Physical exertion undoubtedly influences physiological parameters. The aim of this paper is to propose a Machine Learning classifier able to evaluate the physical state of subjects monitored through a wearable device, by simply analysing their Blood Volume Pulse signals. Moreover, a Fatigue-Related Index is presented to quantify the physical well-being status. Results show that the Support Vector Machine classifier provides the best performance for detecting fatigue-induced stress, since it shows an accuracy of 97.50%. The obtained results prove that the proposed approach allows to support the assessment of the worker's well-being status, with the aim of improving the workload management in the context of Industry 4.0.

Learning classifiers for analysis of Blood Volume Pulse signals in IoT-enabled systems

Cosoli G.
Primo
;
Poli A.
Penultimo
;
Spinsante S.
Ultimo
Supervision
2021-01-01

Abstract

Physical exertion undoubtedly influences physiological parameters. The aim of this paper is to propose a Machine Learning classifier able to evaluate the physical state of subjects monitored through a wearable device, by simply analysing their Blood Volume Pulse signals. Moreover, a Fatigue-Related Index is presented to quantify the physical well-being status. Results show that the Support Vector Machine classifier provides the best performance for detecting fatigue-induced stress, since it shows an accuracy of 97.50%. The obtained results prove that the proposed approach allows to support the assessment of the worker's well-being status, with the aim of improving the workload management in the context of Industry 4.0.
978-1-6654-1980-2
File in questo prodotto:
Non ci sono file associati a questo prodotto.

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/11566/294226
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 12
  • ???jsp.display-item.citation.isi??? 7
social impact