most citedAutomatic non-invasive Cough Detection based on Accelerometer and Audio Signals

31 citations · 82 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2022★ 27 cited

Automatic Tuberculosis and COVID-19 cough classification using deep learning

Madhurananda Pahar, Marisa Klopper, Byron Reeve +4

We present a deep learning based automatic cough classifier which can discriminate tuberculosis (TB) coughs from COVID-19 coughs and healthy coughs. Both TB and COVID-19 are respir…

cs.LG2022

Accelerometer-based Bed Occupancy Detection for Automatic, Non-invasive Long-term Cough Monitoring

Madhurananda Pahar, Igor Miranda, Andreas Diacon +1

We present a new machine learning based bed-occupancy detection system that uses the accelerometer signal captured by a bed-attached consumer smartphone. Automatic bed-occupancy de…

cs.SD2021

Wake-Cough: cough spotting and cougher identification for personalised long-term cough monitoring

Madhurananda Pahar, Marisa Klopper, Byron Reeve +4

We present `wake-cough', an application of wake-word spotting to coughs using a Resnet50 and the identification of coughers using i-vectors, for the purpose of a long-term, persona…

cs.SD2021★ 31 cited

Automatic non-invasive Cough Detection based on Accelerometer and Audio Signals

Madhurananda Pahar, Igor Miranda, Andreas Diacon +1

We present an automatic non-invasive way of detecting cough events based on both accelerometer and audio signals. The acceleration signals are captured by a smartphone firmly attac…

cs.LG2021★ 24 cited

Deep Neural Network based Cough Detection using Bed-mounted Accelerometer Measurements

Madhurananda Pahar, Igor Miranda, Andreas Diacon +1

We have performed cough detection based on measurements from an accelerometer attached to the patient's bed. This form of monitoring is less intrusive than body-attached accelerome…