IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
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IEEE Trans Neural Syst Rehabil Eng · Oct 2017
Quasi-Periodicities Detection Using Phase-Rectified Signal Averaging in EEG Signals as a Depth of Anesthesia Monitor.
Phase-rectified signal averaging (PRSA) has been known to be a useful method to detect periodicities in non-stationary biological signals. Determination of quasi-periodicities in electroencephalogram (EEG) is a candidate for quantifying the changes in the depth of anesthesia (DOA). In this paper, DOA monitoring capacity of periodicities detected using PRSA was quantified by assessing EEG signals collected from 56 patients during surgery. ⋯ There is a larger mean AUC and correlation coefficient of quasi-periodicities compared with SampEn, DFA, and PE using expert assessment of conscious level and bispectral index as the gold standard, respectively. Quasi-periodicities detected using PRSA in EEG signals are a powerful monitor of DOA and perform more accurate and robust results compared with SampEn, DFA, and PE. The results do provide a valuable reference to researchers in the field of clinical applications.
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IEEE Trans Neural Syst Rehabil Eng · Oct 2017
Epidural Stimulation of Rat Spinal Cord at Lumbosacral Segment Using a Surface Electrode: A Computer Simulation Study.
Clinical research indicates that the epidural spinal cord stimulation (ESCS) at lumbosacral segment has shown potential for promoting locomotor recovery in patients with incomplete spinal cord injury. However, the underlying neural mechanism needs to be determined by animal experiments. In order to refine experimental protocols, we used a finite element simulation to investigate the activation of nerve fibers in a rat spinal cord model. ⋯ The spikes were initiated at sites along the nerve fibers depending on which component was closest to the cathode among the longitudinal part of the fiber, its entrance into spinal cord, or strong bending at the entry. Our simulation results show good agreement with the previous findings from animal studies. It is concluded that the computational ESCS model is a valuable tool to obtain a better insight into the immediately evoked electrophysiological phenomena in animal models, and provides further guidelines for conducting animal experiments to enhance the exploration of basic neural mechanisms.
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IEEE Trans Neural Syst Rehabil Eng · Sep 2017
Combining Improved Gray-Level Co-Occurrence Matrix With High Density Grid for Myoelectric Control Robustness to Electrode Shift.
Pattern recognition-based myoelectric control is greatly influenced by electrode shift, which is inevitable during prosthesis donning and doffing. This study used gray-level co-occurrence matrix (GLCM) to represent the spatial distribution among high density (HD) electrodes and improved its calculation based on the using condition of myoelectric system, proposing a new feature, iGLCM, to improve the robustness of the system. The effects of its two parameters, quantization level and input data, were first evaluated and it was found that improved discrete Fourier transform (iDFT) performed better than the other three (time-domain, autoregressive, root mean square) as the input data of iGLCM, and increasing quantization level did not significantly decrease the error rate of iGLCM when it was above 8. ⋯ Combined with the small interelectrode distance of HD electrodes, it provided a way to control the effect of perpendicular shifts fundamentally, which were the main source of performance degradation. Finally, the analysis of feature space revealed that the robustness was improved by discarding information sensitivity to shift and keeping as much as useful information. This study highlighted the importance of HD electrodes in robust myoelectric control, and the outcome would help the design of robust control system based on pattern recognition and promote its application in real-world condition.
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IEEE Trans Neural Syst Rehabil Eng · Aug 2017
Use of Virtual Reality Feedback for Patients with Chronic Neck Pain and Kinesiophobia.
This study examined how individuals with and without neck pain performed exercises under the influence of altered visual feedback in virtual reality. Chronic neck pain (n=9) and asymptomatic (n=10) individuals were recruited for this cross-sectional study. Participants performed head rotations while receiving programmatically manipulated visual feedback from a head-mounted virtual reality display. ⋯ The head rotation angle increased 4.29° for every 0.1 decrease in gain. On average, chronic pain individuals reported that neck rotation was feasible for 84% of the unity gain trials, 66% of the individual just-noticeable difference trials, and 50% of the "nudged" just-noticeable difference trials. This research demonstrated that virtual reality may be useful for promoting the desired outcome of increased range of motion in neck rehabilitation exercises by altering visual feedback.
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IEEE Trans Neural Syst Rehabil Eng · Nov 2016
Tone Entropy Analysis of Augmented Information Effects on Toe-Ground Clearance When Walking.
Minimum toe clearance (MTC) is an event approximately mid-swing in the walking cycle that is critical for preventing unintended foot contact with surface irregularities ("tripping"). Treadmill-based gait training for older adults was undertaken using real-time augmented information to increase foot-ground clearance at MTC (MTC height). Ten young (Y) (Age: 23±2 year) and ten older (O) (Age: 76±9 year) participants undertook 10 min preferred speed treadmill walking (baseline) followed by 20 min with MTC height information (training) and 10 min without augmented information (retention). ⋯ T and E measures of MTC height considered separately discriminated the age groups only in baseline but distinctive "clusters" were observed in tone versus entropy plots indicating characteristically different patterns of MTC adjustment over step cycles. Treadmill training with MTC height augmented information is a practical intervention for reducing tripping in older people and others with gait impairments. T-E analysis is useful for identifying characteristics of lower limb control with ageing that have not been previously recognized in studies employing traditional statistical analysis of the MTC event.