Artifact: recording EEG in special care units

How to carry out and interpret EEG recordings in COVID-19 patients in ICU?

There are questions and challenges regarding neurologic complications in COVID-19 patients. EEG is a safe and efficient tool for the evaluation of brain function, even in the context of COVID-19. However, EEG technologists should not be put in danger if obtaining an EEG does not significantly advance diagnosis or change management in the patient. Not every neurologic problem stems from a primary brain injury: confusion, impaired consciousness that evolves to stupor and coma, and headaches are frequent in hypercapnic/hypoxic encephalopathies. In patients with chronic pulmonary disorders, acute symptomatic seizures have been reported in acute respiratory failure in 6%. The clinician should be aware of the various EEG patterns in hypercapnic/hypoxic and anoxic (post-cardiac arrest syndrome) encephalopathies as well as encephalitides. In this emerging pandemic of infectious disease, reduced EEG montages using single-use subdermal EEG needle electrodes may be used in comatose patients. A full 10-20 EEG complement of electrodes with an ECG derivation remains the standard. Under COVID-19 conditions, an expedited study that adequately screens for generalized status epilepticus, most types of regional status epilepticus, encephalopathy or sleep may serve for most clinical questions, using simplified montages may limit the risk of infection to EEG technologists. We recommend noting whether the patient is undergoing or has been placed prone, as well as noting the body and head position during the EEG recording (supine versus prone) to avoid overinterpretation of respiratory, head movement, electrode, muscle or other artifacts. There is slight elevation of intracranial pressure in the prone position. In non-comatose patients, the hyperventilation procedure should be avoided. At present, non-specific EEG findings and abnormalities should not be considered as being specific for COVID-19 related encephalopathy.

Artifact Mimicking Ictal Epileptiform Activity in EEG

Although the EEG is designed to record cerebral activity, it also frequently records activity from extracerebral sources, leading to artifact. Differentiating rhythmical artifact from true electrographic ictal activity remains a substantial challenge to even experienced electroencephalographers because the sources of artifact able to mimic ictal activity on EEG have continued to increase with the advent of technology. Knowledge of the characteristics of the polarity and physiologic electrical fields of the brain, as opposed to those generated by the eyes, heart, and muscles, allows the electroencephalographer to intuitively recognize noncerebrally generated waveforms. In this review, we provide practical guidelines for the EEG interpreter to correctly identify physiologic and nonphysiologic artifacts capable of mimicking electrographic seizures. In addition, we further elucidate the common pitfalls in artifact interpretation and the costly impact of epilepsy misdiagnosis due to artifact.

American Clinical Neurophysiology Society Guideline 6: Minimum Technical Standards for EEG Recording in Suspected Cerebral Death

This revision to the EEG Guidelines is an update incorporating current EEG technology and practice. The role of the EEG in making the determination of brain death is discussed as are suggested technical criteria for making the diagnosis of electrocerebral inactivity.

Train of four stimulation artifact mimicking a seizure during computerized automated ICU EEG monitoring

A 54-year-old man was admitted to the intensive care unit with an aneurysmal subarachnoid hemorrhage and subsequently underwent mechanical ventilation and received neuromuscular blocking drugs to control refractory elevated intracranial pressure. During quantitative EEG monitoring, an automated alert was triggered by the train of four peripheral nerve stimulation artifacts. Real-time feedback was made possible due to remote monitoring. This case illustrates how computerized, automated artificial intelligence algorithms can be used beyond typical seizure detection in the intensive care unit for remote monitoring to benefit patient care.

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ICU EEG provides an emerging opportunity for seizure detection (ictal) and interictal monitoring in the ICU setting.

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Artifacts are plentiful in the ICU EEG setting.

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Quantitative EEG (QEEG) with artificial neural-networks can be programmed to generate interesting artifacts that are not seizures, as the current example.

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Such artifacts while not being epileptiform in nature, may still have clinical context such as moving the patient, suctioning intubated patients, being disconnected to go for CT scan, or in this case checking neuromuscular stimulation for neuromuscular blockade level.

American Clinical Neurophysiology Society Guideline 6: Minimum Technical Standards for EEG Recording in Suspected Cerebral Death

This revision to the EEG Guidelines is an update incorporating current EEG technology and practice. The role of the EEG in making the determination of brain death is discussed as are suggested technical criteria for making the diagnosis of electrocerebral inactivity.

The Texting Rhythm: A Novel EEG Waveform Using Smartphones

INTRODUCTION

We report a unique EEG phenomenon in patients with paroxysmal neurological events undergoing video EEG monitoring.

METHODS

Two epilepsy centers analyzed the interictal scalp EEG in patients using personal electronic devices during epilepsy monitoring. The texting rhythm (TR) was defined as a reproducible, stimulus-evoked, generalized frontocentral monomorphic burst of 5-6 Hz theta consistently induced by active text messaging. An independent prospective and retrospective cohort was analyzed and compared from two sites in Florida and Illinois. We assessed age, gender, diagnosis, epilepsy classification, MRI, and EEG to compare patients with a TR. Analysis was performed with statistical significance set at P < 0.05.

RESULTS

We identified 24 of 98 evaluable patients with a TR in a prospective arm at one center and 7 of 31 patients in a retrospective arm at another totaling 31/129 (24.0%). The waveform prevalence was similar at both centers independent of location. TR was highly specific to active texting. A similar waveform during independent cognitive, speech or language, motor activation and audio cellular telephone use was absent (P < 0.0001). It appeared to be increased in patients with epilepsy in one cohort (P = 0.03) and generalized seizures in the other (P = 0.025). Age, gender, epilepsy type, MRI results, and EEG lateralization in patients with focal epileptic seizures did not bear a relationship to the presence of a TR in either arm of the study (P = NS).

CONCLUSIONS

The TR is a novel waveform time-locked to text messaging and associated with active use of smartphones. Electroencephalographers should be aware of the TR to separate it from an abnormality in patients undergoing video EEG monitoring. Larger sample sizes and additional research may help define the significance of this unique cognitive-visual-cognitive-motor network that is technology-related and task-specific with implications in communication research and transportation safety.

Evaluation of Dry Sensors for Neonatal EEG Recordings

PURPOSE

Neonatal seizures are a common neurologic diagnosis in neonatal intensive care units, occurring in approximately 14,000 newborns annually in the United States. Although the only reliable means of detecting and treating neonatal seizures is with an electroencephalography (EEG) recording, many neonates do not receive an EEG or experience delays in getting them. Barriers to obtaining neonatal EEGs include (1) lack of skilled EEG technologists to apply conventional wet electrodes to delicate neonatal skin, (2) poor signal quality because of improper skin preparation and artifact, and (3) extensive time needed to apply electrodes. Dry sensors have the potential to overcome these obstacles but have not previously been evaluated on neonates.

METHODS

Sequential and simultaneous recordings with wet and dry sensors were performed for 1 hour on 27 neonates from 35 to 42.5 weeks postmenstrual age. Recordings were analyzed for correlation and amplitude and were reviewed by neurophysiologists. Performance of dry sensors on simulated vernix was examined.

RESULTS

Analysis of dry and wet signals showed good time-domain correlation (reaching >0.8), given the nonsuperimposed sensor positions and similar power spectral density curves. Neurophysiologist reviews showed no statistically significant difference between dry and wet data on most clinically relevant EEG background and seizure patterns. There was no skin injury after 1 hour of dry sensor recordings. In contrast to wet electrodes, impedance and electrical artifact of dry sensors were largely unaffected by simulated vernix.

CONCLUSIONS

Dry sensors evaluated in this study have the potential to provide high-quality, timely EEG recordings on neonates with less risk of skin injury.

Respiratory artifact on EEG independent of the respirator

Recognizing EEG artifacts is important to correctly interpret and avoid unnecessary intervention. EEG artifacts from mechanical ventilation have been described as periodic, frontally maximal high amplitude waveforms, occurring at the same rate as the ventillator. Here, we describe a non-periodic respiratory artifact that was independent of the ventilator rate. The concomitant use of audio was helpful in identifying this artifact.