Photonic Textiles: Optical Fiber Integrated Smart Textile for Healthcare Applications

Nome: Letícia Munhoz de Avellar
Tipo: Tese de doutorado
Data de publicação: 31/01/2022
Orientador:

Nomeordem decrescente Papel
Anselmo Frizera Neto Co-orientador
Arnaldo Gomes Leal Júnior Orientador

Banca:

Nomeordem decrescente Papel
Anselmo Frizera Neto Coorientador
Arnaldo Gomes Leal Júnior Orientador
Camilo Arturo Rodriguez Diaz Examinador Interno
Carlos Alberto Ferreira Marques Examinador Externo
Daniele Tosi Examinador Externo
Eduardo Rocon de Lima Coorientador
Santosh Kumar Examinador Externo

Resumo: In recent years, technologies in the scope of Internet of Things (IoT) have been employed as strategical approaches for decentralized decision making through the connection of the digital and physical worlds. Smart Healthcare is an IoT application, which aims at the improvement of the everyday quality of life in the end-user community. Sensor devices are employed to collect medical data and vital signs from patients to monitor diagnose conditions, track progress and indicate anomalies. Moreover, remote healthcare monitoring with high speed and intelligent execution can be achieved by increasing the number of devices and using Artificial Intelligence (AI) algorithms, since the combination of IoT and AI in the healthcare sector has a higher potential of making intelligent decisions in real-time for patient medical records. Flexible sensors miniaturization and advancements have boosted the development of wearable technologies to track health-related parameters or to extract practical features from multi-modal sensors on the wearable device. Wearable sensors play an important role in remote healthcare monitoring, since they allow performing a diagnostic evaluation at home with the use of non-invasive and unobtrusive sensors during daily activities. There are popular wearable devices in the market, such as inertial sensors embedded in elastic bands, smart watches and instrumented insoles, for movement and posture analysis, physiological parameters monitoring and pressure plantar detection. However, simultaneous monitoring of different healthrelated parameters requires the use of several individual devices, which lead to issues related to devices’ connection and synchronization, in addition to a discomfort and a possible skin irritation due to long-term use of these wearable devices. Sensors integration with clothing, so-called smart textiles, are attractive solutions to overcome these drawbacks. The smart textiles present the advantages regarding to sensors compactness and higher transparency between the sensor and the user, which leads to the monitoring of the natural activity without inhibiting the user’s movement. Furthermore, smart textiles are easily handled, with simple installation and removal, which represents an advantage in terms of usability.
Optical fiber sensors (OFS) have attractive features for smart textile technology, including compactness, lightweight and multiplexing capabilities. In addition, OFS are not susceptible to electrical discharges and they are immune to electromagnetic interference. The polymer optical fiber (POF) sensors have additional advantages since they present high flexibility and biocompatibility. This PhD Thesis presents a promising remote healthcare monitoring solution based on the combination of different optical fiber sensors approaches with AI algorithms and the integration of such systems in textiles and clothing accessories. Such approach leads to innovative optical fiber-based solutions capable of accurately identify activities, assess movement-related parameters, including physiological and gait parameters. The approaches proposed in this work includes the multiplexed intensity variation-based sensors, fiber Bragg gratings (FBGs) and transmission-reflection analysis (TRA) systems for distributed and quasi-distributed sensors systems. These approaches are applied in different protocols and applications, including balance assessment, movement analysis and classification. In addition, this PhD Thesis also presents the development of a Smart Environment based on Heterogeneous OFS Network for remote healthcare monitoring. This leads to the improvement of the communication between patients and clinicians leading to a high potential of making intelligent real-time decisions in a homecare assessment, which not only indicate an important improvement in Healthcare 4.0 systems, but also lead to the possibility of developing innovative multifunctional devices for healthcare applications.

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