Shilpa Pavithran;Vineeta V Nair;Aravind S;Elizabeth George;Alex James
{"title":"基于交叉槽天线和人工智能集成的手部位置监测及手部摆动分析","authors":"Shilpa Pavithran;Vineeta V Nair;Aravind S;Elizabeth George;Alex James","doi":"10.1109/JSAS.2025.3586207","DOIUrl":null,"url":null,"abstract":"This work details the position monitoring of human hands using two similar cross-slot antennas operating in the frequency range of 2–3 GHz. Here, one antenna is kept on the chest and the other one is kept on the hand of a volunteer to monitor hand swing activity. The measured transmission values (<inline-formula><tex-math>$S_{21}$</tex-math></inline-formula>) along with corresponding frequencies from the antenna are used for generating synthetic <inline-formula><tex-math>$S_{21}$</tex-math></inline-formula> data using custom generative adversarial networks (GANs). Classification of data for two positions is performed on an artificial neural network (ANN), support vector machines (SVMs), decision tree (DT), and random forest. ANN gives an accuracy of 85% and is implemented on FPGA. The article also discusses the electromagnetic (EM) wave propagation around the human torso.","PeriodicalId":100622,"journal":{"name":"IEEE Journal of Selected Areas in Sensors","volume":"2 ","pages":"212-221"},"PeriodicalIF":0.0000,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072042","citationCount":"0","resultStr":"{\"title\":\"Position Monitoring of Human Hands Using Cross-Slot Antennas and AI Integration for Hand Swing Activity Analysis\",\"authors\":\"Shilpa Pavithran;Vineeta V Nair;Aravind S;Elizabeth George;Alex James\",\"doi\":\"10.1109/JSAS.2025.3586207\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work details the position monitoring of human hands using two similar cross-slot antennas operating in the frequency range of 2–3 GHz. Here, one antenna is kept on the chest and the other one is kept on the hand of a volunteer to monitor hand swing activity. The measured transmission values (<inline-formula><tex-math>$S_{21}$</tex-math></inline-formula>) along with corresponding frequencies from the antenna are used for generating synthetic <inline-formula><tex-math>$S_{21}$</tex-math></inline-formula> data using custom generative adversarial networks (GANs). Classification of data for two positions is performed on an artificial neural network (ANN), support vector machines (SVMs), decision tree (DT), and random forest. ANN gives an accuracy of 85% and is implemented on FPGA. The article also discusses the electromagnetic (EM) wave propagation around the human torso.\",\"PeriodicalId\":100622,\"journal\":{\"name\":\"IEEE Journal of Selected Areas in Sensors\",\"volume\":\"2 \",\"pages\":\"212-221\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11072042\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Journal of Selected Areas in Sensors\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11072042/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Selected Areas in Sensors","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/11072042/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Position Monitoring of Human Hands Using Cross-Slot Antennas and AI Integration for Hand Swing Activity Analysis
This work details the position monitoring of human hands using two similar cross-slot antennas operating in the frequency range of 2–3 GHz. Here, one antenna is kept on the chest and the other one is kept on the hand of a volunteer to monitor hand swing activity. The measured transmission values ($S_{21}$) along with corresponding frequencies from the antenna are used for generating synthetic $S_{21}$ data using custom generative adversarial networks (GANs). Classification of data for two positions is performed on an artificial neural network (ANN), support vector machines (SVMs), decision tree (DT), and random forest. ANN gives an accuracy of 85% and is implemented on FPGA. The article also discusses the electromagnetic (EM) wave propagation around the human torso.