{"title":"Numerical Examination of RIS-Enabled Microwave Imaging for Sleep Monitoring.","authors":"Kavian Zirak, Mohammadreza F Imani","doi":"10.1109/ap-s/usnc-ursi60190.2026.11675113","DOIUrl":"10.1109/ap-s/usnc-ursi60190.2026.11675113","url":null,"abstract":"<p><p>This paper introduces a reconfigurable intelligent surface (RIS)-enabled framework for microwave imaging aimed at non-invasive human monitoring in indoor environments. Our primary objective is to generate a representative reflectivity map of a resting or sleeping individual. This imaging can facilitate tracking of movements and biomarkers, such as breathing, during rest or sleep. Achieving this challenging task necessitates high signal strength, robustness against clutter, and minimal measurements to ensure fast data acquisition. To address these requirements, the proposed system utilizes programmable RIS configurations to manipulate the electromagnetic field distribution within the region of interest (ROI). In contrast to traditional methods, we combine radar-coincidence imaging (RCI) with computational imaging techniques. The former method yields high signal strength and facilitates clutter rejection, while the latter reduces the number of required measurements. Numerical simulations using a humanoid demonstrate the feasibility of reconstructing key features. The low number of measurements paves the way for fast image reconstruction and movement detection. Additionally, a comparative study with conventional random illumination is conducted, demonstrating improved reconstruction outcomes. These findings underscore the potential of RIS-enabled imaging for non-contact biomarker monitoring applications.</p>","PeriodicalId":74559,"journal":{"name":"Proceedings. IEEE Antennas and Propagation Society. International Symposium","volume":"2026 ","pages":"13-16"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13674466/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149217391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Wearable 2.4 GHz Bluetooth Antenna for Respiration Monitoring and Contact Tracing.","authors":"Md Abu Saleh Tajin, Nathan Judd, Kapil Dandekar","doi":"10.1109/ap-s/usnc-ursi47032.2022.9887274","DOIUrl":"https://doi.org/10.1109/ap-s/usnc-ursi47032.2022.9887274","url":null,"abstract":"<p><p>A 2.4 GHz on-body Bluetooth antenna (BLEpatch) is proposed for respiration monitoring and contact tracing applications. Due to its patch structure, the antenna performance is robust at body proximity. The introduction of a compressible foam substrate allows it to periodically compress and relax in response to abdominal pressure due to respiration. The antenna is simulated both in free space and on a human body model. The antenna passband is 2.36 - 2.57 GHz with a maximum gain of 8.2 dBi in the relaxed state.</p>","PeriodicalId":74559,"journal":{"name":"Proceedings. IEEE Antennas and Propagation Society. International Symposium","volume":"2022 ","pages":"97-98"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10193855/pdf/nihms-1897105.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9551075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}