Szczegóły publikacji
Opis bibliograficzny
Measurement uncertainty for biological signals / Andrzej KOT, Agata NAWROCKA // W: 2025 26th International Carpathian Control Conference (ICCC) [Dokument elektroniczny] : 19-21 May 2025, Starý Smokovec, Slovakia : proceedings. — Wersja do Windows. — Dane tekstowe. — Piscataway : IEEE, cop. 2025. — Dod. ISBN: 979-8-3315-0126-6, 979-8-3315-0128-0. — e-ISBN: 979-8-3315-0127-3. — S. [1-5]. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. [5], Abstr. — Publikacja dostępna online od: 2025-06-10
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 160611 |
|---|---|
| Data dodania do BaDAP | 2025-06-24 |
| Tekst źródłowy | URL |
| DOI | 10.1109/ICCC65605.2025.11022854 |
| Rok publikacji | 2025 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Institute of Electrical and Electronics Engineers (IEEE) |
Abstract
The measurement of biological signals, such as electrophysiological signals (ECG, EEG) or biochemical signals, is associated with many sources of uncertainty that can significantly affect the accuracy and reliability of the results. The paper emphasizes the role of uncertainty reduction methods, including using digital filters, advanced signal analysis, and mathematical models for data interpretation. An important aspect is the standardization of measurement procedures, which allows for better comparability of results between different studies. The paper suggests that integrating artificial intelligence and machine learning techniques can help better model and compensate for real-time uncertainty. It also emphasizes the importance of documenting and quantifying uncertainty in research reports, which is crucial for the further development of bioengineering and medicine.
