Because of the high mortality rate after rupture of small abdominal aortic aneurysms (AAAs), surveillance is recommended to detect aneurysm expansion; however, the effects of clinical risk factors on long-term patterns of AAA expansion are poorly characterized.
Abstract Purpose: The common responses to pressure sensor saturation are extreme: either discarding of data, or wholesale alteration of experimental protocol. Here, we test four simplistic strategies for restoring missing data due to sensor saturation, avoiding such drastic measures. Methods: We tested these algorithms on 62 pressure maps collected from 42 individuals (20 M/22 F, 54.1?±?26.2 years, 1.7?±?0.1?m, 71.9?±?17.8?kg) under a variety of seating conditions. These strategies were tested via a cross-validation design, censoring the maximum pressure value in the datasets and measuring prediction error. Results: The four strategies showed various prediction error rates: ??=?0.43?±?0.14 (simple substitution), ??=?0.16?±?0.21 (scaled substitution), ??=?0.19?±?0.21 (feature extraction), and ??=?0.24?±?0.32 (extrapolation by non-linear modeling). Conclusion: For single-sensor saturation, it may be possible to restore missing data using simple techniques. Implications for Rehabilitation We present a method for imputing missing data from pressure sensor arrays. The implications for rehabilitation are as follows. Improved flexibility in design of protocols concerning interfacial pressure measurement. Restoration of missing data from existing datasets. Reduction in recruitment burden for future studies. Reduction in exposure risk to study participants.
One of the hottest topics in rehabilitation robotics is that of proper control of prosthetic devices. Despite decades of research, the state of the art is dramatically behind the expectations. To shed light on this issue, in June, 2013 the first international workshop on Present and future of non-invasive peripheral nervous system (PNS)-Machine Interfaces (MI; PMI) was convened, hosted by the International Conference on Rehabilitation Robotics. The keyword PMI has been selected to denote human-machine interfaces targeted at the limb-deficient, mainly upper-limb amputees, dealing with signals gathered from the PNS in a non-invasive way, that is, from the surface of the residuum. The workshop was intended to provide an overview of the state of the art and future perspectives of such interfaces; this paper represents is a collection of opinions expressed by each and every researcher/group involved in it.
Background:At the age of 18 years, jazz guitarist Django Reinhardt (1910-1953) sustained significant burns to his left-hand ring and little fingers; yet, subsequently, he relearned to play and achieved international fame, despite his injuries.Case description and methods:Archive film footage and novel motion analysis software were used to compare movements of Django's fretting hand with that of six other guitarists of the same genre.Findings and outcomes:Django employed greater abduction of index and middle fingers (-9.11 ± 6.52° vs -5.78 ± 2.41°; p < 0.001) and more parallel alignment of fingers to the guitar neck (157.7 ± 3.37° vs 150.59 ± 2.67°; p < 0.001) compared to controls.Conclusion:In response to debilitating hand injury, Django developed quantifiable compensatory adaptation of function of his remaining functional fingers by developing an original playing technique.Clinical relevanceHand function following injury may be optimized by maximizing latent degrees of freedom in remaining digits, rather than through extensive surgical reconstruction or complex prostheses. Further study of adaptation strategies may inform prosthesis design.
Understanding interactions between cognitive and motor performance is an important theoretical and practical aim of motor neuroscience. Toward this aim, we invited university students to move one hand back and forth at a self-paced rate either in silence or while overtly generating words from semantic categories. The same participants also generated words without movement. Word generation affected manual performance but manual performance did not affect word generation. Only the timing, but not the spatial features, of the hand movements were influenced by word generation. The simplicity of our procedure argues for its future use, both for theoretical and practical purposes.
Repetitive reaching movements to a fixed target can be generally characterized by bell-shaped velocity profiles and sigmoidal trajectories with variable morphologies across multiple repetitions. A neuromuscular correspondence of these kinematic variations has thus far eluded electromyographic (EMG) analysis. We recorded EMG and elbow kinematics from fourteen healthy individuals performing repetitive, self-paced, isolated elbow flexions, with their arms supported against gravity. The global kinematic pattern of each flexion was classified as either sigmoidal (S) or non-sigmoidal (NS), based on goodness of fit with analytical curves. Ten of the fourteen subjects generated an approximately equal number of S and NS types (383 movement cycles). Trajectories of the other four subjects were not classifiable or did not vary sufficiently and were excluded from subsequent analysis. A post hoc predictor of trajectory type was derived by testing linear support vector machines trained with a strategically selected 3-feature sub-space of the early phase of enveloped biceps EMG during a leave-one-out cross-validation paradigm. Results showed that EMG features predicted kinematic morphology with sensitivity and specificity both exceeding 80%. The high predictive accuracy suggests neuromotor signals coding for subtle variations in elbow kinematics during self-paced, unloaded motions, can be deciphered from the biceps EMG.
This study aims to address shortcomings of the relative phase analysis, a widely used method for assessment of coupling among joints of the lower limb. Goniometric data from 15 individuals with spastic diplegic cerebral palsy were recorded from the hip and knee joints during ambulation on a flat surface, and from a single healthy individual with no known motor impairment, over at least 10 gait cycles. The minimum relative phase (MRP) revealed substantial disparity in the timing and severity of the instance of maximum coupling, depending on which reference frame was selected: MRP(knee-hip) differed from MRP(hip-knee) by 16.1±14% of gait cycle and 50.6±77% difference in scale. Additionally, several relative phase portraits contained discontinuities which may contribute to error in phase feature extraction. These vagaries can be attributed to the predication of relative phase analysis on a transformation into the velocity-position phase plane, and the extraction of phase angle by the discontinuous arc-tangent operator. Here, an alternative phase analysis is proposed, wherein kinematic data is transformed into a profile of joint coupling across the entire gait cycle. By comparing joint velocities directly via a standard linear regression in the velocity-velocity phase plane, this regressed phase analysis provides several key advantages over relative phase analysis including continuity, commutativity between reference frames, and generalizability to many-joint systems.
While surface electromyography (SEMG) can accurately register electrical activity of muscles during gait, there are no methods to estimate muscular force non-invasively. To better understand the mechanical behavior of muscle, we evaluated surface muscle pressure (SMP) in conjunction with SEMG. Changes in anterior thigh radial pressure during isometric contractions and gait were registered by pressure sensors on the limb. During isometric knee extensions by a single subject, SMP waveforms correlated well with SEMG (r=0.97), and SEMG onsets preceded those of SMP by 35-40 ms. SMP and SEMG signals were simultaneously recorded from the quadriceps of 10 healthy subjects during gait at speeds of 0.4, 0.8, 1.1, 1.4 and 2.2m/s. Muscle activity onset and cessation times were objectively determined for both modalities, and results showed high intra-class correlations. SMP waveforms were highly consistent from stride to stride, while SEMG waveforms varied widely. SEMG waveforms were typically brief, while SMP waveforms tended to be biphasic and outlasted the SEMG by approximately 40% of gait cycle at all speeds. These results are consistent with mechanical models of muscle, and demonstrate the use of SMP to estimate the timing of knee extensor muscle stiffness during gait.
Ductal carcinoma in situ (DCIS) of the breast is a non-invasive tumor in which cells proliferate abnormally, but remain confined within a duct. Although four distinguishable DCIS morphologies are recognized, the mechanisms that generate these different morphological classes remain unclear, and consequently the prognostic strength of DCIS classification is not strong. To improve the understanding of the relation between morphology and time course, we have developed a 2D in silico particle model of the growth of DCIS within a single breast duct. This model considers mechanical effects such as cellular adhesion and intra-ductal pressure, and biological features including proliferation, apoptosis, necrosis, and cell polarity. Using this model, we find that different regions of parameter space generate distinct morphological subtypes of DCIS, so elucidating the relation between morphology and time course. Furthermore, we find that tumors with similar architectures may in fact be produced through different mechanisms, and we propose future work to further disentangle the mechanisms involved in DCIS progression.
Reaching tasks are considered well-executed if they appear "smooth," a quality that is typically quantified by its opposite, jerk, the rate of change of acceleration. While jerk is a theoretically sound measure, its application to spastic individuals sometimes yields counter-intuitive results, and does not reveal motor impairment across the workspace. To more generally quantify spontaneous accelerative transients (SATs) within a movement, a pseudo-wavelet transform was devised that iteratively compared angular trajectories to a series of straight-line approximants. Cumulative linear fit errors were expressed in terms of flexion angle, yielding an SAT map of the entire motion. To compare SAT maps with traditional smoothness measures, two scalar indices were extracted from them: residual excursion deviation (RED), representing the integral over Deltatheta and the ratio of peak error to mean error (PEME) on the map. Fifteen subjects, including five subjects with chronic stroke performed elbow flexions throughout their entire ranges of motion, Deltatheta, at a comfortable pace with their arms supported in the transverse plane. Maps revealed that stroke subjects were significantly less coordinated than controls, as measured both by RED: 8.0+/-2.9 x 10(-3) versus 3.1+/-0.8 x 10(-3) and PEME: 6.6+/-0.9 versus 12.1+/-1.9, both P<0.001. Comparable jerk metrics, including integrated average jerk, did not report a significant performance deficit at the P<0.05 level. Map metrics for all subjects were independent of average velocity (correlation with theta : rho0.31), but jerk-based metrics for stroke subjects were spuriously co-variant with velocity rho=0.85, which may relate to the significantly higher mean arrest period ratio in stroke subjects (0.26+/-0.19 versus 0.09+/-0.08, P<0.001). We conclude that SAT maps provide reliable information on regional movement impairments at a wide range of proficiency levels.
Inter-limb learning transfer (ILT) between the upper-limbs has been well documented, but no corresponding study of the lower limbs has been done. We investigated ILT in the lower limbs of subjects who learned to move a cursor toward targets within 800 ms using ankle movements: plantar/dorsi-flexion and inversion/eversion. Twenty-two healthy right-dominant subjects were divided into two groups: half performed the tasks first using the right foot (group RL), and the other half performed it first with the left foot (group LR). Targets appeared on a computer screen at head-height while subjects were seated with one foot on a goniometric ankle platform. Subjects were required to move the cursor toward one of three randomly appearing targets under two conditions: (1) neutral or no visual motor rotation, and (2) with a 30 degrees visuo-motor rotation. Performance was quantified by computing the z-score for direction and position errors for each subject and ILT was assessed by comparing group performances for each foot. Results demonstrated that group LR but not group RL experienced significant ILT of directional as well as positional information in both tasks in a manner reflective of the distinctly different functional roles played by the upper and lower limbs.
We tested the possibility that exogenous electrical activity from a piezoelectric substrate could influence neuronal structure in cultured spinal cord neurons. Oscillating electrical fields were delivered to rat neurons via substrates consisting of poly(vinylidene fluoride) film, both in its piezoelectric (PZ) and non-piezoelectric (PV) forms. To induce oscillating electrical fields at the film surfaces, a 50 Hz mechanical vibration was applied. After 4 days of mechano-electrical stimulation, neuronal densities were increased by 115% and neurons grew 79% more neurites, with more than double the branch points, compared with neurons grown on non-stimulated PZ films (p < 0.001). The effects were due to electrical field, because vibration applied to non-PZ films did not increase neurite growth. We conclude that the oscillating electric fields produced from PZ polymer substrates can induce plastic changes in neurons of the central nervous system and herein we show its influence on neurite growth and branching.
Recent work has proposed the reformulation of smoothness measures derived from standard integrated squared jerk, as a function of position, not time. However, its promulgation was in the context of monotonic excursion data extracted from single degree-of-freedom (DOF) movements; the result was a formulation of a phase smoothness measure with limited generalizability. Here, we present a complete methodology for implementing the phase smoothness measure in arbitrary datasets, i.e. for multi-DOF movements with no assumptions of monotonicity in the kinematic profile. Additional suggestions are made for best practices.
To improve the characterization of motor impairment, we compared the sensitivities of a phase plane metric with temporal domain measures derived from integrated squared jerk (ISJ). Five subjects with stroke and a cohort of 21 neurologically intact volunteers performed self-paced, isolated elbow flexions. Analysis of angular trajectories from the stroke group revealed that temporal domain metrics failed to detect a performance deficit at the p < .05 level, while the phase plane metric did resolve a deficit (p < .01). When applied to a subset of movements with arrest periods, the phase measure also uniquely identified impairment (Wilcoxon rank-sum test, p < .001). Finally, when tested on a data-driven model, the phase measure, but not temporal metrics, increased monotonically with the severity of trajectory distortions. We conclude that motion smoothness can be accurately measured in the phase plane.
The human prefrontal cortex (PFC), a mastermind of the brain, is one of the last brain regions to mature. To investigate the role of epigenetics in the development of PFC, we examined DNA methylation in ?14,500 genes at ?27,000 CpG loci focused on 5 promoter regions in 108 subjects range in age from fetal to elderly. DNA methylation in the PFC shows unique temporal patterns across life. The fastest changes occur during the prenatal period, slow down markedly after birth and continue to slow further with aging. At the genome level, the transition from fetal to postnatal life is typified by a reversal of direction, from demethylation prenatally to increased methylation postnatally. DNA methylation is strongly associated with genotypic variants and correlates with expression of a subset of genes, including genes involved in brain development and in de novo DNA methylation. Our results indicate that promoter DNA methylation in the human PFC is a highly dynamic process modified by genetic variance and regulating gene transcription. Additional discovery is made possible with a stand-alone application, BrainCloudMethyl.
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