2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)最新文献_第8页

Needle-implantable, wireless biosensor for continuous glucose monitoring 可植入针头的无线生物传感器，用于连续血糖监测

2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN) Pub Date : 2015-06-09 DOI: 10.1109/BSN.2015.7299421

Santhisagar Vaddiraju, M. Kastellorizios, Allen Legassey, D. Burgess, F. Jain, F. Papadimitrakopoulos

{"title":"Needle-implantable, wireless biosensor for continuous glucose monitoring","authors":"Santhisagar Vaddiraju, M. Kastellorizios, Allen Legassey, D. Burgess, F. Jain, F. Papadimitrakopoulos","doi":"10.1109/BSN.2015.7299421","DOIUrl":"https://doi.org/10.1109/BSN.2015.7299421","url":null,"abstract":"Unlike non-invasive and minimally invasive continuous monitoring of glucose (CGM) devices, invasive devices require less rigorous calibration and exhibit smaller subject-to-subject variability. Biorasis, Inc. and the University of Connecticut are developing a totally implantable CGM device. Glucowizzard™ is engineered at the smallest possible footprint (0.5 × 0.5 × 5 mm). This miniaturization is made possible by utilizing light both for powering and wireless communication. In addition, Glucowizzard™ utilizes “smart” hydrogel coatings intended for localized release of various tissue response modifiers for effective control of negative tissue responses. The use of light-based powering and communication together with advanced microelectronic design rules has allowed the fabrication of truly miniaturized CGM device. The drug delivery coating has enabled substantial reduction of negative tissue responses for up to 1 month in small as well as large animals (rats and minipigs). The functionality of Glucowizzard™ has been demonstrated in vivo in both rats and minipigs.","PeriodicalId":447934,"journal":{"name":"2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130388302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Real-time American Sign Language Recognition using wrist-worn motion and surface EMG sensors 使用手腕运动和表面肌电传感器的实时美国手语识别

2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN) Pub Date : 2015-06-09 DOI: 10.1109/BSN.2015.7299393

Jian Wu, Zhongjun Tian, Lu Sun, L. Estevez, R. Jafari

引用次数: 75

Novel technique for sleep apnea monitoring 睡眠呼吸暂停监测的新技术

2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN) Pub Date : 2015-06-09 DOI: 10.1109/BSN.2015.7299418

V. Sivaji, D. Bhatia, S. Prasad

引用次数: 3

BioInsights: Extracting personal data from “Still” wearable motion sensors BioInsights:从“静止的”可穿戴运动传感器中提取个人数据

2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN) Pub Date : 2015-06-01 DOI: 10.1109/BSN.2015.7299354

Javier Hernández, Daniel J. McDuff, Rosalind W. Picard

引用次数: 37

Wearable biometric authentication based on human body communication 基于人体通信的可穿戴生物识别认证

2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN) Pub Date : 2015-06-01 DOI: 10.1109/BSN.2015.7299362

Ze-dong Nie, Yuhang Liu, Changjiang Duan, Z. Ruan, Jingzhen Li, Lei Wang

{"title":"Wearable biometric authentication based on human body communication","authors":"Ze-dong Nie, Yuhang Liu, Changjiang Duan, Z. Ruan, Jingzhen Li, Lei Wang","doi":"10.1109/BSN.2015.7299362","DOIUrl":"https://doi.org/10.1109/BSN.2015.7299362","url":null,"abstract":"Human body communication (HBC) is a short-range, wireless communication in the vicinity of, or inside a human body. In this paper, biometric authentication based on capacitive coupled HBC is presented for the wearable devices. In-situ experiments were conducted with 20 volunteers to investigate the feasibility. The S21 parameters of the HBC channel from one palm to the other within the frequency range of 300 KHz-50 MHz were measured. A total of 2,561,600 data are acquired. The data are analyzed by the support vector machines (SVM) including C-SVM and nu-SVM, where 2,241,400 data are used to train the SVM model and 320,200 data are used to estimate the authentication rate. Linear, polynomial, and radial basis function (RBF) are adopted as the kernel functions, respectively. In addition, to verify whether the features in low frequency band will affect the performance of HBC authentication, the features in four frequency bands, i.e., from 300 KHz to 50 MHz, from 3.4 MHz to 50 MHz, from 5.6 MHz to 50 MHz, and from 9.6 MHz to 50 MHz are used as the biometric trait, respectively. The experiment results show that, in biometric identification mode, identification rate of 98% is achieved, and in biometric verification mode, the equal error rate (EER) is 0.24%, the average area under the curve (AUC) of receiver operating characteristic (ROC) reaches 0.9993.","PeriodicalId":447934,"journal":{"name":"2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125347564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Novel peak detection to estimate HRV using smartphone audio 新颖的峰值检测估计HRV使用智能手机音频

2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN) Pub Date : 2015-06-01 DOI: 10.1109/BSN.2015.7299378

Aditi Misra, Rohan Banerjee, A. Choudhury, Aniruddha Sinha, A. Pal

引用次数: 5

A low-power opportunistic communication protocol for wearable applications 用于可穿戴应用的低功耗机会通信协议

2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN) Pub Date : 2015-06-01 DOI: 10.1109/BSN.2015.7299387

A. Gaglione, Shanshan Chen, Benny P. L. Lo, Guang-Zhong Yang

引用次数: 1