... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks最新文献

英文中文

SLAE6: Secure and Lightweight Authenticated Encryption Scheme for 6LoWPAN Networks SLAE6: 6LoWPAN网络的安全轻量级认证加密方案

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2023-01-01 DOI: 10.5220/0011632200003399

Fatma Foad Ashrif, Elankovan Sundarajan, Rami Ahmed, M Zahid Hasan

引用次数: 5

A Low-Cost Sensors Study Measuring Exposure to Particulate Matter in Mobility Situations 低成本传感器在移动环境中测量暴露于颗粒物的研究

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2023-01-01 DOI: 10.5220/0011747600003399

Marie-Laure Aix, Mélaine Claitte, D. Bicout

引用次数: 0

TSCH Slotframe Optimization Using Differential Evolution Algorithm for Heterogeneous Sensor Networks 基于差分进化算法的异构传感器网络TSCH槽帧优化

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2023-01-01 DOI: 10.5220/0011623400003399

Aida Vatankhah, R. Liscano, Tarana Ara

引用次数: 0

SmartAct: Energy Efficient and Real-Time Hand-to-Mouth Gesture Detection Using Wearable RGB-T. SmartAct:使用可穿戴RGB-T的节能实时手对嘴手势检测。

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2022-09-01 DOI: 10.1109/bsn56160.2022.9928492

Soroush Shahi, Mahdi Pedram, Glenn Fernandes, Nabil Alshurafa

Researchers have been leveraging wearable cameras to both visually confirm and automatically detect individuals' eating habits. However, energy-intensive tasks such as continuously collecting and storing RGB images in memory, or running algorithms in real-time to automate detection of eating, greatly impacts battery life. Since eating moments are spread sparsely throughout the day, battery life can be mitigated by recording and processing data only when there is a high likelihood of eating. We present a framework comprising a golf-ball sized wearable device using a low-powered thermal sensor array and real-time activation algorithm that activates high-energy tasks when a hand-to-mouth gesture is confirmed by the thermal sensor array. The high-energy tasks tested are turning on the RGB camera (Trigger RGB mode) and running inference on an on-device machine learning model (Trigger ML mode). Our experimental setup involved the design of a wearable camera, 6 participants collecting 18 hours of data with and without eating, the implementation of a feeding gesture detection algorithm on-device, and measures of power saving using our activation method. Our activation algorithm demonstrates an average of at-least 31.5% increase in battery life time, with minimal drop of recall (5%) and without impacting the accuracy of detecting eating (a slight 4.1% increase in F1-Score).

研究人员一直在利用可穿戴摄像头从视觉上确认和自动检测个人的饮食习惯。然而，诸如在内存中持续收集和存储RGB图像，或实时运行算法以自动检测进食等高能耗任务，会极大地影响电池寿命。由于一天中吃饭的时间很少，所以只有在很可能吃东西的时候才记录和处理数据，从而缩短电池寿命。我们提出了一个框架，包括一个高尔夫球大小的可穿戴设备，使用低功率热传感器阵列和实时激活算法，当热传感器阵列确认手对嘴的手势时，激活高能任务。测试的高能任务是打开RGB相机(触发RGB模式)和在设备上的机器学习模型(触发ML模式)上运行推理。我们的实验设置包括设计一个可穿戴相机，6名参与者在进食和不进食的情况下收集18小时的数据，在设备上实现进食手势检测算法，以及使用我们的激活方法节省电力的措施。我们的激活算法显示电池寿命平均至少增加31.5%，召回率最小(5%)，并且不影响检测饮食的准确性(F1-Score略有增加4.1%)。

{"title":"SmartAct: Energy Efficient and Real-Time Hand-to-Mouth Gesture Detection Using Wearable RGB-T.","authors":"Soroush Shahi, Mahdi Pedram, Glenn Fernandes, Nabil Alshurafa","doi":"10.1109/bsn56160.2022.9928492","DOIUrl":"https://doi.org/10.1109/bsn56160.2022.9928492","url":null,"abstract":"<p><p>Researchers have been leveraging wearable cameras to both visually confirm and automatically detect individuals' eating habits. However, energy-intensive tasks such as continuously collecting and storing RGB images in memory, or running algorithms in real-time to automate detection of eating, greatly impacts battery life. Since eating moments are spread sparsely throughout the day, battery life can be mitigated by recording and processing data only when there is a high likelihood of eating. We present a framework comprising a golf-ball sized wearable device using a low-powered thermal sensor array and real-time activation algorithm that activates high-energy tasks when a hand-to-mouth gesture is confirmed by the thermal sensor array. The high-energy tasks tested are turning on the RGB camera (Trigger RGB mode) and running inference on an on-device machine learning model (Trigger ML mode). Our experimental setup involved the design of a wearable camera, 6 participants collecting 18 hours of data with and without eating, the implementation of a feeding gesture detection algorithm on-device, and measures of power saving using our activation method. Our activation algorithm demonstrates an average of at-least 31.5% increase in battery life time, with minimal drop of recall (5%) and without impacting the accuracy of detecting eating (a slight 4.1% increase in F1-Score).</p>","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":"2022 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10176499/pdf/nihms-1889783.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9460562","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}

引用次数: 2

IoT Application for Monitoring and Storage of Temperature History in Electric Motors 物联网应用于电机温度历史的监测和存储

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2022-01-01 DOI: 10.5220/0010818300003118

Jairovan Denis de Paiva, Carlos Roberto Silveira Junior, Arquimedes Lopes da Silva

引用次数: 0

Semantic Segmentation of Retinal Blood Vessels from Fundus Images by using CNN and the Random Forest Algorithm 基于CNN和随机森林算法的眼底图像视网膜血管语义分割

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2022-01-01 DOI: 10.5220/0010911800003118

Ayoub Skouta, Abdelali Elmoufidi, Said Jai-Andaloussi, O. Ouchetto

Abstract: In this paper, we present a new study to improve the automated segmentation of blood vessels in diabetic retinopathy images. Pre-processing is necessary due to the contrast between the blood vessels and the background, as well as the uneven illumination of the retinal images, in order to produce better quality data to be used in further processing. We use data augmentation techniques to increase the amount of accessible data in the dataset to overcome the data sparsity problem that deep learning requires. We then use the CNN VGG16 architecture to extract the feature from the preprocessed background images. The Random Forest method will then use the extracted attributes as input parameters. We used part of the augmented dataset to train the model (1764 images, representing the training set); the rest of the dataset will be used to test the model (196 images, representing the test set). Regarding the model validation phase, we used the dedicated part for testing the DRIVE dataset. Promising results compared to the state of the art were obtained. The method achieved an accuracy of 98.7%, a sensitivity of 97.4% and specificity of 99.5%. A comparison with some recent previous work in the literature has shown a significant advancement in our proposal.

摘要:本文提出了一种改进糖尿病视网膜病变图像血管自动分割的新方法。由于血管和背景之间的对比度，以及视网膜图像的光照不均匀，预处理是必要的，以便产生更好质量的数据，用于进一步处理。我们使用数据增强技术来增加数据集中可访问数据的数量，以克服深度学习所需的数据稀疏性问题。然后，我们使用CNN VGG16架构从预处理的背景图像中提取特征。然后随机森林方法将使用提取的属性作为输入参数。我们使用增强数据集的一部分来训练模型(1764张图像，代表训练集);数据集的其余部分将用于测试模型(196张图像，代表测试集)。关于模型验证阶段，我们使用专用部分来测试DRIVE数据集。与目前的技术水平相比，取得了令人满意的结果。准确度为98.7%，灵敏度为97.4%，特异度为99.5%。与文献中最近的一些先前工作的比较显示了我们的建议的重大进步。

{"title":"Semantic Segmentation of Retinal Blood Vessels from Fundus Images by using CNN and the Random Forest Algorithm","authors":"Ayoub Skouta, Abdelali Elmoufidi, Said Jai-Andaloussi, O. Ouchetto","doi":"10.5220/0010911800003118","DOIUrl":"https://doi.org/10.5220/0010911800003118","url":null,"abstract":"Abstract: In this paper, we present a new study to improve the automated segmentation of blood vessels in diabetic retinopathy images. Pre-processing is necessary due to the contrast between the blood vessels and the background, as well as the uneven illumination of the retinal images, in order to produce better quality data to be used in further processing. We use data augmentation techniques to increase the amount of accessible data in the dataset to overcome the data sparsity problem that deep learning requires. We then use the CNN VGG16 architecture to extract the feature from the preprocessed background images. The Random Forest method will then use the extracted attributes as input parameters. We used part of the augmented dataset to train the model (1764 images, representing the training set); the rest of the dataset will be used to test the model (196 images, representing the test set). Regarding the model validation phase, we used the dedicated part for testing the DRIVE dataset. Promising results compared to the state of the art were obtained. The method achieved an accuracy of 98.7%, a sensitivity of 97.4% and specificity of 99.5%. A comparison with some recent previous work in the literature has shown a significant advancement in our proposal.","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":"5 1","pages":"163-170"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79854395","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: 4

Underwater Wireless Sensor Networks: A Review 水下无线传感器网络:综述

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2022-01-01 DOI: 10.5220/0010970700003118

Mohammad Alsulami, Rafaat Elfouly, Reda Ammar

Several disciplines like science, engineering, and biological industry have been influenced by sensor networks which have brought sensing and computation into reality. The possibility of having these sensors physically assigned close to the target whose parameters are to be observed enables remote monitoring of various aspects of the physical world. Wireless channeling of information beneath the ocean or generally underwater has provided the best technological ways of oceanic observations. Ocean bottoms have been monitored traditionally by deploying oceanographic sensors that obtain information at distinct and fixed ocean zones. The oceanographic instruments are then recovered when the tasks are completed. This implies that data cannot be monitored remotely since there is no collaborative communication of obtained data between the collection point and the monitoring end. The data recorded can also be destroyed in case of a non-successful mission. Oceanic observations have been made primarily possible by sensor networks carefully laid out under the waters. Underwater sensor networks can also be achieved wirelessly by establishing communications between sensors and monitors without major cabling. These are known as Underwater Wireless Sensor Networks (UWSNs). The UWSNs are comprised of various gadgets like vehicles that can operate autonomously under the water and sensors. Deployment of these gadgets is done in targeted acoustic zones for the collection of data and monitoring tasks. Bilateral communication is established between stations based on the ground and different UWSNs nodes. This enables instantaneous remote monitoring and communication of information from the specified oceanic zones to engineering personnel based on the shores. This paper looks at the various aspects of Underwater Wireless Sensor Networks UWSNs including their importance, applications, network architecture, requirements, and challenges and in their deployments.

许多学科，如科学、工程和生物工业都受到传感器网络的影响，传感器网络使传感和计算成为现实。将这些传感器物理地布置在要观察其参数的目标附近的可能性，使对物理世界的各个方面进行远程监测成为可能。在海底或一般在水下进行信息的无线传输为海洋观测提供了最好的技术手段。传统上，海底监测是通过部署海洋传感器来获取不同和固定海洋区域的信息。当任务完成后，海洋仪器将被回收。这意味着不能远程监控数据，因为在收集点和监控端之间没有获得数据的协作通信。如果任务不成功，记录的数据也可以销毁。海洋观测主要是通过精心布置在水下的传感器网络实现的。水下传感器网络也可以通过在传感器和监测器之间建立无线通信来实现，而不需要主要的电缆。这些被称为水下无线传感器网络(UWSNs)。UWSNs由各种小装置组成，如可以在水下自主操作的车辆和传感器。这些设备部署在目标声学区域，用于收集数据和监测任务。基于地面的站点与不同uwsn节点之间建立双边通信。这使得从指定的海洋区域向岸上的工程人员进行即时远程监测和信息通信成为可能。本文研究了水下无线传感器网络uwsn的各个方面，包括它们的重要性、应用、网络架构、需求和挑战以及它们的部署。

{"title":"Underwater Wireless Sensor Networks: A Review","authors":"Mohammad Alsulami, Rafaat Elfouly, Reda Ammar","doi":"10.5220/0010970700003118","DOIUrl":"https://doi.org/10.5220/0010970700003118","url":null,"abstract":"Several disciplines like science, engineering, and biological industry have been influenced by sensor networks which have brought sensing and computation into reality. The possibility of having these sensors physically assigned close to the target whose parameters are to be observed enables remote monitoring of various aspects of the physical world. Wireless channeling of information beneath the ocean or generally underwater has provided the best technological ways of oceanic observations. Ocean bottoms have been monitored traditionally by deploying oceanographic sensors that obtain information at distinct and fixed ocean zones. The oceanographic instruments are then recovered when the tasks are completed. This implies that data cannot be monitored remotely since there is no collaborative communication of obtained data between the collection point and the monitoring end. The data recorded can also be destroyed in case of a non-successful mission. Oceanic observations have been made primarily possible by sensor networks carefully laid out under the waters. Underwater sensor networks can also be achieved wirelessly by establishing communications between sensors and monitors without major cabling. These are known as Underwater Wireless Sensor Networks (UWSNs). The UWSNs are comprised of various gadgets like vehicles that can operate autonomously under the water and sensors. Deployment of these gadgets is done in targeted acoustic zones for the collection of data and monitoring tasks. Bilateral communication is established between stations based on the ground and different UWSNs nodes. This enables instantaneous remote monitoring and communication of information from the specified oceanic zones to engineering personnel based on the shores. This paper looks at the various aspects of Underwater Wireless Sensor Networks UWSNs including their importance, applications, network architecture, requirements, and challenges and in their deployments.","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":"5 1","pages":"202-214"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86815337","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: 13

A Novel Energy-efficient Wormhole Attack Prevention Protocol for WSN based on Trust and Reputation Factors 一种基于信任和声誉因子的无线传感器网络节能虫洞攻击防御协议

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2022-01-01 DOI: 10.5220/0010951400003118

Saad Al-Ahmadi

The deployment of Wireless Sensor Networks (WSNs) for the Internet of Things (IoT) is important, but this also poses some security issues. Wireless Sensor Networks (WSNs) are vulnerable to various attacks, such as the Wormhole attack. The Wormhole attack is one of the most severe attacks on WSNs that is particularly challenging to defend against even when the communication is authentic, and sensors are not compromised. Existing techniques to detect and protect against Wormhole attacks place a substantial burden on the scarce sensor resources and do not consider the dynamic nature of the network. In this paper, a novel Energy Efficient Wormhole Attack Prevention Protocol (EWATR) is proposed to protect WSNs against Wormhole attacks. EWATR is based on trust and reputation among WSN nodes that consider the dynamic nature of the network. This study also compares EWATR against several state-of-the-art trust and reputation models through extensive simulations using the TRMSim-WSN simulator. Eventually, the simulation results show the superiority of EWATR over other proposed protocols in terms of efficient energy consumption and shorter

为物联网(IoT)部署无线传感器网络(wsn)非常重要，但这也带来了一些安全问题。无线传感器网络容易受到各种攻击，如虫洞攻击。虫洞攻击是对wsn最严重的攻击之一，即使在通信是真实的，传感器没有受到损害的情况下，也特别难以防御。现有的检测和防御虫洞攻击的技术对稀缺的传感器资源造成了沉重的负担，并且没有考虑到网络的动态性。为了保护无线传感器网络免受虫洞攻击，提出了一种新的能量高效虫洞攻击防御协议(EWATR)。EWATR基于WSN节点之间的信任和声誉，考虑了网络的动态性。本研究还通过使用TRMSim-WSN模拟器进行广泛的仿真，将EWATR与几种最先进的信任和声誉模型进行了比较。最后，仿真结果表明了EWATR协议在高效能耗和较短时间上优于其他协议

{"title":"A Novel Energy-efficient Wormhole Attack Prevention Protocol for WSN based on Trust and Reputation Factors","authors":"Saad Al-Ahmadi","doi":"10.5220/0010951400003118","DOIUrl":"https://doi.org/10.5220/0010951400003118","url":null,"abstract":"The deployment of Wireless Sensor Networks (WSNs) for the Internet of Things (IoT) is important, but this also poses some security issues. Wireless Sensor Networks (WSNs) are vulnerable to various attacks, such as the Wormhole attack. The Wormhole attack is one of the most severe attacks on WSNs that is particularly challenging to defend against even when the communication is authentic, and sensors are not compromised. Existing techniques to detect and protect against Wormhole attacks place a substantial burden on the scarce sensor resources and do not consider the dynamic nature of the network. In this paper, a novel Energy Efficient Wormhole Attack Prevention Protocol (EWATR) is proposed to protect WSNs against Wormhole attacks. EWATR is based on trust and reputation among WSN nodes that consider the dynamic nature of the network. This study also compares EWATR against several state-of-the-art trust and reputation models through extensive simulations using the TRMSim-WSN simulator. Eventually, the simulation results show the superiority of EWATR over other proposed protocols in terms of efficient energy consumption and shorter","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":"21 1","pages":"191-201"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86324565","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: 0

Reaction-Diffusion Inspired Sensor Networking: From Theory to Application 反应扩散启发的传感器网络:从理论到应用

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2022-01-01 DOI: 10.5220/0010993300003118

Shu-Yuan Wu, T. Brown, Hsien-Tseng Wang

: Alan Turing introduced a novel Reaction-Diffusion (RD) model in 1952 to explain biological pattern formation found in animals. Since then, studies based on the RD model have long proved the feasibility of adapting it to spatial patern formation in distributed systems, especially in networking systems. In the past two decades, RD mechanism started being applied to Wireless Sensor Networks, and the possiblity of expanding to new applications is promising. In this paper, we ﬁrst review the original RD model and further show its variants, known as activator-inhibitor models. Several research efforts on applying them to model tasks in wireless sensor networks will be presented and summarized.

艾伦·图灵在1952年提出了一个新的反应-扩散(RD)模型来解释动物体内生物模式的形成。此后，基于RD模型的研究早已证明了将其应用于分布式系统，特别是网络系统中空间模式形成的可行性。在过去的二十年中，研发机制开始应用于无线传感器网络，并有可能扩展到新的应用领域。在本文中，我们首先回顾了原始的RD模型，并进一步展示了它的变体，即活化剂-抑制剂模型。本文将介绍和总结几种应用于无线传感器网络建模任务的研究成果。

引用次数: 0

Flexigy Smart-grid Architecture 灵活的智能电网架构

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2022-01-01 DOI: 10.5220/0010918400003118

Tiago Fonseca, Luís Ferreira, L. Klein, J. Landeck, P. Sousa

The electricity field is facing major challenges in the implementation of Renewable Energy Sources (RES) at a large scale. End users are taking on the role of electricity producers and consumers simultaneously (prosumers), acting like Distributed Energy Resources (DER), injecting their excess electricity into the grid. This challenges the management of grid load balance, increases running costs, and is later reflected in the tariffs paid by consumers, thus threatening the widespread of RES. The Flexigy project explores a solution to this topic by proposing a smart-grid architecture for day-ahead flexibility scheduling of individual and Renewable Energy Community (REC) resources. Our solution is prepared to allow Transmission System Operators (TSO) to request Demand Response (DR) services in emergency situations. This paper overviews the grid balance problematic, introduces the main concepts of energy flexibility and DR, and focuses its content on explaining the Flexigy architecture.

电力领域在大规模实施可再生能源(RES)方面面临着重大挑战。终端用户同时扮演着电力生产者和消费者(产消者)的角色，就像分布式能源(DER)一样，将他们多余的电力注入电网。这对电网负载平衡的管理提出了挑战，增加了运行成本，并随后反映在消费者支付的电价上，从而威胁到可再生能源的广泛应用。Flexigy项目通过提出一种智能电网架构，为个人和可再生能源社区(REC)资源的日前灵活调度，探索了这一主题的解决方案。我们的解决方案准备允许传输系统运营商(TSO)在紧急情况下请求需求响应(DR)服务。本文概述了电网平衡问题，介绍了能量柔性和DR的主要概念，重点阐述了柔性体系结构。

引用次数: 2

首页上一页

下一页尾页

类型

全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

数据库

全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

期刊

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.

﹀