model. These results demonstrate that microvascular impairment is directly correlated with amyloid-β accumulation and highlight the importance of targeting cerebrovascular amyloid angiopathy clearance for effective diagnosis, monitoring of disease progression and treatment of Alzheimer’s disease