Benchmarking of the BITalino biomedical toolkit against an established gold standard

Autor: Margarida Reis, Diana Batista, Hugo Ferreira, Ana Fred, Carlos Santos Moreira, Hugo Silva
Rok vydání: 2018
Předmět:
electromyography
lcsh:Medical technology
Computer science
data acquisition
electrocardiography
electromyography data
post-processing methods
0206 medical engineering
Feature extraction
BioPac MP35 Student Lab Pro device
Health Informatics
02 engineering and technology
Article
030218 nuclear medicine & medical imaging
03 medical and health sciences
medical signal detection
0302 clinical medicine
Data acquisition
Health Information Management
Similarity (network science)
Segmentation
medical signal processing
Protocol (science)
Signal processing
business.industry
feature extraction
physiological signal acquisition
educational research purposes
electrodermal activity signals
Pattern recognition
Benchmarking
Gold standard (test)
020601 biomedical engineering
signal processing techniques
lcsh:R855-855.5
BITalino biomedical toolkit
electroencephalography data
physiology
root mean square error
mean square error methods
Artificial intelligence
methodical experimental protocol
business
electroencephalography
Zdroj: Healthcare Technology Letters
Healthcare Technology Letters (2019)
ISSN: 2053-3713
Popis: The low-cost multimodal platform BITalino is being increasingly used for educational and research purposes. However, there is still a lack of well-structured work comparing data acquired by this toolkit against a reference device, using established experimental protocols. This work intends to fill the said gap by benchmarking the performance of BITalino against the BioPac MP35 Student Lab Pro device. This work followed a methodical experimental protocol to acquire data from the two devices simultaneously. Four physiological signals were acquired: electrocardiography, electromyography, electrodermal activity and electroencephalography. Root mean square error and coefficient of determination were computed to analyse differences between BITalino and BioPac. Electrodermal activity signals were very similar for the two devices, even without applying any major signal processing techniques. For electrocardiography, a simple morphological comparison also revealed high similarity between devices, and this similarity increased after a common segmentation procedure was followed. Regarding electromyography and electroencephalography data, the approach consisted of comparing features extracted using common post-processing methods. The differences between BITalino and BioPac were again small. Overall, the results presented here show a close similarity between data acquired by the BITalino and by the reference device. This is an important validation step for all researchers working with this multimodal platform.
Databáze: OpenAIRE
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