Tesi etd-09192018-172811
Link copiato negli appunti
Tipo di tesi
Perfezionamento
Autore
MASELLI, MARTINA
URN
etd-09192018-172811
Titolo
Soft and Flexible Sensors: technologies and biomedical applications
Settore scientifico disciplinare
ING-IND/34
Corso di studi
INGEGNERIA - Biorobotics
Commissione
relatore Prof.ssa LASCHI, CECILIA
Parole chiave
- biomedical engineering
- pressure mapping
- strain detection
- textile sensors
Data inizio appello
07/12/2018;
Disponibilità
completa
Riassunto analitico
The study of pressure distribution over a not-defined surface, as well as the detection of stretching capability, are subjects matter of great interest in many fields as biomedical measurements, human motion detection, human-machine interfaces, and soft robotics. Novel and smart sensing solutions are research topics of great interest since the need for sensors with properties of flexibility and stretchability is growing. The emerging class of smart textiles holds great potential for developing new concepts of transducers and sensors, and investigations about their prospects deserve rising attention.
The aim of this research is the study of concepts and applications of textile sensors for strain and pressure detection. An example of matrix textile sensor has been designed and developed, by sandwiching a piezoresistive fabric sheet between two outer fabric layers embedding conductive rows and columns. The location of the applied pressure can be identified by detecting the position where the change of resistances occurs between the external conductive paths. Tests regarding its metrological properties have been carried out to highlight the sensor advantages and drawbacks and to establish general guidelines for its use. Also, a strain-resistance sensor based on commercial knitted textile has been designed and developed. Firstly, a methodology to characterize and to calibrate the strain-resistance sensor is proposed, suitable also for analysing the behaviour of any conductive and stretchable fabrics and useful to establish general guidelines for its use. Secondly, a new mathematical model is proposed to compensate for hysteresis and relaxation in strain sensors made of conductive textile.
The wide selection of advantages exhibited by this class of sensors, e.g. thinness, lightness, flexibility, stretchability and wearability, suggests their exploitation in a huge number of applications, especially concerning the biomedical field. In this thesis, smart fabric sensors based on a piezoresistive detecting principle have been employed to monitor single planes neck movements and to develop a new cognitive technological tool for physical and cognitive training. Development, testing and data analysis phases have been accomplished, confirming the versatility and potentiality of the sensing solutions based on smart textiles.
The aim of this research is the study of concepts and applications of textile sensors for strain and pressure detection. An example of matrix textile sensor has been designed and developed, by sandwiching a piezoresistive fabric sheet between two outer fabric layers embedding conductive rows and columns. The location of the applied pressure can be identified by detecting the position where the change of resistances occurs between the external conductive paths. Tests regarding its metrological properties have been carried out to highlight the sensor advantages and drawbacks and to establish general guidelines for its use. Also, a strain-resistance sensor based on commercial knitted textile has been designed and developed. Firstly, a methodology to characterize and to calibrate the strain-resistance sensor is proposed, suitable also for analysing the behaviour of any conductive and stretchable fabrics and useful to establish general guidelines for its use. Secondly, a new mathematical model is proposed to compensate for hysteresis and relaxation in strain sensors made of conductive textile.
The wide selection of advantages exhibited by this class of sensors, e.g. thinness, lightness, flexibility, stretchability and wearability, suggests their exploitation in a huge number of applications, especially concerning the biomedical field. In this thesis, smart fabric sensors based on a piezoresistive detecting principle have been employed to monitor single planes neck movements and to develop a new cognitive technological tool for physical and cognitive training. Development, testing and data analysis phases have been accomplished, confirming the versatility and potentiality of the sensing solutions based on smart textiles.
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