This thesis falls within the field of bioengineering applied to audiology and describes the development and validation of an automated system for analyzing auditory brainstem evoked potentials (ABRs) acquired in vivo from a mouse model of spontaneous aging at the Bioacoustics Laboratory of the University of Padua. The primary objective of this work is to automate the extraction process of key audiological parameters, particularly hearing thresholds and wave latencies, which traditionally require time-consuming manual assessment and are subject to inter-operator variability. The developed script efficiently manages the import and organization of data from murine subjects across multiple experimental sessions. The script provides graphical representations of responses to click stimuli and various tonal frequencies and applies cross-correlation and peak detection algorithms to automatically determine thresholds and wave latencies from waves I to IV. Validation was conducted by systematically comparing the automatic results with those obtained from manual analysis, using independent and paired t-tests. The statistical results and comparison with the literature confirm that the automatic method could represent, albeit with limitations, a reliable and reproducible tool for the objective processing of ABR tracings.
La presente tesi si inserisce nell’ambito della bioingegneria applicata all’audiologia e descrive lo sviluppo e la validazione di un sistema automatizzato per l’analisi dei potenziali evocati uditivi del tronco encefalico (ABR, Auditory Brainstem Response) acquisiti in vivo da un modello murino di invecchiamento spontaneo presso il Laboratorio di Bioacustica dell’Università di Padova. Obiettivo principale del lavoro è l’automazione del processo di estrazione dei parametri audiologici fondamentali, in particolare la soglia uditiva e latenze delle onde, che tradizionalmente richiedono una valutazione manuale dispendiosa in termini di tempo e soggetta a variabilità inter-operatore. Lo script sviluppato gestisce in modo efficiente l’importazione e l’organizzazione dati provenienti da soggetti murini in più sessioni sperimentali. Lo script è in grado di fornire rappresentazioni grafiche delle risposte a stimoli click e a varie frequenze tonali e applica algoritmi di cross-correlazione e rilevamento dei picchi per determinare automaticamente le soglie e le latenze da I a IV onda. La validazione è stata condotta confrontando sistematicamente i risultati automatici con quelli ottenuti da analisi manuale, mediante t-test indipendenti e accoppiati. I risultati delle statistiche e il confronto con la letteratura confermano che il metodo automatico potrebbe rappresentare, seppur con dei limiti, uno strumento affidabile e riproducibile per l’elaborazione oggettiva dei tracciati ABR.
Rilevazione automatizzata della soglia uditiva e analisi delle latenze mediante elaborazione di segnali elettrofisiologici in modelli animali con invecchiamento spontaneo.
CRISTILLO, GIOVANNA
2024/2025
Abstract
This thesis falls within the field of bioengineering applied to audiology and describes the development and validation of an automated system for analyzing auditory brainstem evoked potentials (ABRs) acquired in vivo from a mouse model of spontaneous aging at the Bioacoustics Laboratory of the University of Padua. The primary objective of this work is to automate the extraction process of key audiological parameters, particularly hearing thresholds and wave latencies, which traditionally require time-consuming manual assessment and are subject to inter-operator variability. The developed script efficiently manages the import and organization of data from murine subjects across multiple experimental sessions. The script provides graphical representations of responses to click stimuli and various tonal frequencies and applies cross-correlation and peak detection algorithms to automatically determine thresholds and wave latencies from waves I to IV. Validation was conducted by systematically comparing the automatic results with those obtained from manual analysis, using independent and paired t-tests. The statistical results and comparison with the literature confirm that the automatic method could represent, albeit with limitations, a reliable and reproducible tool for the objective processing of ABR tracings.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/93730