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Design of Internet of Things-enabled textile-based biosensors
1 , * 2
1  Department of Biomedical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai.
2  Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and
Academic Editor: Paolo Bollella

Abstract:

During a health crisis or pandemic, people with breathing issues may find it challenging to receive timely medical attention as access to healthcare services is limited. Breathing difficulties can contribute to anxiety, stress, and uncertainty, and fear associated with a health crisis can further negatively impact mental health. To effectively tackle this situation, it is essential to diagnose these issues early. Furthermore, the primary symptom of such diseases is difficulty in breathing, accompanied by coughing. To identify these conditions, various sensor technologies such as plethysmography sensors, pressure transducers, acoustic sensors, accelerometers, gyroscopes, etc., were used. However, the use of these sensors poses certain challenges in terms of accuracy, calibration issues, discomfort, influence of body position, noise interference, cost, reliability in dynamic environments, and user acceptance. In this work, a textile-based sensor using conductive thread is designed and developed for the measurement of respiration rate. Further, the conductive thread is combined with woollen material to form a chest band that can be affixed to any person. Also, the developed sensor in the form of a chest band is integrated into the Internet of Things (IoT) controller, which measures the respiratory rate of the users while they perform various activities such as walking, running, practicing exercises, standing still, etc. Results demonstrate that the developed sensor can store the respiratory rate in the IoT cloud platform. Further, it is observed that the frequency of the acquired signals due to respiration changes for various activities. Additionally, the increase in frequency increases the noise in the acquired signal, and it is removed using a filter algorithm. This work appears to be of high clinical significance since the developed sensor diagnoses the breathing disorders in terms of respiration rate.

Keywords: Breathing; Internet of Things; health monitoring; Respiration rate; Textile

 
 
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