Improving Multiscale Fuzzy Entropy Robustness in EEG-Based Alzheimer’s Disease Detection via Amplitude Transformation
Pasquale Arpaia, Maria Cacciapuoti, Andrea Cataldo, Sabatina Criscuolo, Egidio De Benedetto, Antonio Masciullo, Marisa Pesola, Raissa Schiavoni, Alessandro Bevilacqua · 2024
Read Improving Multiscale Fuzzy Entropy Robustness in EEG-Based Alzheimer’s Disease Detection via Amplitude Transformation by Pasquale Arpaia, Maria Cacciapuoti, Andrea Cataldo, Sabatina Criscuolo, Egidio De Benedetto, Antonio Masciullo, Marisa Pesola, Raissa Schiavoni, Alessandro Bevilacqua (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11645052.txt.
Description
Pasquale Arpaia and a team of co-authors improve a brain wave method for spotting Alzheimer disease in a 2024 paper. The method measures how complex brain signals are at many scales, but its results swing with signal size and with user chosen settings. That fragility has kept it from use as a steady diagnostic tool.
The team test a preprocessing step that reshapes signal amplitude before the complexity measure runs. Across many setting blends, the transformed signals gave far more consistent and stronger splits between patients and healthy people than raw signals. Clustering tests backed that gain. The authors present the step as a way to steady the method for early detection.
Catalog record
| CREATOR | Pasquale Arpaia, Maria Cacciapuoti, Andrea Cataldo, Sabatina Criscuolo, Egidio De Benedetto, Antonio Masciullo, Marisa Pesola, Raissa Schiavoni, Alessandro Bevilacqua |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 58 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |