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(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.
Details
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
; Shi, Victoria 2 ; Sollee, John 1 ; Wen-Chi, Hsu 3
; Yu, Guangdi 4 ; Yu-Wei, Dai 4 ; Merlo, Christian 2 ; Suresh, Karthik 2 ; Jiao, Zhicheng 5 ; Wang, Xuyu 6 ; Mao, Shiwen 7
; Harrison, Bai 4 1 The Warren Alpert Medical School, Brown University, Providence, RI 02903, USA
2 School of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
3 Department of Radiology and Radiological Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA; Department of Medical Imaging and Intervention, Linkou Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
4 Department of Radiology and Radiological Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
5 Department of Diagnostic Radiology, Warren Alpert Medical School of Brown University, Providence, RI 02903, USA
6 School of Computing and Information Sciences, Florida International University, Miami, FL 33199, USA
7 Department of Electrical and Computer Engineering, Auburn University, Auburn, AL 36849, USA