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Deep Breath - Wearable IoT sensor node to Monitor and Detect cough
KTH, School of Information and Communication Technology (ICT), Electronics and Embedded Systems. UTU. (Electronics systems)
KTH, School of Information and Communication Technology (ICT), Electronics and Embedded Systems.
KTH, School of Information and Communication Technology (ICT).
2016 (English)In: Thirteenth International Summer School on Advanced Computer Architecture and Compilation for High-Performance and Embedded Systems, 2016Conference paper, Poster (with or without abstract) (Other (popular science, discussion, etc.))
Abstract [en]

Coughing is the number one symptom individuals report when experiencing an illness. It is the most common symptom for respiratory disorders, including chronic lung disease, pneumonia, tuberculosis and influenza. Cough can appear sporadically with common illnesses

(e.g. cold), but when it becomes chronic it can severely impair life quality. This symptom is the most common reason for people to seek medical advice.

Continuous monitoring of objective cough frequency and severity can greatly assist physicians to give an early diagnosis of patient’s illness and the assessment of treatment efficiency. It requires a combination of measures characterizing cough frequency, intensity and its impact on quality of life.

In the proposed project we will investigate a sensor fusion approach, where the sound detection algorithms are combined with additional sensor parameters from a wearable health device. Parameters such as accelerometer and bio impedance data is combined with audio input to give a reliable cough detection. The algorithms will be

implemented on a low power sensor node for real-time operation. The respiratory sounds and signal processing focused on detection of frequency and phases of respiratory cycle are the main features. The research include cough sound detection designed for operation on sensor node with low power management.

Place, publisher, year, edition, pages
2016.
National Category
Engineering and Technology
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-238467OAI: oai:DiVA.org:kth-238467DiVA, id: diva2:1260113
Conference
Thirteenth International Summer School on Advanced Computer Architecture and Compilation for High-Performance and Embedded Systems
Note

QC 20181130

Available from: 2018-11-01 Created: 2018-11-01 Last updated: 2018-11-30Bibliographically approved

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Kelati, AmlesetTenhunen, Hannu

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CiteExportLink to record
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