The capability of monitoring user’s performance represents a crucial aspect to improve safety and efficiency of several human‐related activities. Human errors are indeed among the major causes of work‐related accidents. Assessing human factors (HFs) could prevent these accidents through specific neurophysiological signals’ evaluation but laboratory sensors require highly-specialized operators and imply a certain grade of invasiveness which could negatively interfere with the worker’s activity. On the contrary, consumer wearables are characterized by their ease of use and their comfortability, other than being cheaper compared to laboratory technologies. Therefore, wearable sensors could represent an ideal substitute for laboratory technologies for a real‐time assessment of human performances in ecological settings. The present study aimed at assessing the reliability and capability of consumer wearable devices (i.e., Empatica E4 and Muse 2) in discriminating specific mental states compared to laboratory equipment. The electrooculographic (EOG), electrodermal activity (EDA) and photoplethysmographic (PPG) signals were acquired from a group of 17 volunteers who took part to the experimental protocol in which different working scenarios were simulated to induce different levels of mental workload, stress, and emotional state. The results demonstrated that the parameters computed by the consumer wearable and laboratory sensors were positively and significantly correlated and exhibited the same evidences in terms of mental states discrimination.

Wearable technologies for mental workload, stress, and emotional state assessment during working‐like tasks: A comparison with laboratory technologies / Giorgi, A.; Ronca, V.; Vozzi, A.; Sciaraffa, N.; Di Florio, A.; Tamborra, L.; Simonetti, I.; Arico, P.; Di Flumeri, G.; Rossi, Dario; Borghini, G.. - In: SENSORS. - ISSN 1424-8220. - 21:7(2021), pp. 2332--. [10.3390/s21072332]

Wearable technologies for mental workload, stress, and emotional state assessment during working‐like tasks: A comparison with laboratory technologies

Rossi D.;
2021

Abstract

The capability of monitoring user’s performance represents a crucial aspect to improve safety and efficiency of several human‐related activities. Human errors are indeed among the major causes of work‐related accidents. Assessing human factors (HFs) could prevent these accidents through specific neurophysiological signals’ evaluation but laboratory sensors require highly-specialized operators and imply a certain grade of invasiveness which could negatively interfere with the worker’s activity. On the contrary, consumer wearables are characterized by their ease of use and their comfortability, other than being cheaper compared to laboratory technologies. Therefore, wearable sensors could represent an ideal substitute for laboratory technologies for a real‐time assessment of human performances in ecological settings. The present study aimed at assessing the reliability and capability of consumer wearable devices (i.e., Empatica E4 and Muse 2) in discriminating specific mental states compared to laboratory equipment. The electrooculographic (EOG), electrodermal activity (EDA) and photoplethysmographic (PPG) signals were acquired from a group of 17 volunteers who took part to the experimental protocol in which different working scenarios were simulated to induce different levels of mental workload, stress, and emotional state. The results demonstrated that the parameters computed by the consumer wearable and laboratory sensors were positively and significantly correlated and exhibited the same evidences in terms of mental states discrimination.
2021
Emotional state; Eye blinks rate; Heart rate; Mental workload; Skin conductance level; Stress; Wearable device; Heart Rate; Humans; Reproducibility of Results; Workload; Laboratories; Wearable Electronic Devices
Wearable technologies for mental workload, stress, and emotional state assessment during working‐like tasks: A comparison with laboratory technologies / Giorgi, A.; Ronca, V.; Vozzi, A.; Sciaraffa, N.; Di Florio, A.; Tamborra, L.; Simonetti, I.; Arico, P.; Di Flumeri, G.; Rossi, Dario; Borghini, G.. - In: SENSORS. - ISSN 1424-8220. - 21:7(2021), pp. 2332--. [10.3390/s21072332]
File in questo prodotto:
File Dimensione Formato  
sensors-21-02332.pdf

Open Access

Descrizione: Articolo principale
Tipologia: Versione dell'editore
Licenza: Creative commons
Dimensione 17.83 MB
Formato Adobe PDF
17.83 MB Adobe PDF Visualizza/Apri
sensors-21-02332_rid.pdf

Solo gestori archivio

Descrizione: File pdf in versione ridotta per invio LoginMIUR
Tipologia: Versione dell'editore
Licenza: DRM (Digital rights management) non definiti
Dimensione 434.32 kB
Formato Adobe PDF
434.32 kB Adobe PDF   Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11385/207378
Citazioni
  • Scopus 28
  • ???jsp.display-item.citation.isi??? 22
social impact