Home > Journals > Minerva Cardiology and Angiology > Past Issues > Articles online first > Minerva Cardiology and Angiology 2022 Jun 29



Publishing options
To subscribe
Submit an article
Recommend to your librarian


Publication history
Cite this article as


Original Article   

Minerva Cardiology and Angiology 2022 Jun 29

DOI: 10.23736/S2724-5683.22.06066-5


language: English

Neural interfaces to monitor Interventional Cardiologists’ mental work-load: GAME-ON SAGA

Antonella SCALA 1, Gianluca CAMPO 2, Matteo TEBALDI 3, Carlo PENZO 4, Carlo TUMSCITZ 5, Arif KHOKHAR 6, Andrea ERRIQUEZ 7, Marco RENZI 8, Luca TALEVI 8, Simone BISCAGLIA 1

1 Cardiovascular Institute, S. Anna University Hospital, Ferrara, Italy; 2 Unit of Cardiology, Department of Medical Sciences, S. Anna University Hospital, Ferrara, Italy; 3 Cardiologic Center, S. Anna University Hospital, Ferrara, Italy; 4 Public Hospital of Mirano, Mirano, Venice, Italy; 5 S. Anna University Hospital, Ferrara, Italy; 6 Unit of Interventional Cardiology, GVM Care & Research Maria Cecilia Hospital, Cotignola, Ravenna, Italy; 7 University of Ferrara, Ferrara, Italy; 8 Vibre Srl, Cesena, Forlì-Cesena, Italy


BACKGROUND: Interventional cardiologists’ mental workload may impact on their performance as well as on patients’ outcome. Nevertheless, little attention is paid to the monitoring and optimization of their mental status. Electroencephalogram (EEG)-based neural-interfaces can estimate mental fatigue and sleepiness through spectral analysis techniques and the amplitude of alpha waves is a widely validated indicator of mental engagement’s level.
METHODS: The present study aims to describe mental fatigue and sleepiness through variation of psychometrics and neurometrics during a work shift in a population of 7 interventional cardiologists. Neurometrics have been acquired at the beginning of the shift, before and after each procedure performed during 127 valid Alpha Attenuation Protocols (AAP), a practical test to quantify sleepiness measuring alpha power during 2 cycle of eye opening/closing protocol. We collected alpha waves’ power measures obtained during resting condition (AA Coefficient-eyes open (AAC-eo), AAC-eyes closed (AAC-ec) and AAC-mean), related to fatigue, and AAC-ec/AAC-eo (AAC-ratio), related to sleepiness.
RESULTS: From a two-months observation, the first interesting preliminary results emerged: i) AAC-mean showed an upward trend during the working day, reflecting an increase in mental fatigue (p=0.01); ii) population-level psychometrics trend confirms the same tendency described by neurometrics, possibly reflecting a reduced awareness of the operator of his/her actual mental status.
CONCLUSIONS: Developing a low cost and high feasibility device to monitor and analyse operator’s mental engagement level could be extremely appealing, considering the lack of data in literature for interventional disciplines and recent technology developments.

KEY WORDS: Workload; Stress, psychological; Percutaneous coronary intervention

top of page