Wearable Sensor Networks for Interactive Applications

用于交互式应用的可穿戴传感器网络

• 批准号: RGPIN-2016-06272
• 负责人: Whitehead, Anthony
• 金额: $ 2.26万
• 依托单位: Carleton University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=616200
• 关键词: Wearable; Sensor; Networks; Interactive; Applications

This research program investigates wearable multi-sensor activity recognition and verification for humans wearing inertial measurement sensors. A body area sensor network (BASN) involves the use of various sensors to continuously monitor the physiological or biomechanical state of an individual. The development of Micro-Electro Mechanical Systems (MEMS) allow sensor sizes to be greatly reduced and newer wireless communication protocols allow wearable sensors to lightweight and practical. There are a wide range of potential areas where BASNs could play a key role. These include encouraging exercise, military applications, sports training, secure authentication, personal information sharing as well as a variety of entertainment applications. An area of intense research is in using BASNs in health care. Here they could serve a huge number of functions such as fall detection, remote monitoring, physiotherapy and recovery from acquired brain injury. The short term objectives of this program are to address key challenges in multi-sensor pattern recognition and the convergence of biomechanical and biophysical data in these pattern matching applications in either a complementary or confirmatory manner. The long term objective of this research is to contribute to the advancement of wearable wireless sensor network technologies through the next generation and beyond. The technologies resulting from the proposed research have the potential of making significant impact on the health care and personal training industries. The outcome of the proposed research also has significant potential for commercialization and technology transfer directly to the Canadian industry. The scientific approach will be based on sound research principles involving literature survey, pattern matching techniques combined with extensive analysis and application evaluation. The research will prepare a number of highly qualified personnel at the postgraduate and undergraduate level to serve the needs of the growing information and communications technologies industry in Canada.

本研究计划研究可穿戴多传感器活动识别和验证人类佩戴惯性测量传感器。体域传感器网络（BERO）涉及使用各种传感器来连续监测个体的生理或生物力学状态。微机电系统（MEMS）的发展使传感器的尺寸大大减小，新的无线通信协议使可穿戴传感器变得轻便实用。BASN可以在许多潜在领域发挥关键作用。这些应用包括鼓励锻炼、军事应用、体育训练、安全认证、个人信息共享以及各种娱乐应用。一个密集的研究领域是在医疗保健中使用BASNs。在这里，它们可以提供大量的功能，如跌倒检测，远程监控，物理治疗和后天性脑损伤的恢复。该计划的短期目标是以互补或验证的方式解决多传感器模式识别以及生物力学和生物物理数据在这些模式匹配应用中的融合方面的关键挑战。这项研究的长期目标是通过下一代及以后的可穿戴无线传感器网络技术的进步做出贡献。从拟议的研究中产生的技术有可能对医疗保健和个人培训行业产生重大影响。拟议研究的成果也具有直接向加拿大工业进行商业化和技术转让的巨大潜力。科学的方法将基于合理的研究原则，包括文献调查，模式匹配技术结合广泛的分析和应用评估。这项研究将培养一些高素质的研究生和本科生人才，以满足加拿大日益增长的信息和通信技术行业的需求。