Improving fNIRS Signal Quality Using Smoothing Filtering
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Biomedical signals are extremely difficult to analyze, mainly due to the non-stationary nature of these signals. Filtering does not always bring the desired results, because often the desired information is filtered out. In the case of EEG signals, smoothing filters gave very good results. In this paper, various types of smoothing filters for the analysis of infrared spectroscopy signals were compared.
| Original language | English |
|---|---|
| Title of host publication | 2023 Progress in Applied Electrical Engineering, PAEE 2023 |
| Publisher | IEEE |
| Publication date | 2023 |
| Pages | 1-8 |
| ISBN (Electronic) | 9798350316254 |
| DOIs | |
| Publication status | Published - 2023 |
| Event | 2023 Progress in Applied Electrical Engineering, PAEE 2023 - Koscielisko, Poland Duration: 26 Jun 2023 → 30 Jun 2023 |
Conference
| Conference | 2023 Progress in Applied Electrical Engineering, PAEE 2023 |
|---|---|
| Land | Poland |
| By | Koscielisko |
| Periode | 26/06/2023 → 30/06/2023 |
| Sponsor | Polish Society of Theoretical and Applied Electrical Engineering (PTETiS), The Institute of Electrical and Electronics Engineers (IEEE), Warsaw University of Technology |
Bibliographical note
Publisher Copyright:
© 2023 IEEE.
- brain signals, filtering, functional near-infrared spectroscopy, preprocessing, smoothing filtering
Research areas
ID: 383790128