Deep Learning Models for Physiological Data Classification of Children During Computerized Auditory Tests: Deep Learning-Based Emotion Recognition in Child-Computer Interaction

Deep Learning Models for Physiological Data Classification of Children During Computerized Auditory Tests: Deep Learning-Based Emotion Recognition in Child-Computer Interaction

Duygun Erol Barkana, Itır Kaşıkçı, Hatice Kose, Elif Toprak, Selma Yılar, Dilara Demirpençe Seçinti
Copyright: © 2022 |Pages: 17
DOI: 10.4018/978-1-7998-8686-0.ch003
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Abstract

The chapter aims to classify the physiological data of hearing impaired (HI) and typically developed (TD) children using machine/deep learning techniques 1) to reveal if the physiological data of the HI and TD are distinguishable, 2) to understand which emotions of HI and TD are recognized, and 3) to investigate the effect of computerization in a subset of audiology perception tests. Physiological signals, which are blood volume pulse (BVP), skin conductance (SC), and skin temperature (ST), are collected using a wearable E4 wristband during computerized and conventional tests. Sixteen HI and 18 TD children participated in this study. An artificial neural network (ANN) and a convolutional neural network (CNN) model are used to classify physiological data. The physiological changes of HI and TD children are distinguishable in computerized tests. TD children's positive (pleasant) and negative (unpleasant) emotions (PN) are distinguishable on both computerized and conventional tests. HI children's neutral and negative (unpleasant) (NU) emotions are distinguishable in the computerized tests.
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Background

Auditory Perception

Auditory perception is the recognition and interpretation of auditory stimuli and is especially important for speech and language development in children (Cole, 2007). Furthermore, auditory maturation is the basic component in the development of auditory perception (Saffran, 2006), and children with hearing loss are at risk in the development of auditory perception. For this reason, evaluation of the auditory perception skills of children with hearing loss is also necessary for typical development.

Auditory perception tests are screening or diagnostic evaluation tools used to identify deficiencies, especially auditory discrimination skills. Therefore, it is essential to evaluate auditory perception skills, especially preschool and school-age children (Hull, 1999). developmental test of auditory perception (DTAP) is a comprehensive auditory perception test battery previously used and validated in a study done with Turkish typically developed children (Cinar, 2021).

DTAP consists of five subtests to evaluate auditory perception: environmental sounds, word discrimination, phonemes in isolation, tonal pattern, and rhyming sounds. In this chapter, environmental sounds and tonal patterns are used to evaluate the auditory perception skills of children with hearing loss and are presented in two different media (computerized and conventional), and the results were evaluated.

Key Terms in this Chapter

Classification: Recognizing the states of the categorized objective to solve a grouping, detecting, or stratifying problem.

Conventional Test: The traditional tests that are manually done with paper-and-pencil formats.

Emotion: The automatically evoked regulation system of the body when a situation is encountered relating to ones' well-being.

Physiological Signals: Biological markers such as heat, heartbeat, or skin moisture that are collected via sensors on the skin and that change according to people’s emotional states.

Auditory Perception: The ability to identify, interpret, and attach meaning to the sound that is heard.

Computerized Test: A conventional test designed and developed as a computer program via a digitized interface.

Hearing Loss: The partial or complete disability to hear the sound by one or both of ones’ ears.

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