Enhancing sleep pattern assessment with biocompatible smart materials

Autor: Makwana Dhaval, Najah Zahraa, Soni Devendra, Valiveti Hima Bindu, Chandrashekar Rakesh, Nijhawan Ginni, Yakaiah P
Jazyk: English<br />French
Rok vydání: 2024
Předmět:
Zdroj: E3S Web of Conferences, Vol 552, p 01095 (2024)
Druh dokumentu: article
ISSN: 2267-1242
DOI: 10.1051/e3sconf/202455201095
Popis: Biomaterials with intelligence can respond to variations in physiological factors. Additionally, they react to external stimuli that influence many attributes of allopathic drugs (technological advances medicine). Smart biomaterials are employed in a variety of therapies to enhance the care of different illnesses. Bio-based smart materials can be molded into a variety of soft designs, such as textiles, hydrogel, membranes film, aerogels, nanofibers, and fabrics, which are advantageous for wearable sensors when compared to polymers generated from petroleum. In this paper, sleep patterns are examined closely in relation to mental health, with a particular focus on bio-signal processing in identifying sleep-related disorders. According to the study, sleep stage analysis is critical to improving therapeutic outcomes for individuals suffering from depression due to its physiological influence. Biologically compatible smart devices enhance advanced biological capture techniques such as electroencephalography (EEG), electrocardiogram (ECG), and electromyography (EMG). As a result, these features increase sensor reliability, accuracy and reliability, ensuring high signal fidelity. The use of biocompatible smart-material based devices with artificial intelligence provides a revolutionary approach to the diagnosis of complex interconnected disorders of mental illness, sleep disorders and schizophrenia, including neural changes and its recurrence to identify sleep phases and identify trauma-related disturbances, and sophisticated machine learning provides in-depth insights.
Databáze: Directory of Open Access Journals