Advances in Data Science: Methodologies and Applications by Unknown

Author:Unknown
Language: eng
Format: epub
ISBN: 9783030518707
Publisher: Springer International Publishing

Recently, new polymer compositions and new materials have emerged in order to address these limitations of traditional electrodes, aiming to adhere seamlessly to the skin [13, 14]. In this regard, many novel polymer materials have been researched to prepare conformable electrodes based on smart textiles and adhesive hydrogel [15, 16]. Considering the polymer made electrodes, for example, cellulose-based composite hydrogels and membranes with conductive compounds show potential applications in the acquisition of bio-signals [17, 18]. In this work, a novel biocompatible polymer electrolyte with good mechanical and conductive performance was prepared using polyvinyl alcohol (PVA), and carboxy-methil-cellulose (CMC) in order to obtain flexible and conductive membrane. Some studies indicated the blending of CMC with PVA in order to increase stability and mechanical properties through preparation of its hybrid materials porosity [19]. In the optical of creating polymers as electrode coatings for EMG, it has been proposed an approach to blending the electrolyte or conducting polymers (CPs) with other polymer forms, such as hydrogels or matrices improving conductivity [20]. Although both synthesis and evaluation on structure–property still remain challenges; these new materials comprised of electrolyte, conducting polymers and co-biopolymers in different forms as matrix hydrogel or textile, are promising in the field of bioactive electrode coatings, useful in smart wearable system research.

In the paper, new wireless and low cost smart socks for the surface EMG signals acquisition were developed to increase the users’ level of usability and acceptability. This aim was achieved with the integration into the device of all electronics components and biocompatible hybrid polymer electrolyte (HPe)-based electrodes for the EMG data acquisition and transmission. The hardware was realized customizing commercial devices for that purpose and a low computational cost machine learning paradigm was chosen for the evaluation of imbalance events. The device was designed to monitor the Gastrocnemius Lateralis (GL) and Tibialis Anterior (TA) muscles contractions. The lack of human balance analysis is described by using the realized socks, suitable for the fall risk evaluation.

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