针对神经障碍的智能辅助技术:对人工智能,物联网和可穿戴系统进行审查,以改善患者护理
Sandeep Chouhan1, Deepika Ghai2, Ramandeep Sandhu1
1Lovely Professional University, Phagwara, India.
概括
本文审查了神经系统疾病的智能辅助技术,分类了AI,物联网和可穿戴系统. 它提出了一个框架,以提高诊断,监测和康复的临床可访问性.
科学领域:
- 神经科学和生物医学工程
- 专注于神经系统疾病和智能辅助技术的交集.
背景情况:
- 神经系统疾病影响全球数百万人,影响认知,运动和自主功能.
- 现有的辅助技术在临床部署和可访问性方面面临挑战.
研究的目的:
- 系统地审查和分类用于神经疾病的智能辅助技术.
- 建立神经辅助研究的统一分类.
- 提出一个框架,以提高神经辅助解决方案的临床可访问性.
主要方法:
- 使用布尔运算符和PRISMA对齐选的系统文献搜索.
- 分析了154篇同行评审的文章.
- 智能辅助技术架构在四个维度中的分类.
主要成果:
- 确定了三种主要的智能辅助技术:基于人工智能,基于物联网和可穿戴系统.
- 评估的绩效指标 (DR%,PR%,RR%,PT) 和基准数据集.
- 突出了诸如多式联运融合挑战和数据隐私等局限性.
结论:
- 智能辅助技术为神经疾病管理提供了巨大的潜力.
- 提出了一个前性框架,以改善临床可访问性.
- 倡导用于先进诊断,监测和康复的连接,智能和自适应系统.
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