Quantitative Electroencephalography in Hemodialysis: Scoping Review and Translational Framework
Meng-Hsun Tsai1, Cheng-Hsiung Chan1
1Department of Mechanical Engineering, National Yunlin University of Science and Technology, No. 123, Section 3, University Road, Douliu, Yunlin, 64002, Taiwan, 886 5-534-2601 ext 4102, 886 5-532-1719.
JMIR Biomedical Engineering
|July 31, 2026
Summary
Quantitative electroencephalography (qEEG) shows promise for monitoring brain changes in hemodialysis patients, but requires standardized protocols and validation for clinical use. Current evidence highlights qEEG
Area of Science:
- Neuroscience and Biomedical Engineering
- Nephrology and Dialysis Monitoring
- Quantitative Electroencephalography (qEEG) Applications
Background:
- End-stage kidney disease patients on hemodialysis often experience cognitive impairment and cerebral dysfunction.
- Intradialytic hemodynamic stress, including reduced cerebral blood flow and hypotension, is linked to neurological issues.
- Quantitative electroencephalography (qEEG) offers noninvasive cerebral activity assessment, but its role in dialysis monitoring is unclear due to implementation challenges.
Purpose of the Study:
- To synthesize evidence on qEEG alterations during the hemodialysis cycle.
- To evaluate technical requirements for translating qEEG features into cerebral monitoring systems for dialysis.
Main Methods:
- Conducted a scoping review of literature from January 2005 to February 2026 in major databases (PubMed/MEDLINE, Embase, IEEE Xplore).
- Included 62 studies after screening 554 records and assessing 70 full-text articles.
- Analyzed clinical findings and engineering aspects: hardware, signal processing, artifact mitigation, synchronization, and digital biomarker validation.
Main Results:
- Hemodialysis patients showed baseline spectral slowing (increased delta/theta, reduced alpha power).
- Intradialysis changes included ~10-15% cerebral blood flow reduction and dynamic qEEG shifts (e.g., alpha-delta ratio, slow wave activity).
- Implementation challenges involve electrical interference, motion artifacts, electrode instability, and lack of standardization; quality, artifact rejection, and synchronization are key for translation.
Conclusions:
- qEEG measures correlate with neurophysiological changes in hemodialysis patients but are insufficient for routine clinical use.
- Standardized protocols, robust artifact mitigation, synchronized multimodal monitoring, and validation studies are needed for future implementation.
- qEEG features are currently candidate digital biomarkers, not validated clinical tools.
