Acoustic therapies for tinnitus: The basis and the electroencephalographic evaluation

Ibarra-Zárate, David I.; Alonso-Valerdi, Luz María

doi:10.1016/j.bspc.2020.101900

Cited by 17 publications

(25 citation statements)

References 109 publications

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“…Recently, there have been substantial achievements in tinnitus diagnosis. Among them, methods based on electroencephalography (EEG) signals attract much attention because 1) many works prove that there exists a strong correlation between abnormal EEG and tinnitus [8], [9]; 2) EEG signals have objective evaluation compared with traditional methods that are based on the Visual Analog Scale (VAS) or questionnaires [10], [11], [12], [13]. With the development of information technology, many efforts are made to utilize machine learning and deep learning algorithms to analyze EEG signals and classify patients' tinnitus status [14], [15], [16], [17], [18], [19].…”

Section: Introductionmentioning

confidence: 99%

Disentangled and Side-aware Unsupervised Domain Adaptation for Cross-dataset Subjective Tinnitus Diagnosis

Li¹,

Liu²,

Yao³

et al. 2022

Preprint

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EEG-based tinnitus classification is a valuable tool for tinnitus diagnosis, research, and treatments. Most current works are limited to a single dataset where data patterns are similar. But EEG signals are highly non-stationary, resulting in model's poor generalization to new users, sessions or datasets. Thus, designing a model that can generalize to new datasets is beneficial and indispensable. To mitigate distribution discrepancy across datasets, we propose to achieve Disentangled and Sideaware Unsupervised Domain Adaptation (DSUDA) for crossdataset tinnitus diagnosis. A disentangled auto-encoder is developed to decouple class-irrelevant information from the EEG signals to improve the classifying ability. The side-aware unsupervised domain adaptation module adapts the class-irrelevant information as domain variance to a new dataset and excludes the variance to obtain the class-distill features for the new dataset classification. It also align signals of left and right ears to overcome inherent EEG pattern difference. We compare DSUDA with state-of-the-art methods, and our model achieves significant improvements over competitors regarding comprehensive evaluation criteria. The results demonstrate our model can successfully generalize to a new dataset and effectively diagnose tinnitus.

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Section: Introductionmentioning

confidence: 99%

Disentangled and Side-aware Unsupervised Domain Adaptation for Cross-dataset Subjective Tinnitus Diagnosis

Li¹,

Liu²,

Yao³

et al. 2022

Preprint

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“…One of the possible methods that can be used in the detection of binaural processing is by analysing brain signals is Electroencephalography (EEG) [23]. This technique measures the scalp potentials at the delivery of auditory stimuli in order to diagnose hearing disorders [24]. The EEG method removes reliance on participant literacy and communication skills and is easier for the participant to perform than the standard psychoacoustic tests, making it highly suitable for children.…”

Section: Introductionmentioning

confidence: 99%

Study of Correlation Between EEG Electrodes for the Analysis of Cortical Responses Related to Binaural Hearing

et al. 2021

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Binaural hearing is the ability of the human auditory system to integrate information received from both ears simultaneously. Binaural hearing is fundamental in understanding speech in noisy backgrounds. Any disfunction in one or both ears could cause a disruption in the processing mechanism. Auditory evoked potentials (AEPs) are electrical potentials evoked by externally presented auditory stimuli from any part of the auditory system. A non-invasive technology, electroencephalography (EEG) is used for the monitoring of AEPs. The research aims to identify the best suited electrode positions through correlation analysis and analyse the AEP signals from the selected electrodes in order to detect binaural sensitivity of the human brain. The study evaluates the time-averaged EEG responses of normal hearing subjects to auditory stimuli. The stimuli used for the study are 500 Hz Blackman windowed pure tones, presented in either homophasic (the same phase in both ears) or antiphasic (180-degree phase difference between the two ears) conditions. The study focuses on understanding the effect of phase reversal of auditory stimuli, an under interaural time difference (ITD) cue, on the middle latency response (MLR) region of the AEPs. A correlation analysis was carried out between the eight different locations and as a result, Cz and Pz electrode positions were selected as the best suited positions for further analysis. The selected electrode signals were further processed in the time domain and frequency domain analysis. In the time domain analysis, it was found that Cz electrode for eight subjects out of nine and Pz electrode for seven subjects out of nine, had the larger area under signal curve obtained in the antiphasic condition than in the homophasic signals. Frequency domain analysis showed that the frequency bands 20 to 25Hz and 25 to 30Hz had the most energy when elicited by antiphasic stimuli than by homophasic stimuli. The findings of this study can be further utilised for the detection of binaural processing in a human brain.

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“…Por otro lado, para la terapia TRT, la cual busca disminuir la percepción del acúfeno al presentar un sonido similar a este, pero un nivel disminuido [3], alejó los valores promedio de este grupo de los observados en el grupo Control en las métricas AC y EL para la banda alfa. Esto no necesariamente refleja que la terapia TRT no tuvo un efecto positivo en el tratamiento del acúfeno, ya que cada una de las terapias genera un efecto distinto sobre las estructuras del cerebro para habituar o reducir la percepción del acúfeno [10,13]. Ambos grupos reportaron una mejoría en su condición al recibir la terapia designada.…”

Section: Discussionunclassified

“…Dentro de los diferentes enfoques utilizados para el estudio del acúfeno se ha implementado el análisis de la conectividad funcional. Algunos estudios han reportado que en el padecimiento de acúfeno existe un comportamiento anormal en la comunicación entre neuronas (sincronía) y tasas de descarga espontáneas en los centros del sistema auditivo y no auditivos [9,10]. En otro estudio reportaron que la actividad asociada a la banda alfa presenta una reducción en regiones temporales, mientras que en las bandas delta y gamma existe un incremento en su actividad en regiones cerebrales como el área temporal derecha y frontal izquierdo [11].…”

Section: Introductionunclassified

“…Entre los diferentes tratamientos disponibles, las terapias acústicas han mostrado un buen desempeño. Estas terapias buscan principalmente restablecer el comportamiento de las vías y estructuras cerebrales involucradas en el sentido de la audición a su condición normal [10,13]. La evaluación del desempeño de las terapias acústicas se ha realizado con más frecuencia mediante el uso de herramientas como cuestionarios, Escalas Visuales Análogas (EVA) y pruebas de audiometría de tono puro [14].…”

Section: Introductionunclassified

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Evaluación de Terapias Acústicas en Pacientes con Acúfeno: Análisis de Conectividad en Potenciales Relacionados a Eventos

Álvarez-Terríquez

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The application of acoustic therapies in the treatment of patients with tinnitus is increasingly common. The main objective of these therapies is to restore the behavior of the brain pathways and structures involved in the sense of hearing to their normal condition. Brain electrical activity (EEG) is analyzed as it is one of many tools that have been used to study the underlying mechanisms of tinnitus. In this work, some characteristics that allow the detection of changes in brain connectivity 8 weeks after starting therapy in some acoustic therapies are presented. The auditory discrimination therapy or ADT, not only presented changes in the brain connectivity of the subjects who received it, but also the graph metrics used as feature values to measure this connectivity were close to the values presented in the control subjects. In the other hand, the tinnitus retraining therapy TRT, also presented changes in brain connectivity; however, the graph metrics used as feature values to measure this connectivity were not close to the values presented in the control subjects.

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Acoustic therapies for tinnitus: The basis and the electroencephalographic evaluation

Cited by 17 publications

References 109 publications

Disentangled and Side-aware Unsupervised Domain Adaptation for Cross-dataset Subjective Tinnitus Diagnosis

Disentangled and Side-aware Unsupervised Domain Adaptation for Cross-dataset Subjective Tinnitus Diagnosis

Study of Correlation Between EEG Electrodes for the Analysis of Cortical Responses Related to Binaural Hearing

Evaluación de Terapias Acústicas en Pacientes con Acúfeno: Análisis de Conectividad en Potenciales Relacionados a Eventos

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