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卫健学术沙龙:基于5G+人工智能的心理/精神健康服务与管理体系建设
Gauging spacetime inversions
AI合成化学前沿与战略研讨会暨国家智能化学数据中心启动会
Macro to micro- and nano-scale fluidic engineering for analytical chemistry
报告题目:
Smart Sensing Technologies for Chronic Disease Management
 报告人:
Yongji Fu
Algorithm development manager at Becton Dickinson 
Technologies (BDT) in Research Triangle Park of North Carolina
报告时间:
2012-12-11 15:00
报告地点:
Medical Science Building B323
主办单位:
  简介:
Abstract: Smart physiological sensing have become a powerful tool to extend healthcare services from hospital to daily life for patients with chronic diseases, to improve their life quality and reduce healthcare costs by avoiding disease exacerbation and other short term and long term consequences. Wearable sensors enable ambulatory monitoring of disease specific physiological parameters (e.g. heart rate, blood glucose, blood pressure). Acquired physiological signal is transferred through a body area network (BAN) to a central device such as a smartphone for data processing and review. Innovative signal processing algorithms are developed to overcome challenges in ambulatory monitoring such as motion artifacts and ambient noises. Patient’s disease status is estimated in real time to guide medication reminder, caregiver notification or automatic drug delivery. In this talk, a number of sensing technologies (optical, acoustical, electrical), wireless BAN communication protocols and large scale data mining, decision making and closed loop control algorithms will be reviewed. Finally, several disease management systems will be introduced to address different chronic diseases such as diabetes, asthma, and COPD.
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