可穿戴计算机
边缘计算
计算机科学
可穿戴技术
GSM演进的增强数据速率
医疗保健
人机交互
数据科学
风险分析(工程)
嵌入式系统
医学
人工智能
经济
经济增长
作者
Angela Tafadzwa Shumba,Teodoro Montanaro,Ilaria Sergi,Alessia Bramanti,Michele Ciccarelli,Antonella Rispoli,Albino Carrizzo,Massimo De Vittorio,Luigi Patrono
出处
期刊:Sensors
[MDPI AG]
日期:2023-08-03
卷期号:23 (15): 6896-6896
被引量:2
摘要
Smart wearable devices enable personalized at-home healthcare by unobtrusively collecting patient health data and facilitating the development of intelligent platforms to support patient care and management. The accurate analysis of data obtained from wearable devices is crucial for interpreting and contextualizing health data and facilitating the reliable diagnosis and management of critical and chronic diseases. The combination of edge computing and artificial intelligence has provided real-time, time-critical, and privacy-preserving data analysis solutions. However, based on the envisioned service, evaluating the additive value of edge intelligence to the overall architecture is essential before implementation. This article aims to comprehensively analyze the current state of the art on smart health infrastructures implementing wearable and AI technologies at the far edge to support patients with chronic heart failure (CHF). In particular, we highlight the contribution of edge intelligence in supporting the integration of wearable devices into IoT-aware technology infrastructures that provide services for patient diagnosis and management. We also offer an in-depth analysis of open challenges and provide potential solutions to facilitate the integration of wearable devices with edge AI solutions to provide innovative technological infrastructures and interactive services for patients and doctors.
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