RESUMO
Focal vibratory stimulation (FVS) and neuromuscular electrical stimulation (NMES) are promising technologies for sensory rehabilitation after stroke. However, the differences between these techniques in immediate neuromodulatory effects on the poststroke cortex are not yet fully understood. In this research, cortical responses in persons with chronic stroke (n = 15) and unimpaired controls (n = 15) were measured by whole-brain electroencephalography (EEG) when FVS and NMES at different intensities were applied transcutaneously to the forearm muscles. Both FVS and sensory-level NMES induced alpha and beta oscillations in the sensorimotor cortex after stroke, significantly exceeding baseline levels (p < 0.05). These oscillations exhibited bilateral sensory deficiency, early adaptation, and contralesional compensation compared to the control group. FVS resulted in a significantly faster P300 response (p < 0.05) and higher theta oscillation (p < 0.05) compared to NMES. The beta desynchronization over the contralesional frontal-parietal area remained during NMES (p > 0.05), but it was significantly weakened during FVS (p < 0.05) after stroke. The results indicated that both FVS and NMES effectively activated the sensorimotor cortex after stroke. However, FVS was particularly effective in eliciting transient involuntary attention, while NMES primarily fostered the cortical responses of the targeted muscles in the contralesional motor cortex.
RESUMO
Recently, to easily extend the helical field-of-view (FOV), the segmented helical computed tomography (SHCT) method was proposed, as well as the corresponding generalized backprojection filtration (G-BPF) type algorithm. Similar to the geometric relationship between helical and circular CT, SHCT just becomes full-scan multiple source-translation CT (F-mSTCT) when the pitch is zero and the number of scan cycles is one. The strategy of G-BPF follows the idea of the generalized Feldkamp approximate cone-beam algorithm for helical CT, i.e., using the F-mSTCT cone-beam BPF algorithm to approximately perform reconstruction for SHCT. The image quality is limited by the pitch size, which implies that satisfactory quality could only be obtained under the conditions of small pitches. To extend the analytical reconstruction for SHCT, an effective single-slice rebinning (SSRB) method for SHCT is investigated here. Transforming the SHCT cone-beam reconstruction into the virtual F-mSTCT fan-beam stack reconstruction task with low computational complexity, and then some techniques are developed to address the challenges involved. By using the basic BPF reconstruction with derivating along the detector (D-BPF), our experiments demonstrate that SSRB has fewer interlayer artifacts, higher z-resolution, more uniform in-plane resolution, and higher reconstruction efficiency compared to G-BPF. SSRB could promote the effective application of deep learning in SHCT reconstruction.
