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Query: UMLS:C0010200 (cough)
 23,843 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Infants' ability to process others' emotional expressions is fundamental for their social development. While infants' processing of emotions expressed by faces and speech has been more extensively investigated, less is known about how infants process non-verbal vocalizations of emotions. Here, we recorded frontal N100, P200, and LPC event-related potentials (ERPs) from 8-month-old infants listening to sounds of other infants crying, laughing, and coughing. Infants' temperament was measured via parental report. Results showed that processing of emotional information from non-verbal vocalizations was associated with more negative N100 and greater LPC amplitudes for peer's crying sounds relative to positive and neutral sounds. Temperament was further related to the N100, P200, and LPC difference scores between conditions. One important finding was that infants with improved ability to regulate arousal exhibited increased sustained processing of peers' cry sounds compared to both laughter and cough sounds. These results emphasize the relevance of considering the temperamental characteristics in understanding the development of infant emotion information processing, as well as for formulating comprehensive theoretical models of typical and atypical social development.
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PMID:Individual differences in infants' neural responses to their peers' cry and laughter. 2959 56

Cough is a common symptom of numerous respiratory diseases. In certain cases, such as asthma and COPD, early identification of coughs is useful for the management of these diseases. This paper presents an algorithm for automatic identification of cough events from acoustic signals. The algorithm is based on only four features of the acoustic signals including LPC coefficient, tonality index, spectral flatness and spectral centroid with a logistic regression model to label sound segments into cough and non-cough events. The algorithm achieves sensitivity of of 86.78%, specificity of 99.42%, and F1-score of 88.74%. Its high performance despite its small size of feature-space demonstrate its potential for use in remote patient monitoring systems for automatic cough detection using acoustic signals.
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PMID:Automatic Identification of Cough Events from Acoustic Signals. 3194 81