Thingspeak-based respiratory rate streaming system for essential monitoring purposes
-
Mohammed S. Jarjees
,
Mohammed G. Ayoub
Abstract
Introduction
Chronic obstructive pulmonary diseases are the most common disease worldwide. Asthma and sleep apnea are the most prevalent of pulmonary diseases. Patients with such chronic diseases require special care and continuous monitoring to avoid any respiratory deterioration. Therefore, the development of a dedicated and reliable sensor with the aid of modern technologies for measuring and monitoring respiratory parameters is very necessary nowadays.
Objective
This study aims to develop a small and cost-effective respiratory rate sensor.
Methods
A microcontroller and communication technology (NodeMCU) with the ThingSpeak platform is used in the proposed system to view and process the respiratory rate data every 60 s. The total current consumption of the proposed sensor is about 120 mA. Four able-bodied participants were recruited to test and validate the developed system.
Results
The results show that the developed sensor and the proposed system can be used to measure and monitor the respiratory rate.
Conclusions
The demonstrated system showed applicable, repeatable, and acceptable results.
Research funding: There is no research funding for this study.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
Ethical Approval: The conducted research is not related to either human or animal use.
Conflict of interest: The authors declare that they have no conflict of interest.
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© 2020 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
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- Cooperation of CUDA and Intel multi-core architecture in the independent component analysis algorithm for EEG data
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Artikel in diesem Heft
- Research Articles
- Overview of the holographic-guided cardiovascular interventions and training – a perspective
- Development of the low-cost, smartphone-based cardiac auscultation training manikin
- Cooperation of CUDA and Intel multi-core architecture in the independent component analysis algorithm for EEG data
- A distributed cognitive approach in cybernetic modelling of human vision in a robotic swarm
- Thingspeak-based respiratory rate streaming system for essential monitoring purposes
- Recognition of multifont English electronic prescribing based on convolution neural network algorithm
- Short Communication
- BatchDeconvolution: a Fiji plugin for increasing deconvolution workflow
