Wearable smart devices, such as smart watch, wristband are becoming increasingly popular recently. They generally integrate the MEMS-designed inertial sensors, including accelerometer, gyroscope and compass, which pro...Wearable smart devices, such as smart watch, wristband are becoming increasingly popular recently. They generally integrate the MEMS-designed inertial sensors, including accelerometer, gyroscope and compass, which provide a convenient and inexpensive way to collect motion data of users. Such rich, continuous motion data provide great potential for remote healthcare and decease diagnosis. Information processing algorithms play the critical role in these approaches, which is to extract the motion signatures and to access different kinds of judgements. This paper reviews key algorithms in these areas. In particular, we focus on three kinds of applications: 1) gait analysis; 2) fall detection and 3) sleep monitoring. They are the most popular healthcare applications based on the inertial data. By categorizing and introducing the key algorithms, this paper tries to build a clear map of how the inertial data are processed; how the inertial signatures are defined, extracted, and utilized in different kinds of applications. This will provide a valuable guidance for users to understand the methodologies and to select proper algorithm for specifi c application purpose.展开更多
Simple, portable analytical devices are entering our daily lives for personal care, clinical analysis, allergen detection in food, and environmental monitoring. Smart- phones, as the most popular state-of-art mobile d...Simple, portable analytical devices are entering our daily lives for personal care, clinical analysis, allergen detection in food, and environmental monitoring. Smart- phones, as the most popular state-of-art mobile device, have remarkable potential for sensing applications. A growing set of physical-co-chemical sensors have been embedded; these include accelerometers, microphones, cameras, gyroscopes, and GPS units to access and perform data analysis. In this review, we discuss recent work focusing on smartphone sensing including representative electromag- netic, audio frequency, optical, and electrochemical sen- sors. The development of these capabilities will lead to more compact, lightweight, cost-effective, flexible, and durable devices in terms of their performances.展开更多
基金supported in part by National Natural Science Foundation of China Grant 61202360, 61033001, 61361136003the National Basic Research Program of China Grant 2011CBA00300, 2011CBA00302
文摘Wearable smart devices, such as smart watch, wristband are becoming increasingly popular recently. They generally integrate the MEMS-designed inertial sensors, including accelerometer, gyroscope and compass, which provide a convenient and inexpensive way to collect motion data of users. Such rich, continuous motion data provide great potential for remote healthcare and decease diagnosis. Information processing algorithms play the critical role in these approaches, which is to extract the motion signatures and to access different kinds of judgements. This paper reviews key algorithms in these areas. In particular, we focus on three kinds of applications: 1) gait analysis; 2) fall detection and 3) sleep monitoring. They are the most popular healthcare applications based on the inertial data. By categorizing and introducing the key algorithms, this paper tries to build a clear map of how the inertial data are processed; how the inertial signatures are defined, extracted, and utilized in different kinds of applications. This will provide a valuable guidance for users to understand the methodologies and to select proper algorithm for specifi c application purpose.
文摘Simple, portable analytical devices are entering our daily lives for personal care, clinical analysis, allergen detection in food, and environmental monitoring. Smart- phones, as the most popular state-of-art mobile device, have remarkable potential for sensing applications. A growing set of physical-co-chemical sensors have been embedded; these include accelerometers, microphones, cameras, gyroscopes, and GPS units to access and perform data analysis. In this review, we discuss recent work focusing on smartphone sensing including representative electromag- netic, audio frequency, optical, and electrochemical sen- sors. The development of these capabilities will lead to more compact, lightweight, cost-effective, flexible, and durable devices in terms of their performances.
