A novel automatic cough frequency monitoring system combining a triaxial accelerometer and a stretchable strain sensor
Abstract Objective evaluations of cough frequency are considered important for assessing the clinical state of patients with respiratory diseases. However, cough monitors with audio recordings are rarely used in clinical settings. Issues regarding privacy and background noise with audio recordings a...
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Nature Portfolio
2021
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oai:doaj.org-article:36ecbdbe3ce44bf0adc232e554b9603e2021-12-02T17:02:21ZA novel automatic cough frequency monitoring system combining a triaxial accelerometer and a stretchable strain sensor10.1038/s41598-021-89457-02045-2322https://doaj.org/article/36ecbdbe3ce44bf0adc232e554b9603e2021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-89457-0https://doaj.org/toc/2045-2322Abstract Objective evaluations of cough frequency are considered important for assessing the clinical state of patients with respiratory diseases. However, cough monitors with audio recordings are rarely used in clinical settings. Issues regarding privacy and background noise with audio recordings are barriers to the wide use of these monitors; to solve these problems, we developed a novel automatic cough frequency monitoring system combining a triaxial accelerator and a stretchable strain sensor. Eleven healthy adult volunteers and 10 adult patients with cough were enrolled. The participants wore two devices for 30 min for the cough measurements. An accelerator was attached to the epigastric region, and a stretchable strain sensor was worn around their neck. When the subjects coughed, these devices displayed specific waveforms. The data from all the participants were categorized into a training dataset and a test dataset. Using a variational autoencoder, a machine learning algorithm with deep learning, the components of the test dataset were automatically judged as being a “cough unit” or “non-cough unit”. The sensitivity and specificity in detecting coughs were 92% and 96%, respectively. Our cough monitoring system has the potential to be widely used in clinical settings without any concerns regarding privacy or background noise.Takehiro OtoshiTatsuya NaganoShintaro IzumiDaisuke HazamaNaoko KatsuradaMasatsugu YamamotoMotoko TachiharaKazuyuki KobayashiYoshihiro NishimuraNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021) |
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DOAJ |
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EN |
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Medicine R Science Q |
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Medicine R Science Q Takehiro Otoshi Tatsuya Nagano Shintaro Izumi Daisuke Hazama Naoko Katsurada Masatsugu Yamamoto Motoko Tachihara Kazuyuki Kobayashi Yoshihiro Nishimura A novel automatic cough frequency monitoring system combining a triaxial accelerometer and a stretchable strain sensor |
| description |
Abstract Objective evaluations of cough frequency are considered important for assessing the clinical state of patients with respiratory diseases. However, cough monitors with audio recordings are rarely used in clinical settings. Issues regarding privacy and background noise with audio recordings are barriers to the wide use of these monitors; to solve these problems, we developed a novel automatic cough frequency monitoring system combining a triaxial accelerator and a stretchable strain sensor. Eleven healthy adult volunteers and 10 adult patients with cough were enrolled. The participants wore two devices for 30 min for the cough measurements. An accelerator was attached to the epigastric region, and a stretchable strain sensor was worn around their neck. When the subjects coughed, these devices displayed specific waveforms. The data from all the participants were categorized into a training dataset and a test dataset. Using a variational autoencoder, a machine learning algorithm with deep learning, the components of the test dataset were automatically judged as being a “cough unit” or “non-cough unit”. The sensitivity and specificity in detecting coughs were 92% and 96%, respectively. Our cough monitoring system has the potential to be widely used in clinical settings without any concerns regarding privacy or background noise. |
| format |
article |
| author |
Takehiro Otoshi Tatsuya Nagano Shintaro Izumi Daisuke Hazama Naoko Katsurada Masatsugu Yamamoto Motoko Tachihara Kazuyuki Kobayashi Yoshihiro Nishimura |
| author_facet |
Takehiro Otoshi Tatsuya Nagano Shintaro Izumi Daisuke Hazama Naoko Katsurada Masatsugu Yamamoto Motoko Tachihara Kazuyuki Kobayashi Yoshihiro Nishimura |
| author_sort |
Takehiro Otoshi |
| title |
A novel automatic cough frequency monitoring system combining a triaxial accelerometer and a stretchable strain sensor |
| title_short |
A novel automatic cough frequency monitoring system combining a triaxial accelerometer and a stretchable strain sensor |
| title_full |
A novel automatic cough frequency monitoring system combining a triaxial accelerometer and a stretchable strain sensor |
| title_fullStr |
A novel automatic cough frequency monitoring system combining a triaxial accelerometer and a stretchable strain sensor |
| title_full_unstemmed |
A novel automatic cough frequency monitoring system combining a triaxial accelerometer and a stretchable strain sensor |
| title_sort |
novel automatic cough frequency monitoring system combining a triaxial accelerometer and a stretchable strain sensor |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/36ecbdbe3ce44bf0adc232e554b9603e |
| work_keys_str_mv |
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