Sensitivity analysis of marine Controlled-Source Electromagnetic data

Electromagnetic sounding methods represent one of the few geophysical techniques that can provide information about the state and the properties of deep continental crust and upper mantle. In particular, marine Controlled-Source Electromagnetic (mCSEM) method is being applied to offshore hydrocarbon exploration and providing encouraging results, as it can complement the information obtained from seismic elaborations, mainly the position of the elastic discontinuities, with a map of electrical conductivity, the principal "discriminator" between conductive water-bearing rocks and non-conductive hydrocarbon accumulations. The processing of mCSEM data can be problematic due to the non-uniqueness of the solution, the environmental and equipment noise, and the high computational power required when dealing with 3D inversion. This paper proposes a simplified procedure to study and rank the sensitivity of mCSEM in a canonical 1D scenario, with a single resistive anomaly embedded in a homogeneous background. We analyze the sensitivity of the data with respect to the most important test parameters, namely the frequency, target depth, thickness, and resistivity. In addition, this procedure is also utilized to validate the so-called T-equivalence theorem. The results of this study could assist the interpreter to highlight the reliability of the inverted parameters in a complex inversion environment

Upper Body-Based Power Wheelchair Control Interface for Individuals with Tetraplegia

Many power wheelchair control interfaces are not sufficient for individuals with severely limited upper limb mobility. The majority of controllers that do not rely on coordinated arm and hand movements provide users a limited vocabulary of commands and often do not take advantage of the user's residual motion. We developed a body-machine interface (BMI) that leverages the flexibility and customizability of redundant control by using high dimensional changes in shoulder kinematics to generate proportional control commands for a power wheelchair. In this study, three individuals with cervical spinal cord injuries were able to control a power wheelchair safely and accurately using only small shoulder movements. With the BMI, participants were able to achieve their desired trajectories and, after five sessions driving, were able to achieve smoothness that was similar to the smoothness with their current joystick. All participants were twice as slow using the BMI however improved with practice. Importantly, users were able to generalize training controlling a computer to driving a power wheelchair, and employed similar strategies when controlling both devices. Overall, this work suggests that the BMI can be an effective wheelchair control interface for individuals with high-level spinal cord injuries who have limited arm and hand control

Movement distributions of stroke survivors exhibit distinct patterns that evolve with training

BACKGROUND: While clinical assessments provide tools for characterizing abilities in motor-impaired individuals, concerns remain over their repeatability and reliability. Typical robot-assisted training studies focus on repetition of prescribed actions, yet such movement data provides an incomplete account of abnormal patterns of coordination. Recent studies have shown positive effects from self-directed movement, yet such a training paradigm leads to challenges in how to quantify and interpret performance. METHODS: With data from chronic stroke survivors (n = 10, practicing for 3 days), we tabulated histograms of the displacement, velocity, and acceleration for planar motion, and examined whether modeling of distributions could reveal changes in available movement patterns. We contrasted these results with scalar measures of the range of motion. We performed linear discriminant analysis (LDA) classification with selected histogram features to compare predictions versus actual subject identifiers. As a basis of comparison, we also present an age-matched control group of healthy individuals (n = 10, practicing for 1 day). RESULTS: Analysis of range of motion did not show improvement from self-directed movement training for the stroke survivors in this study. However, examination of distributions indicated that increased multivariate normal components were needed to accurately model the patterns of movement after training. Stroke survivors generally exhibited more complex distributions of motor exploration compared to the age-matched control group. Classification using linear discriminant analysis revealed that movement patterns were identifiable by individual. Individuals in the control group were more difficult to identify using classification methods, consistent with the idea that motor deficits contribute significantly to unique movement signatures. CONCLUSIONS: Distribution analysis revealed individual patterns of abnormal coordination in stroke survivors and changes in these patterns with training. These findings were not apparent from scalar metrics that simply summarized properties of motor exploration. Our results suggest new methods for characterizing motor capabilities, and could provide the basis for powerful tools for designing customized therapy