Validation and application of wearable sensors for capturing kinematic responses to real-world losses of balance among balance-impaired older adults

可穿戴传感器的验证和应用，用于捕获现实世界中平衡受损老年人失去平衡的运动学反应

• 批准号: 10693380
• 负责人: Neil Alexander
• 金额: $ 22.83万
• 依托单位: VIRGINIA POLYTECHNIC INST AND ST UNIV
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10693380
• 关键词: Adherence; Age; Agreement; Algorithms; Awareness; Body measure procedure; Characteristics; Classification; Communities; Data; Development; Devices; Effectiveness; Elderly; Equilibrium; Etiology; Evaluation; Event; Exercise; Exhibits; Exposure to; Fall prevention; Frequencies; Gait; Hour; Impairment; Individual; Injury; Investigation; Knowledge; Laboratories; Laboratory Study; Life; Measurable; Measurement; Measures; Memory; Methodology; Methods; Motion; Movement; Nature; Participant; Patient Self-Report; Prevention Research; Recovery; Research Personnel; Speed; System; Techniques; Time; Touchdown; Training; Validation; Video Recording; Voice; Walking; Work; age related; balance recovery; diaries; fall risk; falls; feasibility testing; foot; hazard; improved; injury-related death; innovation; kinematics; memory recall; novel; preventive intervention; response; sensor; wearable sensor technology

The broad objective of this application is to establish a methodology to measure kinematic (i.e. bodily movement) responses to losses of balance (LOBs) in the real-world during daily life. Falls are the leading cause of injuries and injury-related deaths among older adults, with tripping and slipping being responsible for an estimated 60% of these falls. Numerous laboratory studies have shown that these falls generally result from an age-related decline in balance recovery responses to these LOBs. Unfortunately, technical challenges have limited our ability to assess LOB responses outside the lab, and therefore has allowed a disconnect to persist between lab studies of trips and slips and actual trips and slips in the real-world. We recently developed a novel technique to capture the kinematics of real-world LOBs and their context using wearable sensors and voice recorders. Aim 1 of this application will investigate the feasibility of this technique for extended use by asking balance-impaired community-dwelling older adults to wear the system daily during their waking hours for three weeks. Aim 2 will involve a laboratory validation of this technique by inducing trips and slips among Aim 1 participants while measuring LOB response kinematics simultaneously with the wearable sensor system and a gold-standard optoelectronic motion capture system. Aim 3 will use wearable sensor data from Aims 1 and 2 to begin to explore differences between real-world and laboratory LOB responses. The ability to capture detailed kinematics of LOB responses and their context in the real-world would have a profound and fundamental impact on fall prevention efforts. First, it would clarify any differences between laboratory and real-world LOBs to enhance the generalizability of lab studies to the real-world. Second, it would overcome well-known limitations of using memory recall when evaluating the frequency and characteristics of real-world falls. Third, it would greatly enhance the critical evaluation of fall prevention interventions and their mechanisms to maximize training benefits. Fourth, it would assist researchers developing algorithms to automatically detect real-world LOBs among individuals using wearable sensors.

该应用程序的主要目标是建立一种测量运动学的方法（即 身体运动）对日常生活中现实世界中失去平衡（LOB）的反应。 跌倒是老年人受伤和受伤相关死亡的主要原因，其中绊倒 据估计，其中 60% 是由滑倒造成的。众多实验室 研究表明，这些跌倒通常是由于年龄相关的平衡能力下降造成的 对这些 LOB 的恢复响应。不幸的是，技术挑战限制了我们的能力 评估实验室外的 LOB 响应，因此允许断开连接持续存在 实验室对行程和滑倒的研究与现实世界中的实际行程和滑倒之间的关系。我们最近 开发了一种新技术来捕捉现实世界 LOB 的运动学及其背景 使用可穿戴传感器和录音机。该应用程序的目标 1 将调查 通过询问平衡受损的社区住宅来扩展该技术的可行性 老年人每天醒着的时候都佩戴该系统，为期三周。目标2将 通过在目标 1 中诱导绊倒和滑倒来对该技术进行实验室验证 参与者同时使用可穿戴传感器测量 LOB 响应运动学 系统和黄金标准光电动作捕捉系统。目标 3 将使用可穿戴设备 来自目标 1 和 2 的传感器数据开始探索现实世界和 实验室 LOB 响应。能够捕获 LOB 响应的详细运动学和 他们在现实世界中的背景将对秋季产生深远而根本的影响 预防工作。首先，它将澄清实验室和现实世界之间的任何差异 LOB 可增强实验室研究对现实世界的普遍性。其次，它会 克服评估频率时使用记忆回忆的众所周知的局限性 现实世界跌倒的特征。三是大幅提升对跌倒的批判性评价。 预防干预措施及其机制，以最大限度地提高培训效益。第四，它会 协助研究人员开发算法来自动检测现实世界中的 LOB 使用可穿戴传感器的个人。