WearSys '16最新文献

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MiHub: Wearable Management for IoT MiHub:物联网可穿戴管理
WearSys '16 Pub Date : 2016-06-30 DOI: 10.1145/2935643.2935646
Kirill Varshavskiy, A. Harris, R. Kravets
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引用次数: 2
Wireless Smartphone Keyboard for Visually Challenged Users 无线智能手机键盘为视障用户
WearSys '16 Pub Date : 2016-06-30 DOI: 10.1145/2935643.2935648
Cecil D'silva, Vickram Parthasarathy, Sethuraman N. Rao
{"title":"Wireless Smartphone Keyboard for Visually Challenged Users","authors":"Cecil D'silva, Vickram Parthasarathy, Sethuraman N. Rao","doi":"10.1145/2935643.2935648","DOIUrl":"https://doi.org/10.1145/2935643.2935648","url":null,"abstract":"A Smartphone is a combination of a cell phone, a personal digital assistant (PDA), a media player, a GPS navigation unit and much more. To a blind and visually impaired (BVI) user, a Smartphone can assist and help connect with our modern day cyber social world. The only inconvenience to the BVI user is its user interface, which is a touch screen display. In this project, an economical user-friendly compact text-input device for a BVI Smartphone user is developed. This device is designed for daily use and it supports Braille text. The device is connected to the smart phone by Bluetooth interface. A Smartphone app pairs the phone with the device and switches the default keyboard service to use the device keyboard. The Smartphone operating system runs the screen reader when the keyboard is in use, giving real time audio feedback to the user. Thus, a setup for nearly seamless text input is provided to the BVI user. A low-cost Arduino based prototype has been developed as a proof of concept. As part of the future work, the prototype keyboard will be evaluated by BVI users and the results will be compared with other existing text input methods for BVI users.","PeriodicalId":345713,"journal":{"name":"WearSys '16","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134128875","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: 6
DeepSense: A GPU-based Deep Convolutional Neural Network Framework on Commodity Mobile Devices DeepSense:商用移动设备上基于gpu的深度卷积神经网络框架
WearSys '16 Pub Date : 2016-06-30 DOI: 10.1145/2935643.2935650
Huynh Nguyen Loc, R. Balan, Youngki Lee
{"title":"DeepSense: A GPU-based Deep Convolutional Neural Network Framework on Commodity Mobile Devices","authors":"Huynh Nguyen Loc, R. Balan, Youngki Lee","doi":"10.1145/2935643.2935650","DOIUrl":"https://doi.org/10.1145/2935643.2935650","url":null,"abstract":"Recently, a branch of machine learning algorithms called deep learning gained huge attention to boost up accuracy of a variety of sensing applications. However, execution of deep learning algorithm such as convolutional neural network on mobile processor is non-trivial due to intensive computational requirements. In this paper, we present our early design of DeepSense - a mobile GPU-based deep convolutional neural network (CNN) framework. For its design, we first explored the differences between server-class and mobile-class GPUs, and studied effectiveness of various optimization strategies such as branch divergence elimination and memory vectorization. Our results show that DeepSense is able to execute a variety of CNN models for image recognition, object detection and face recognition in soft real time with no or marginal accuracy tradeoffs. Experiments also show that our framework is scalable across multiple devices with different GPU architectures (e.g. Adreno and Mali).","PeriodicalId":345713,"journal":{"name":"WearSys '16","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127809745","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: 60
CryptoCoP: Lightweight, Energy-efficient Encryption and Privacy for Wearable Devices CryptoCoP:用于可穿戴设备的轻量级、节能加密和隐私
WearSys '16 Pub Date : 2016-06-30 DOI: 10.1145/2935643.2935647
Robin Snader, R. Kravets, A. Harris
{"title":"CryptoCoP: Lightweight, Energy-efficient Encryption and Privacy for Wearable Devices","authors":"Robin Snader, R. Kravets, A. Harris","doi":"10.1145/2935643.2935647","DOIUrl":"https://doi.org/10.1145/2935643.2935647","url":null,"abstract":"As people use and interact with more and more wearables and IoT-enabled devices, their private information is being exposed without any privacy protections. However, the limited capabilities of IoT devices makes implementing robust privacy protections challenging. In response, we present CryptoCoP, an energy-efficient, content agnostic privacy and encryption protocol for IoT devices. Eavesdroppers cannot snoop on data protected by CryptoCoP or track users via their IoT devices. We evaluate CryptoCoP and show that the performance and energy overheads are viable in a wide variety of situations, and can be modified to trade off forward secrecy and energy consumption against required key storage on the device.","PeriodicalId":345713,"journal":{"name":"WearSys '16","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125370517","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: 24
In-ear Biosignal Recording System: A Wearable For Automatic Whole-night Sleep Staging 入耳式生物信号记录系统:一种用于自动整夜睡眠分期的可穿戴设备
WearSys '16 Pub Date : 2016-06-30 DOI: 10.1145/2935643.2935649
Anh Nguyen, Raghda Alqurashi, Zohreh Raghebi, F. Kashani, A. Halbower, Thang N. Dinh, Tam N. Vu
{"title":"In-ear Biosignal Recording System: A Wearable For Automatic Whole-night Sleep Staging","authors":"Anh Nguyen, Raghda Alqurashi, Zohreh Raghebi, F. Kashani, A. Halbower, Thang N. Dinh, Tam N. Vu","doi":"10.1145/2935643.2935649","DOIUrl":"https://doi.org/10.1145/2935643.2935649","url":null,"abstract":"In this work, we present a low-cost and light-weight wearable sensing system that can monitor bioelectrical signals generated by electrically active tissues across the brain, the eyes, and the facial muscles from inside human ears. Our work presents two key aspects of the sensing, which include the construction of electrodes and the extraction of these biosignals using a supervised non-negative matrix factorization learning algorithm. To illustrate the usefulness of the system, we developed an autonomous sleep staging system using the output of our proposed in-ear sensing system. We prototyped the device and evaluated its sleep stage classification performance on 8 participants for a period of 1 month. With 94% accuracy on average, the evaluation results show that our wearable sensing system is promising to monitor brain, eyes, and facial muscle signals with reasonable fidelity from human ear canals.","PeriodicalId":345713,"journal":{"name":"WearSys '16","volume":"220 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123243862","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: 21
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