Multisensor Systems for Physical Activity Monitoring and Assessment

大多数加拿大人没有意识到定期体育活动的好处，包括增加能量，更好地放松，增强力量和耐力，改善体重管理，最重要的是，减少许多慢性病和疾病的风险。在没有专家或教练的情况下，对许多参加运动的人来说，一个持续的挑战是知道他们做的事情是否正确——在获得高强度运动的好处的同时将受伤的风险降到最低。为此，拟议的研究项目侧重于解决与无障碍技术开发相关的工程挑战，以指导和支持个人的身体健康活动。为了应对这些挑战，建议研究的短期目标如下：1。根据可穿戴传感器的实时图像和数据，正确识别个人正在进行的特定身体活动。机器学习方法将被开发出来，以实时识别练习。2. 开发能够从各种传感器准确估计身体活动期间使用的能量的指标。将确定最优的传感器集，并开发新的能量消耗估算模型。3. 开发能够评估和量化由个人执行的活动与应该如何完成的活动的密切程度的技术和度量标准。运动模型将与指示关节水平运动质量的指标一起开发。4. 设计和评估基于触觉的最佳方法，以便在身体活动期间向个人提供反馈。将探索各种执行器配置和刺激模式，以确定为运动指导提供触觉提示的最佳方式。未来5年的研究成果将对系统和方法的发展做出重大贡献，这些系统和方法可以解释视觉和可穿戴传感器数据，从而在身体活动期间提供见解和可操作的反馈。它们将共同提供额外的工具，支持更广泛的举措，以提高活动水平。从长远来看，拟议中的研究将带来可获得的技术，帮助人们在没有健康专家、培训师或教练在场的情况下安全有效地进行体育活动。为了使拟议的工作取得成功，在雇用研究人员、招募参与者、分析数据以及开发和翻译技术时，将考虑公平性、多样性和包容性标准。将采取协作方法来考虑用户和其他关键利益相关者的需求。

Most Canadians are not realizing the benefits of regular physical activity, including increased energy, better relaxation, increased strength and stamina, improved weight management, and, most importantly, a reduced risk of many chronic conditions and diseases. In the absence of an expert or a coach, a persistent challenge for many engaging in activity is knowing whether they are doing things correctly-gaining the benefits of higher intensity exercise while minimizing the risk of injury. For this purpose, the proposed research program is focused on solving the engineering challenges associated with the development of accessible technologies to guide and support individuals in their physical fitness activities. To address these challenges, the short-term objectives of the proposed research are as follows: 1. To correctly identify specific physical activities that individuals are doing based on real-time images and data from wearable sensors. Machine learning methods will be developed to robustly discriminate exercises in real time. 2. To develop metrics that can accurately estimate the energy used during physical activities from a variety of sensors. The optimal set of sensors will be determined and new models for energy expenditure estimation will be developed. 3. To develop techniques and metrics that can assess and quantify how closely activities performed by an individual compare to how they should be done. Motion models will be developed along with metrics that indicate motion quality at the joint level. 4. To design and evaluate the best haptics-based approaches to provide feedback to an individual during physical activity. A variety of actuator configurations and stimulation patterns will be explored to determine the best way to deliver haptic cues for exercise guidance. The outcomes of the proposed research over the next 5 years will lead to significant contributions in the development of systems and methods that can interpret visual and wearable sensor data to provide insights and actionable feedback during physical activity. Together, they will provide additional tools to support broader initiatives to increase activity levels. In the long term, the proposed research will result in accessible technologies that help people engage in physical activity safely and effectively without the presence of a health expert, trainer, or coach. To succeed with the proposed work, equity, diversity, and inclusion criteria will be considered when hiring research personnel, when recruiting participants, when analyzing the data, and in the development and translation of the technology. A collaborative approach will be taken to consider the needs of the users and other key stakeholders.