Performance analysis and biomechanical power estimation using a novel lower-limb wearable sensing system

使用新型下肢可穿戴传感系统进行性能分析和生物力学功率估计

• 批准号: 485298-2015
• 负责人: Ahmadi, Mojtaba
• 金额: $ 1.82万
• 依托单位: Carleton University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=584852
• 关键词: Performance; analysis; biomechanical; power; estimation

Wearable technology is experiencing very rapid growth in terms of new applications being explored and the number of wearable devices sold in the market. Applications range from virtual reality to health and fitness. Activity, fitness, and athletics-related devices are one of the most dominant categories of wearable devices. Based on academic research conducted over a number of years, Gesturelogic (GL) is commercializing the LEO wearable system for health and fitness activities with a focus on lower limb and initial application in biking. An investment raise of approximately $1.9M in 2014 from OCE and angel investors has provided GL with the working capital to bring LEO to market as quickly as possible. LEO features an integrated sensing and processing system used in the form of a thigh band. It can track both motion and muscle activity using surface electromyographyic (EMG)signals. Given its unique form factor it can be worn on the thigh, thus enabling a novel sensor for walking, running, cycling, and generally any activity utilizing lower limbs. This project initiates a collaborative investigation between Carleton University's Advanced Biomechatronics Laboratory and Gesturelogic Inc (GL) to conduct two research modules that are important in validating and enhancing the LEO system: (1) Sensor performance analysis funded by an OCE-VIP grant This project consists of an experimental study to better understand LEO's novel EMG sensor, develop custom real-time and post-processing techniques to improve signal quality, and investigate the impact of varying environmental and biomechanical conditions on sensor performance. Data will be collected and analyzed to make recommendation for improvements on the product and the embedded processing techniques. (2) Biomechcanical power estimation funded by an NSERC Engage grant GL is interested in exploring the potential to use a single wearable device, at the thigh with possible inertial and EMG sensing capabilities, to estimate the users biomechanical power output while biking. It is proposed to combine the measured accelerations and EMG signals from the thigh muscles together with simple kinematics and dynamics (or inverse kinematics and dynamics) models of the human legs and pedaling system to come up with a real-time estimator for the output power. The research includes proposing appropriate algorithms to fuse information, define and conduct pilot studies, and experimentally validate the proposed methods. Successful execution of these research efforts will result in validation of GL's new sensing system, product modifications, and new product features, which together can strengthen LEO's already deep technology.

可穿戴技术正在经历非常快速的增长，在新的应用程序正在探索和数量的 市场上销售的可穿戴设备。应用范围从虚拟现实到健康和健身。活动、健身和运动相关设备是可穿戴设备的最主要类别之一。基于学术研究 Gesturelogic（GL）进行了多年的研究，正在将用于健康和健身的LEO可穿戴系统商业化 活动，重点放在下肢和骑自行车的初步应用。2014年投资约190万美元， OCE和天使投资者为GL提供了运营资金，以尽快将LEO推向市场。Leo 其特征在于以大腿带的形式使用的集成传感和处理系统。它可以跟踪运动和肌肉 活动使用表面肌电图（EMG）信号。由于其独特的外形，它可以戴在大腿上， 能够实现用于步行、跑步、骑自行车以及通常使用下肢的任何活动的新型传感器。 该项目启动了卡尔顿大学高级生物机电一体化实验室和 Gesturelogic Inc（GL）将进行两个研究模块，这两个模块对验证和增强LEO系统非常重要： (1)由OCE-VIP赠款资助的传感器性能分析 该项目包括一项实验研究，以更好地了解LEO的新型EMG传感器，开发定制的实时和 后处理技术，以提高信号质量，并调查不同的环境和 传感器性能的生物力学条件。将收集和分析数据，以提出建议， 产品和嵌入式处理技术的改进。 (2)由NSERC Engage赠款资助的生物力学功率估计 GL有兴趣探索在大腿处使用单个可穿戴设备的潜力， 传感能力，以估计用户在骑自行车时的生物力学功率输出。建议将联合收割机 来自大腿肌肉的测量的加速度和EMG信号连同简单的运动学和动力学（或逆运动学）， 运动学和动力学）模型，以提出一个实时估计的人腿和踏板系统， 输出功率该研究包括提出适当的算法来融合信息，定义和进行试点研究， 并通过实验验证了所提出的方法。 这些研究工作的成功执行将导致GL的新传感系统的验证，产品修改， 和新的产品功能，这些都可以加强LEO已经很深的技术。