Field Based Gait Monitoring System For the Elderly

描述（由申请人提供）：方便和客观的步态评估对于老年人的健康管理非常重要。客观地测量步态功能和移动性可以评估锻炼或康复计划的依从性和进展，或跟踪药物的剂量和疗效。可以在诊所或实验室进行准确的测量，但实地测量将大大有助于健康管理。不幸的是，几乎没有办法在家中以合理的成本准确地进行真实世界的长期评估。微型传感器在精度和功率经济性方面正在迅速提高，为基于现场的活动评估提供了巨大的潜力。简单的基于加速计的步数计已被证明非常准确，而小型化的无线系统（如Nike+iPod Sport Kit）可提供足够精确的跑步速度和距离估计，供休闲使用，同时保持足够的低调，便于长时间佩戴。然而，研究或临床流动性评估的要求超过了现有系统的要求。几种融合技术使高精度、微型、惯性传感器系统成为可能，包括采用小芯片封装的多轴加速度计和角速率传感器、具有内置无线传输能力的强大微处理器以及更高的存储密度。最重要的是，基于模型的传感器集成技术可以融合来自多种传感器类型的数据，并最大限度地减少漂移误差。该项目的目标是：1。开发一个基于现场的步态评估系统，该系统将整合来自连接到身体和四肢的微型惯性传感器的信息，并在船上处理这些数据，以量化步行速度，步长，步长变化和其他步态变量。我们将设计安装在鞋内的传感器包，以无线传输到安装在腰部的集成和处理单元。 2.使用同时和独立的实验室测量，在人类受试者身上测试和校准该系统。我们将使用光学运动捕捉，以评估实际的步态变量使用已知的准确性标准技术。该项目旨在评估老年人的步态，以评估跌倒风险，帮助预防跌倒，促进锻炼，诊断疾病进展和评估药物治疗。该项目将开发一套微型、可穿戴、无线传感器，可以记录长时间（> 1天）的步态活动，对日常活动的干扰最小。

DESCRIPTION (provided by applicant): Convenient and objective assessment of gait is important for health management of older adults. Measuring gait function and mobility objectively can assess adherence and progress in an exercise or rehabilitation program, or track dosage and efficacy of medication. Accurate measurements can be taken in the clinic or laboratory, but field-based measurements would greatly assist health management. Unfortunately, there is little means of accurately performing real-world, long-term assessments in the home and at reasonable cost. Miniature sensors are rapidly improving in accuracy and power economy, offering great potential for field-based activity assessment. Simple accelerometer-based pedometers have proven highly accurate for step counts, and miniaturized, wireless systems such as the Nike+Ipod Sport Kit provide estimates of running speed and distance accurate enough for casual use, while remaining unobtrusive enough to wear conveniently for long durations. The requirements of research or clinical mobility assessments, however, exceed those of current systems. Several convergent technologies make highly accurate, miniature, inertial sensor systems feasible, including multi-axis accelerometer and angular rate sensors in small chip packages, powerful microprocessors with built-in wireless transmission capabilities, and increases in memory density. Most importantly, model-based sensor integration technology makes it possible to fuse data from multiple sensor types and minimize drift error. The aims of this project are to: 1. Develop a Field-Based Gait Assessment System, which will integrate information from miniature inertial sensors attached to the body and limbs, and process these data onboard to quantify walking speed, stride length, step variability, and other gait variables. We will design the sensor packages mounted in shoes to transmit wirelessly to integration and processing unit mounted at the waist. 2. Test and calibrate this system on human subjects, using simultaneous and independent laboratory-based measurements. We will use optical motion capture to assess actual gait variables using standard techniques of known accuracy. This project seeks to evaluate the gait of elderly individuals to assess fall risk, aid fall prevention, promote exercise, diagnose disease progression, and evaluate medication. This project will develop a set of miniature, wearable, wireless sensors that can record gait activity over long periods of time (> 1 day) with minimal interference with daily activity.