scholarly journals A Novel Passive Method for the Assessment of Skin-Electrode Contact Impedance in Intraoperative Neurophysiological Monitoring Systems

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Eduardo Alonso ◽  
Romano Giannetti ◽  
Carlos Rodríguez-Morcillo ◽  
Javier Matanza ◽  
José Daniel Muñoz-Frías
Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1578
Author(s):  
Luisa Euler ◽  
Li Guo ◽  
Nils-Krister Persson

Textile electrodes, also called textrodes, for biosignal monitoring as well as electrostimulation are central for the emerging research field of smart textiles. However, so far, only the general suitability of textrodes for those areas was investigated, while the influencing parameters on the contact impedance related to the electrode construction and external factors remain rather unknown. Therefore, in this work, six different knitted electrodes, applied both wet and dry, were compared regarding the influence of specific knitting construction parameters on the three-electrode contact impedance measured on a human forearm. Additionally, the influence of applying pressure was investigated in a two-electrode setup using a water-based agar dummy. Further, simulation of an equivalent circuit was used for quantitative evaluation. Indications were found that the preferred electrode construction to achieve the lowest contact impedance includes a square shaped electrode, knitted with a high yarn density and, in the case of dry electrodes, an uneven surface topography consisting of loops, while in wet condition a smooth surface is favorable. Wet electrodes are showing a greatly reduced contact impedance and are therefore to be preferred over dry ones; however, opportunities are seen for improving the electrode performance of dry electrodes by applying pressure to the system, thereby avoiding disadvantages of wet electrodes with fluid administration, drying-out of the electrolyte, and discomfort arising from a “wet feeling”.


2021 ◽  
Author(s):  
Denise F Chen ◽  
Jon T Willie ◽  
David Cabrera ◽  
Katie L Bullinger ◽  
Ioannis Karakis

Abstract BACKGROUND AND IMPORTANCE Intraoperative neurophysiological monitoring of the motor pathways during epilepsy surgery is essential to safely achieve maximal resection of the epileptogenic zone. Motor evoked potential (MEP) recording is usually performed intermittently during resection using a handheld stimulator or continuously through an electrode array placed on the motor cortex. We present a novel variation of continuous MEP acquisition through previously implanted depth electrodes in the perirolandic cortex. CLINICAL PRESENTATION A 60-yr-old woman with a history of a left frontal meningioma (World Health Organization [WHO] grade II) treated with surgical resection and radiation presented with residual right hemiparesis and refractory epilepsy. Imaging demonstrated a perirolandic lesion with surrounding edema and mass effect in the prior surgical site, suspicious for radiation necrosis versus tumor recurrence. Presurgical electrocorticography (ECoG) with orthogonal, stereotactically implanted depth electrodes (stereoelectroencephalography [SEEG]) of the perirolandic cortex captured seizure onsets from the supplementary motor area (SMA) and primary motor cortex (PMC). The patient underwent a left frontal craniotomy for repeat resection and tissue diagnosis. Intraoperative ECoG and MEPs were obtained continuously with direct cortical stimulation through the indwelling SEEG electrodes in the PMC. Maximal resection was achieved with preservation of direct cortical MEPs and without deterioration of her baseline hemiparesis. Biopsy revealed radiation necrosis. At 30-mo follow-up, the patient had only rare seizures (Engel class IIB). CONCLUSION Intraoperative cortical MEP acquisition through implanted SEEG electrode arrays is a potentially safe and effective alternative approach to continuously monitor the motor pathways during the resection of a perirolandic epileptogenic lesion, without the need for surgical interruptions.


2018 ◽  
Vol 31 (3) ◽  
pp. 112-119 ◽  
Author(s):  
Tej D. Azad ◽  
Arjun V. Pendharkar ◽  
Viet Nguyen ◽  
James Pan ◽  
Ian D. Connolly ◽  
...  

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