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智能医疗系统设计的移动技术(无线网络)

English | 2024 | ISBN: 3031573447 | 219 pages | True PDF,EPUB | 57.73 MB

This book offers a comprehensive examination of mobile technologies in healthcare. It starts by covering wireless solutions, including WiFi signals and mmWave technology for activity recognition, fitness assistance, and eating habit monitoring. The discussion extends to wearable technologies that focus on personal fitness and injury prevention, highlighting the innovative use of PPG sensors in wearables, which enable gesture recognition and user authentication.

Based on thorough analyses on the challenges of designing robust mobile healthcare systems, this book addresses the difficulty of gathering accurate and reliable sensor data amidst the variability of human activities. It explores solutions using advanced sensing modalities, such as WiFi, mmWave, and PPG sensors, and robust algorithms for feature extraction to interpret activities, gestures, and biometrics. It also tackles system robustness across diverse environments and practical issues such as reducing training efforts, handling motion artifacts, and the implementation of these systems using commercially available devices.

The primary audience for this book targets computer science students and researchers working in mobile computing, smart healthcare, human-computer interaction and artificial intelligence/machine learning. Professionals and consultants focused on advancing mobile-based healthcare solutions will want to purchase this book as a reference.

中文|2024|ISBN:3031573447|219页|True PDF,EPUB | 57.73 MB这本书对医疗保健中的移动技术进行了全面的考察。它首先涵盖了无线解决方案,包括用于活动识别、健身辅助和饮食习惯监测的WiFi信号和毫米波技术。讨论扩展到专注于个人健身和伤害预防的可穿戴技术,强调了PPG传感器在可穿戴设备中的创新使用,这些传感器可以实现手势识别和用户身份验证。 基于对设计稳健移动医疗系统的挑战的深入分析,本书解决了在人类活动变化中收集准确可靠的传感器数据的困难。它探索了使用WiFi、mmWave和PPG传感器等先进传感方式以及用于特征提取的稳健算法来解释活动、手势和生物识别的解决方案。它还解决了跨不同环境的系统鲁棒性和实际问题,如减少训练工作量、处理运动伪影以及使用商用设备实现这些系统。 本书的主要读者是从事移动计算、智能医疗、人机交互和人工智能/机器学习的计算机科学学生和研究人员。专注于推进基于移动的医疗保健解决方案的专业人士和顾问将希望购买这本书作为参考。
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