Why the study?
The emergence of affordable ECG and EEG sensors and ubiquitous mobile devices offers an opportunity to make medical signal analysis accessible for evaluating diseases in older adults.
Can a neural network-based method using low-cost ECG and EEG sensors accurately identify previously known conditions in older adults?
Cross-Sectional (n=14)
Yes
Can a neural network-based method using low-cost ECG and EEG sensors accurately identify previously known conditions in older adults?
Answers are grounded in this paper and cite their sources.
Low-cost ECG and EEG sensors combined with machine learning can identify age and institutional patterns in older adults, but larger cohorts are needed for accurate disease detection.
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Ponciano et al. (2020) conducted a cross-sectional in Various diseases (cardiovascular, osteoarticular, metabolic, etc.) (n=14). Machine learning analysis of ECG and EEG data was evaluated on Accuracy of identifying groups of diseases (e.g., cardiovascular diseases) using neural networks.
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