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Technical analysis and testing of wearable ECG sensors for vital parameters detection

Vanessa Nani

Technical analysis and testing of wearable ECG sensors for vital parameters detection.

Rel. Luca Mesin, Matteo Raggi. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2023


Nowadays, the field of smart textiles is growing steadily. Smart textiles are commercially available in various applications, such as sports, healthcare, automotive, military, personal protection, security, and space exploration. This is the context for the product developed by start-up H-Cube which designs, manufactures, and markets high-tech clothing. More specifically, the proposed technology aims to transform a traditional garment into a useful active element for monitoring the health state of the user. One of the main problems for these smart technologies is washability; indeed, it affects both the electrical properties of the constituting materials and the functionality of the product. For this reason, it is important to carry out a careful analysis of the effects of washing processes. In this work, we assessed the physical properties and the behavior of the electrodes, embedded in the smart T-shirt, after a defined number of washes, evaluating the electrode integrity and resistivity, and the quality of the recorded electrocardiogram (ECG). Consequently, the focus moved from hardware to software analysis testing the H-Cube method for identifying the heart rate (HR) of the user. The performances of the algorithm were evaluated in recordings corrupted by simulated electromyogram (EMG), a source of interference that, with motion artifacts and power line interference, makes not trivial the HR estimation. As a final step, the smart T-shirt was tested during motor and psychological tests, in order to analyze the subject's stress levels and provide information about the health status. For this purpose, a heart rate variability (HRV) analysis was conducted by studying indices extracted from the recorded ECG signal.

Relators: Luca Mesin, Matteo Raggi
Academic year: 2022/23
Publication type: Electronic
Number of Pages: 97
Additional Information: Tesi secretata. Fulltext non presente
Corso di laurea: Corso di laurea magistrale in Ingegneria Biomedica
Classe di laurea: New organization > Master science > LM-21 - BIOMEDICAL ENGINEERING
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/27833
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