Innovative biomedical microsystems driven by data and artificial intelligence

由数据和人工智能驱动的创新生物医学微系统

• 批准号: RGPIN-2022-03984
• 负责人: Gosselin, Benoit
• 金额: $ 4.66万
• 依托单位: Université Laval
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=754125
• 关键词: Innovative; biomedical; microsystems; driven; data

This research program is at the interface of engineering, neuroscience, assistive technology and life sciences, and addresses the world's most important questions in the field of biomedical technologies, including human performance enhancement, drug discovery, brain diseases, and aging. In particular, the focus is on the creation of new approaches to improve human performance through new smart myoelectric prostheses, and to enhance experimental neuroscience research with novel high-precision tools. In conjunction with the Canada Research Chair in Smart Biomedical Microsystems, this research will be truly enabling and will propel Canada at the forefront of the international scientific scene. Three important research aims will be covered by this program: Aim 1) Create on-chip edge AI (artificial intelligence) strategies that will allow developing closed-loop brain therapies with nearly zero latency, Aim 2) Design ultra-high-density myoelectric controllers with embedded AI providing regressive control, and Aim 3) Design the world's smallest integrated sensors providing medical-grade vital signs measurement. It should be noted that an important focus of this program is on developing in-sensor intelligence drawing from machine learning techniques to avoid latency and enhance sensor precision in Aims 1 to 3. The long-term vision of the program is to foster the creation of new groundbreaking technology drawing from medical instrumentation, material science, AI and advanced microsystems manufacturing to increase biomedical systems intelligence and functionality while pushing their miniaturization to unprecedented levels. Another long-term objective is to continue developing an excellent and inclusive training environment for researchers at all levels in the field of intelligent biomedical technologies. The research proposed in this application is extremely original and innovative and is likely to have impact by leading to groundbreaking advances in preclinical research, assistive technology, and personalized medicine. This program will potentially lead to technologies or policies addressing urgent socio-economic needs to develop better therapeutics against mood disorders, improve the quality of life of people living with a disability and contribute to make personalized medicine becoming a reality. The students involved will participate to international conferences to present their work and building their network. They will learn and develop new advanced skills to address several key challenges in biomedical technology and AI towards the development of groundbreaking devices of added value. They will also develop unique expertise in multi-technology integration, and will gain practical experience in advanced manufacturing, which will be transferred to the Canadian industry when they will take positions, or when they will interact directly with end users during or after this research.

该研究计划是在工程，神经科学，辅助技术和生命科学的接口，并解决世界上最重要的问题，在生物医学技术领域，包括人类性能增强，药物发现，脑部疾病和衰老。特别是，重点是创造新的方法，通过新的智能肌电假肢提高人类的表现，并加强实验神经科学研究与新的高精度工具。 与加拿大智能生物医学微系统研究主席一起，这项研究将真正实现，并将推动加拿大走在国际科学舞台的前列。该计划将涵盖三个重要的研究目标：目标1）创建片上边缘AI（人工智能）策略，允许开发几乎零延迟的闭环脑治疗，目标2）设计超高密度肌电控制器，嵌入式AI提供回归控制，目标3）设计世界上最小的集成传感器，提供医疗级生命体征测量。 应该注意的是，该计划的一个重要重点是从机器学习技术中开发传感器内智能，以避免延迟并提高目标1至3中的传感器精度。 该计划的长期愿景是促进从医疗仪器，材料科学，人工智能和先进的微系统制造中创造新的突破性技术，以提高生物医学系统的智能和功能，同时将其小型化推向前所未有的水平。另一个长期目标是继续为智能生物医学技术领域的各级研究人员开发一个优秀和包容性的培训环境。本申请中提出的研究极具原创性和创新性，可能会通过在临床前研究，辅助技术和个性化医疗方面取得突破性进展而产生影响。该计划将可能导致技术或政策解决紧迫的社会经济需求，以开发更好的治疗情绪障碍的方法，提高残疾人的生活质量，并有助于使个性化医疗成为现实。参与的学生将参加国际会议，介绍他们的工作和建立自己的网络。他们将学习和发展新的先进技能，以应对生物医学技术和人工智能领域的几个关键挑战，从而开发具有附加值的开创性设备。他们还将在多技术集成方面发展独特的专业知识，并将获得先进制造业的实践经验，这些经验将在他们担任职位时转移到加拿大行业，或者在研究期间或之后与最终用户直接互动时转移到加拿大行业。