The structure of key-value data is a typical data structure generated by mobile devices.The collection and analysis of the data from mobile devices are critical for service providers to improve service quality.Neverth...The structure of key-value data is a typical data structure generated by mobile devices.The collection and analysis of the data from mobile devices are critical for service providers to improve service quality.Nevertheless,collecting raw data,which may contain various per⁃sonal information,would lead to serious personal privacy leaks.Local differential privacy(LDP)has been proposed to protect privacy on the device side so that the server cannot obtain the raw data.However,existing mechanisms assume that all keys are equally sensitive,which can⁃not produce high-precision statistical results.A utility-improved data collection framework with LDP for key-value formed mobile data is pro⁃posed to solve this issue.More specifically,we divide the key-value data into sensitive and non-sensitive parts and only provide an LDPequivalent privacy guarantee for sensitive keys and all values.We instantiate our framework by using a utility-improved key value-unary en⁃coding(UKV-UE)mechanism based on unary encoding,with which our framework can work effectively for a large key domain.We then vali⁃date our mechanism which provides better utility and is suitable for mobile devices by evaluating it in two real datasets.Finally,some pos⁃sible future research directions are envisioned.展开更多
Machine learning advancements in healthcare have made data collected through smartphones and wearable devices a vital source of public health and medical insights.While wearable device data help to monitor,detect,and ...Machine learning advancements in healthcare have made data collected through smartphones and wearable devices a vital source of public health and medical insights.While wearable device data help to monitor,detect,and predict diseases and health conditions,some data owners hesitate to share such sensitive data with companies or researchers due to privacy concerns.Moreover,wearable devices have been recently available as commercial products;thus large,diverse,and representative datasets are not available to most researchers.In this article,the authors propose an open marketplace where wearable device users securely monetize their wearable device records by sharing data with consumers(e.g.,researchers)to make wearable device data more available to healthcare researchers.To secure the data transactions in a privacy-preserving manner,the authors use a decentralized approach using Blockchain and Non-Fungible Tokens(NFTs).To ensure data originality and integrity with secure validation,the marketplace uses Trusted Execution Environments(TEE)in wearable devices to verify the correctness of health data.The marketplace also allows researchers to train models using Federated Learning with a TEE-backed secure aggregation of data users may not be willing to share.To ensure user participation,we model incentive mechanisms for the Federated Learning-based and anonymized data-sharing approaches using NFTs.The authors also propose using payment channels and batching to reduce smart contact gas fees and optimize user profits.If widely adopted,it’s believed that TEE and Blockchain-based incentives will promote the ethical use of machine learning with validated wearable device data in healthcare and improve user participation due to incentives.展开更多
随着物联网(Internet of Thing, IoT)和边缘计算技术的快速发展,物理设备接入互联网的规模和速度都在不断增长。这些设备不断地产生大量的数据,而物联网数据采集平台可以有效地对设备产生的数据进行采集和管理。但是,现有的物联网数据...随着物联网(Internet of Thing, IoT)和边缘计算技术的快速发展,物理设备接入互联网的规模和速度都在不断增长。这些设备不断地产生大量的数据,而物联网数据采集平台可以有效地对设备产生的数据进行采集和管理。但是,现有的物联网数据采集平台针对单一的通信协议和设备类型。为了解决上述挑战,设计了一种面向物联网环境的通用型数据采集平台,该平台由设备管理、数据采集、数据传输、数据存储以及数据分析五个模块构成。通过设计和分析各个模块的功能和交互关系,从而为物联网环境下通用型数据采集平台的实际应用提供了基础和指导。展开更多
Objectives Gerontechnology has great potential in promoting older adults’well-being.With the accelerated aging process,gerontechnology has a promising market prospect.However,most technological developers and healthc...Objectives Gerontechnology has great potential in promoting older adults’well-being.With the accelerated aging process,gerontechnology has a promising market prospect.However,most technological developers and healthcare professionals attached importance to products’effectiveness,and ignored older adults’demands and user experience,which reduced older adults'adoption intention of gerontechnology use.The inclusion of older adults in the design process of technologies is essential to maximize the effect.This study explored older adults’demands for a self-developed intelligent medication administration system and proposed optimization schemes,thus providing reference to developing geriatric-friendly technologies and products.Methods A cross-sectional survey was conducted to explore older adults’technological demands for the self-developed intelligent medication administration system,and data were analyzed based on the Kano model.A self-made questionnaire was administered from July 2020 to October 2020 after participants used this system for two weeks.The study was registered with the Chinese Clinical Trial Registry(ChiCTR2000040644).Results A total of 354 older adults participated in the survey.Four items,namely larger font size,simpler operation process,scheduled medication reminders and reliable hardware,were classified as must-be attributes;three items,namely searching drug instructions through WeChat,more sensitive system and longer battery life,as attractive attributes;one item,viewing disease-related information through WeChat,as the one-dimensional attribute;and the rest were indifferent attributes,including simple and beautiful displays,blocking advertisements automatically,providing user privacy protection protocol,viewing personal medical information only by logged-in users,recording all the medications,ordering medications through WeChat.The satisfaction values were between 0.24 and 0.69,and dissatisfaction values were between 0.06 and 0.94.Conclusion This study suggested that older adults had personalized technology demands.Including their technological demands and desire may assist in decreasing the digital divide and promoting the satisfaction of e-health and/or m-health.Based on older adults’demands,our study proposed optimization schemes of the intelligent medication administration system,which may help developers design geriatric-friendly intelligent products and nurses to perform older adults-centered and efficient medication management.展开更多
文摘The structure of key-value data is a typical data structure generated by mobile devices.The collection and analysis of the data from mobile devices are critical for service providers to improve service quality.Nevertheless,collecting raw data,which may contain various per⁃sonal information,would lead to serious personal privacy leaks.Local differential privacy(LDP)has been proposed to protect privacy on the device side so that the server cannot obtain the raw data.However,existing mechanisms assume that all keys are equally sensitive,which can⁃not produce high-precision statistical results.A utility-improved data collection framework with LDP for key-value formed mobile data is pro⁃posed to solve this issue.More specifically,we divide the key-value data into sensitive and non-sensitive parts and only provide an LDPequivalent privacy guarantee for sensitive keys and all values.We instantiate our framework by using a utility-improved key value-unary en⁃coding(UKV-UE)mechanism based on unary encoding,with which our framework can work effectively for a large key domain.We then vali⁃date our mechanism which provides better utility and is suitable for mobile devices by evaluating it in two real datasets.Finally,some pos⁃sible future research directions are envisioned.
文摘Machine learning advancements in healthcare have made data collected through smartphones and wearable devices a vital source of public health and medical insights.While wearable device data help to monitor,detect,and predict diseases and health conditions,some data owners hesitate to share such sensitive data with companies or researchers due to privacy concerns.Moreover,wearable devices have been recently available as commercial products;thus large,diverse,and representative datasets are not available to most researchers.In this article,the authors propose an open marketplace where wearable device users securely monetize their wearable device records by sharing data with consumers(e.g.,researchers)to make wearable device data more available to healthcare researchers.To secure the data transactions in a privacy-preserving manner,the authors use a decentralized approach using Blockchain and Non-Fungible Tokens(NFTs).To ensure data originality and integrity with secure validation,the marketplace uses Trusted Execution Environments(TEE)in wearable devices to verify the correctness of health data.The marketplace also allows researchers to train models using Federated Learning with a TEE-backed secure aggregation of data users may not be willing to share.To ensure user participation,we model incentive mechanisms for the Federated Learning-based and anonymized data-sharing approaches using NFTs.The authors also propose using payment channels and batching to reduce smart contact gas fees and optimize user profits.If widely adopted,it’s believed that TEE and Blockchain-based incentives will promote the ethical use of machine learning with validated wearable device data in healthcare and improve user participation due to incentives.
文摘随着物联网(Internet of Thing, IoT)和边缘计算技术的快速发展,物理设备接入互联网的规模和速度都在不断增长。这些设备不断地产生大量的数据,而物联网数据采集平台可以有效地对设备产生的数据进行采集和管理。但是,现有的物联网数据采集平台针对单一的通信协议和设备类型。为了解决上述挑战,设计了一种面向物联网环境的通用型数据采集平台,该平台由设备管理、数据采集、数据传输、数据存储以及数据分析五个模块构成。通过设计和分析各个模块的功能和交互关系,从而为物联网环境下通用型数据采集平台的实际应用提供了基础和指导。
基金Funding was provided by Chongqing Health Commission,and Chongqing Science and Technology Bureau(grant number 2020MSXM077).
文摘Objectives Gerontechnology has great potential in promoting older adults’well-being.With the accelerated aging process,gerontechnology has a promising market prospect.However,most technological developers and healthcare professionals attached importance to products’effectiveness,and ignored older adults’demands and user experience,which reduced older adults'adoption intention of gerontechnology use.The inclusion of older adults in the design process of technologies is essential to maximize the effect.This study explored older adults’demands for a self-developed intelligent medication administration system and proposed optimization schemes,thus providing reference to developing geriatric-friendly technologies and products.Methods A cross-sectional survey was conducted to explore older adults’technological demands for the self-developed intelligent medication administration system,and data were analyzed based on the Kano model.A self-made questionnaire was administered from July 2020 to October 2020 after participants used this system for two weeks.The study was registered with the Chinese Clinical Trial Registry(ChiCTR2000040644).Results A total of 354 older adults participated in the survey.Four items,namely larger font size,simpler operation process,scheduled medication reminders and reliable hardware,were classified as must-be attributes;three items,namely searching drug instructions through WeChat,more sensitive system and longer battery life,as attractive attributes;one item,viewing disease-related information through WeChat,as the one-dimensional attribute;and the rest were indifferent attributes,including simple and beautiful displays,blocking advertisements automatically,providing user privacy protection protocol,viewing personal medical information only by logged-in users,recording all the medications,ordering medications through WeChat.The satisfaction values were between 0.24 and 0.69,and dissatisfaction values were between 0.06 and 0.94.Conclusion This study suggested that older adults had personalized technology demands.Including their technological demands and desire may assist in decreasing the digital divide and promoting the satisfaction of e-health and/or m-health.Based on older adults’demands,our study proposed optimization schemes of the intelligent medication administration system,which may help developers design geriatric-friendly intelligent products and nurses to perform older adults-centered and efficient medication management.
