Non-negative matrix factorization improves the efficiency of recording frequency-following responses in normal-hearing adults and neonates.

One challenge in extracting the scalp-recorded frequency-following response (FFR) is related to its inherently small amplitude, which means that the response cannot be identified with confidence when only a relatively small number of recording sweeps are included in the averaging procedure. This stu...

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Publicado en:International Journal of Audiology Vol. 62; no. 7; pp. 688 - 699
Autores principales: Jeng, Fuh-Cherng, Lin, Tzu-Hao, Hart, Breanna N., Montgomery-Reagan, Karen, McDonald, Kalyn
Formato: diagnostic images equations & formulas research tables/charts Journal Article
Publicado: Taylor & Francis Ltd Jul2023
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jul2023
      vid: 62
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      pub: Taylor & Francis Ltd
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        10.1080/14992027.2022.2071345
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        atl: Non-negative matrix factorization improves the efficiency of recording frequency-following responses in normal-hearing adults and neonates.
      aug:
        au:
          Jeng, Fuh-Cherng
          Lin, Tzu-Hao
          Hart, Breanna N.
          Montgomery-Reagan, Karen
          McDonald, Kalyn
        affil: Communication Sciences and Disorders, Ohio University, Athens, OH, USA
      sug:
        subj:
          Algorithms
          Brain Stem Physiology
          Hearing
          Hearing Tests
          Infant, Newborn
          Language
          Speech Perception In Middle Age
          Multitrait-Multimethod
          Productivity
          Hearing Aid Care In Infancy and Childhood
          Hearing Aid Care In Adulthood
          Study Methods
          Human
          Adult
          Child
          Middle Age
          Pediatric Care
          Electrophysiology
          Microbiologic Phenomena
          Descriptive Statistics
          Infant, Newborn: birth-1 month
          Adult: 19-44 years
          Child: 6-12 years
          Middle Aged: 45-64 years
      ab: One challenge in extracting the scalp-recorded frequency-following response (FFR) is related to its inherently small amplitude, which means that the response cannot be identified with confidence when only a relatively small number of recording sweeps are included in the averaging procedure. This study examined how the non-negative matrix factorisation (NMF) algorithm with a source separation constraint could be applied to improve the efficiency of FFR recordings. Conventional FFRs elicited by an English vowel/i/with a rising frequency contour were collected. Study sample: Fifteen normal-hearing adults and 15 normal-hearing neonates were recruited. The improvements of FFR recordings, defined as the correlation coefficient and root-mean-square differences across a sweep series of amplitude spectrograms before and after the application of the source separation NMF (SSNMF) algorithm, were characterised through an exponential curve fitting model. Statistical analysis of variance indicated that the SSNMF algorithm was able to enhance the FFRs recorded in both groups of participants. Such improvements enabled FFR extractions in a relatively small number of recording sweeps, and opened a new window to better understand how speech sounds are processed in the human brain.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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