Comparison analysis between standard polysomnographic data and in-ear-electroencephalography signals: a preliminary study.

Journal: Sleep advances : a journal of the Sleep Research Society
Published Date: Nov 29, 2024

Abstract

STUDY OBJECTIVES: Polysomnography (PSG) currently serves as the benchmark for evaluating sleep disorders. Its discomfort makes long-term monitoring unfeasible, leading to bias in sleep quality assessment. Hence, less invasive, cost-effective, and portable alternatives need to be explored. One promising contender is the in-ear-electroencephalography (EEG) sensor. This study aims to establish a methodology to assess the similarity between the single-channel in-ear-EEG and standard PSG derivations.

Authors

  • Gianpaolo Palo
    Department of Innovative Technologies, Institute of Digital Technologies for Personalized Healthcare (MeDiTech), University of Applied Sciences and Arts of Southern Switzerland, Lugano, Switzerland.
  • Luigi Fiorillo
    Department of Innovative Technologies, Institute of Digital Technologies for Personalized Healthcare (MeDiTech), University of Applied Sciences and Arts of Southern Switzerland, Lugano, Switzerland.
  • Giuliana Monachino
    Department of Innovative Technologies, Institute of Digital Technologies for Personalized Healthcare (MeDiTech), University of Applied Sciences and Arts of Southern Switzerland, Lugano, Switzerland.
  • Michal Bechny
    Department of Innovative Technologies, Institute of Digital Technologies for Personalized Healthcare (MeDiTech), University of Applied Sciences and Arts of Southern Switzerland, Lugano, Switzerland.
  • Michel Wälti
    IDUN Technologies AG, Glattpark, Switzerland.
  • Elias Meier
    IDUN Technologies AG, Glattpark, Switzerland.
  • Francesca Pentimalli Biscaretti di Ruffia
    IDUN Technologies AG, Glattpark, Switzerland.
  • Mark Melnykowycz
    IDUN Technologies AG, Glattpark, Switzerland.
  • Athina Tzovara
    Institute of Computer Science, University of Bern, Bern, Switzerland.
  • Valentina Agostini
    Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy.
  • Francesca Dalia Faraci
    Department of Innovative Technologies, Institute of Digital Technologies for Personalized Healthcare (MeDiTech), University of Applied Sciences and Arts of Southern Switzerland, Lugano, Switzerland.

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