Cough Detection from Acoustic signals for patient monitoring system

Autor:	Kulkarni, Vinay, Vadakkethil, Radhakrishnan
Rok vydání:	2021
Předmět:	Computer Science - Sound Electrical Engineering and Systems Science - Audio and Speech Processing
Druh dokumentu:	Working Paper
Popis:	Cough is one of the most common symptoms in all respiratory diseases. In cases like Chronic Obstructive Pulmonary Disease, Asthma, acute and chronic Bronchitis and the recent pandemic Covid-19, the early identification of cough is important to provide healthcare professionals with useful clinical information such as frequency, severity, and nature of cough to enable better diagnosis. This paper presents and demonstrates best feature selection using MFCC which can help to determine cough events, eventually helping a neural network to learn and improve accuracy of cough detection. The paper proposes to achieve performance of 97.77% Sensitivity (SE), 98.75% Specificity (SP) and 98.17% F1-score with a very light binary classification network of size close to 16K parameters, enabling fitment into smart IoT devices. Comment: 5 pages, 10 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2107.11835 Zobrazit plný text záznamu View this record from Arxiv