Imagen de Portada

Artificial Intelligence-Driven Wireless Sensing for Health Management

Guardado en:
Publicado en:Bioengineering vol. 12, no. 3 (2025), p. 244
Autor principal: Toruner, Merih Deniz
Otros Autores: Shi, Victoria, Sollee, John, Wen-Chi, Hsu, Yu, Guangdi, Yu-Wei, Dai, Merlo, Christian, Suresh, Karthik, Jiao, Zhicheng, Wang, Xuyu, Mao, Shiwen, Harrison, Bai
Publicado:
MDPI AG
Materias:
United States > US
Physiology
Medical electronics
Artificial intelligence
Smartphones
Precision medicine
Sensors
Disease
Telemedicine
Signal processing
Chronic illnesses
Radio frequency identification
Data processing
Diagnosis
Network interface cards
Health services
Monitoring
Respiration
Health literacy
Patients
Clinical medicine
Sleep apnea
Acoustics
Real time
Heart rate
Acceso en línea:Citation/Abstract
Full Text + Graphics
Full Text - PDF
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Resumen:(1) Background: With technological advancements, the integration of wireless sensing and artificial intelligence (AI) has significant potential for real-time monitoring and intervention. Wireless sensing devices have been applied to various medical areas for early diagnosis, monitoring, and treatment response. This review focuses on the latest advancements in wireless, AI-incorporated methods applied to clinical medicine. (2) Methods: We conducted a comprehensive search in PubMed, IEEEXplore, Embase, and Scopus for articles that describe AI-incorporated wireless sensing devices for clinical applications. We analyzed the strengths and limitations within their respective medical domains, highlighting the value of wireless sensing in precision medicine, and synthesized the literature to provide areas for future work. (3) Results: We identified 10,691 articles and selected 34 that met our inclusion criteria, focusing on real-world validation of wireless sensing. The findings indicate that these technologies demonstrate significant potential in improving diagnosis, treatment monitoring, and disease prevention. Notably, the use of acoustic signals, channel state information, and radar emerged as leading techniques, showing promising results in detecting physiological changes without invasive procedures. (4) Conclusions: This review highlights the role of wireless sensing in clinical care and suggests a growing trend towards integrating these technologies into routine healthcare, particularly patient monitoring and diagnostic support.
ISSN:2306-5354
DOI:10.3390/bioengineering12030244
Fuente:Engineering Database