论文标题
Mywear:连续身体重要监控和紧急警报的智能磨损
MyWear: A Smart Wear for Continuous Body Vital Monitoring and Emergency Alert
论文作者
论文摘要
由医疗技术系统(H-CP)建立的智能医疗保健(H-CPS)比以前变得越来越重要。与电子健康记录(EHR)和AI分析相同,医疗设备及其通过Internet进行了连接,这使H-CPS成为可能。可穿戴设备和植入物等设备是基于H-CPS的智能医疗保健的关键。智能服装是一种特定的可穿戴设备,可用于智能医疗保健。有各种智能服装可帮助用户实时监测其身体生命力。许多市售服装收集了重要数据,并将其传输到移动应用程序以进行可视化。但是,这些并没有为用户理解其健康状况的实时分析。另外,此类服装不包括在警报系统中,以提醒用户和联系人在紧急情况下。在Mywear中,我们提出了可穿戴的身体重要监测服装,该服装可捕获生理数据并自动分析此类心率,压力水平,肌肉活动以检测异常。生理数据的副本将传输到云中,以检测心跳中的任何异常,并预测未来的任何潜在心力衰竭。我们还提出了一个深层神经网络(DNN)模型,该模型会自动对心跳异常和潜在的心力衰竭进行分类。为了在这种情况下立即提供帮助,我们提出了一个警报系统,该系统向附近的医务官员发送警报。拟议的Mywear的平均准确性为96.9%,对于检测异常的精度为97.3%。
Smart healthcare which is built as healthcare Cyber-Physical System (H-CPS) from Internet-of-Medical-Things (IoMT) is becoming more important than before. Medical devices and their connectivity through Internet with alongwith the electronics health record (EHR) and AI analytics making H-CPS possible. IoMT-end devices like wearables and implantables are key for H-CPS based smart healthcare. Smart garment is a specific wearable which can be used for smart healthcare. There are various smart garments that help users to monitor their body vitals in real-time. Many commercially available garments collect the vital data and transmit it to the mobile application for visualization. However, these don't perform real-time analysis for the user to comprehend their health conditions. Also, such garments are not included with an alert system to alert users and contacts in case of emergency. In MyWear, we propose a wearable body vital monitoring garment that captures physiological data and automatically analyses such heart rate, stress level, muscle activity to detect abnormalities. A copy of the physiological data is transmitted to the cloud for detecting any abnormalities in heart beats and predict any potential heart failure in future. We also propose a deep neural network (DNN) model that automatically classifies abnormal heart beat and potential heart failure. For immediate assistance in such a situation, we propose an alert system that sends an alert message to nearby medical officials. The proposed MyWear has an average accuracy of 96.9% and precision of 97.3% for detection of the abnormalities.