{"title":"Wi-Cyclops: Room-Scale WiFi Sensing System for Respiration Detection Based on Single-Antenna","authors":"Youwei Zhang, Feiyu Han, Panlong Yang, Yuanhao Feng, Yubo Yan, Ran Guan","doi":"10.1145/3632958","DOIUrl":null,"url":null,"abstract":"<p>Recent years have witnessed the emerging development of single-antenna wireless respiration detection that can be integrated into IoT devices with a single transceiver chain. However, existing single-antenna-based solutions are all limited by the short sensing range within 2-4 m due to noise interference, which makes them difficult to be adopted in most room-scale scenarios. To deal with this dilemma, we propose a room-scale, noise-resistance, and accurate respiration monitoring system, named <i>Wi-Cyclops</i>, which captures CSI changes induced by respiratory movements only via one antenna on commercial WiFi devices. To push the limits of effective sensing distance, we innovatively supply a new perspective to review the CSI samples along the sub-carrier dimension. From this dimension, we find that the interrelationship between sub-carriers with different timestamps still shows a high correlation even though the SNR decreases. Based on that, we analyze the noise characteristics along the sub-carrier dimension and correspondingly design a series of denoising schemes. Specifically, we carefully design a PCA-based denoising method to filter out ambient noises. After that, considering the low distribution densities of the AGC-induced noise, we then remove it by optimizing the DBSCAN denoising method with the K-Means-based adaptive radius search. Extensive experiments demonstrate that our system can work effectively in three typical family scenarios. <i>Wi-Cyclops</i> can achieve 98% accuracy even when the person is 7 m away from the transceiver pair. Compared with the start-of-art single-antenna-based approaches in real scenarios, <i>Wi-Cyclops</i> can improve the sensing range from 3 m to 7 m, which can meet the requirements of room-scale respiration monitoring. Additionally, to show the high compatibility with smart home devices, <i>Wi-Cyclops</i> is deployed on seven commercial IoT devices and still achieves a low average absolute error with 0.41 bpm.</p>","PeriodicalId":50910,"journal":{"name":"ACM Transactions on Sensor Networks","volume":"16 1","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Sensor Networks","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3632958","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Recent years have witnessed the emerging development of single-antenna wireless respiration detection that can be integrated into IoT devices with a single transceiver chain. However, existing single-antenna-based solutions are all limited by the short sensing range within 2-4 m due to noise interference, which makes them difficult to be adopted in most room-scale scenarios. To deal with this dilemma, we propose a room-scale, noise-resistance, and accurate respiration monitoring system, named Wi-Cyclops, which captures CSI changes induced by respiratory movements only via one antenna on commercial WiFi devices. To push the limits of effective sensing distance, we innovatively supply a new perspective to review the CSI samples along the sub-carrier dimension. From this dimension, we find that the interrelationship between sub-carriers with different timestamps still shows a high correlation even though the SNR decreases. Based on that, we analyze the noise characteristics along the sub-carrier dimension and correspondingly design a series of denoising schemes. Specifically, we carefully design a PCA-based denoising method to filter out ambient noises. After that, considering the low distribution densities of the AGC-induced noise, we then remove it by optimizing the DBSCAN denoising method with the K-Means-based adaptive radius search. Extensive experiments demonstrate that our system can work effectively in three typical family scenarios. Wi-Cyclops can achieve 98% accuracy even when the person is 7 m away from the transceiver pair. Compared with the start-of-art single-antenna-based approaches in real scenarios, Wi-Cyclops can improve the sensing range from 3 m to 7 m, which can meet the requirements of room-scale respiration monitoring. Additionally, to show the high compatibility with smart home devices, Wi-Cyclops is deployed on seven commercial IoT devices and still achieves a low average absolute error with 0.41 bpm.
期刊介绍:
ACM Transactions on Sensor Networks (TOSN) is a central publication by the ACM in the interdisciplinary area of sensor networks spanning a broad discipline from signal processing, networking and protocols, embedded systems, information management, to distributed algorithms. It covers research contributions that introduce new concepts, techniques, analyses, or architectures, as well as applied contributions that report on development of new tools and systems or experiences and experiments with high-impact, innovative applications. The Transactions places special attention on contributions to systemic approaches to sensor networks as well as fundamental contributions.