Validation of a small cough detector

Abstract

Research questionThe assessment of cough frequency in clinical practice relies predominantly on the patient's history. Currently, objective evaluation of cough is feasible with bulky equipment during a brief time (i.e., hours up to one day). Thus, monitoring of cough has been rarely performed outside clinical studies. We developed a small wearable cough detector (SIVA-P3) that uses deep neural networks for the automatic counting of coughs. This study examined the performance of the SIVA-P3 in an outpatient setting.MethodsWe recorded cough epochs with SIVA-P3 over eight consecutive days in patients suffering from chronic cough. During the first 24 h, the detector was validated against cough events counted by trained human listeners. The wearing comfort and the device usage were assessed by a questionnaire.ResultsIn total, 27 participants (50±14 years) with either chronic unexplained cough (n=12), COPD (n=4), asthma (n=5) or interstitial lung disease (n=6) were studied. During the daytime, the sensitivity of SIVA-P3 cough detection was 88.5±2.49%, and the specificity was 99.97±0.01%. During the night-time, the sensitivity was 84.15±5.04% and the specificity was 99.97±0.02%. The wearing comfort and usage of the device was rated as very high by most participants.ConclusionSIVA-P3 enables automatic continuous cough monitoring in an outpatient setting for objective assessment of cough over days and weeks. It shows comparable or higher sensitivity than other devices with fully automatic cough counting. Thanks to its wearing comfort and the high performance for cough detection, it has the potential for being used in routine clinical practice.

Measuring cough: what really matters?

“…Other cough monitoring systems are in development ( 44 - 46 ), but there are several limitations to current technology. The above-mentioned devices, although small and lightweight, are intrusive to the patient to some degree.…”

Objective measurement of cough

“…The SIVA-P3 (SIVA Health AG, Switzerland) has utilised deep learning neural networks to identify cough sounds 32 . A small detector is worn around the neck and monitors both sound and movement, only recording data when the sound exceeds a specified threshold; it can be worn for up to eight days.…”