Lockhart Thurmon E, Yeoh Han T, Soangra Rahul, Jongprasithporn Manutchanok, Zhang Jian, Wu Xuefang, Ghosh Arka
Virginia Tech Blacksburg.
Biomed Sci Instrum. 2012;48:260-7.
Falls are among the most serious accidents among the elderly leading to increased injuries, reduced functioning and mortality. In 2009, about 2.2 million nonfatal fall injuries were reported among the elderly population (CDC, 2010). In this study, eleven community dwelling elderly (aged 65-84 years) participated in fall risk assessment camp at sterling senior center organized by Northern Virginia Fall Prevention Coalition (NVFPC). Three custom made wireless inertial measurement units (IMUs) were attached on trunk and both shanks. All participants performed postural and locomotor tasks such as sit-to-stand (STS) and timed up and go (TUG). Temporal and kinematic parameters were obtained. Raw signals obtained were denoised using ensemble empirical mode decomposition and savistzky-golay filtering. The mean and standard deviation of TUG time and STS completion time for participants were found to be 11.3±6.6 sec and 3.58±2.07 sec respectively. The high variation in the result may be due to the use of assistive devices (i.e., cane and walker) by two participants. The objective of this study is to classify fall prone community dwelling individuals using non-invasive system. Four participants were classified as fall prone, three without fall risk and four were at potential risk based on their objective assessment and task performance. This system provides a platform for identifying fall prone individuals and may be used for early fall interventions among the elderly.
跌倒在老年人中是最严重的事故之一，会导致受伤增加、功能下降和死亡率上升。2009年，老年人群中报告了约220万例非致命性跌倒受伤事件（疾病控制与预防中心，2010年）。在本研究中，11名居住在社区的老年人（年龄在65 - 84岁之间）参加了由北弗吉尼亚跌倒预防联盟（NVFPC）在斯特林老年中心组织的跌倒风险评估活动。三个定制的无线惯性测量单元（IMU）分别附着在躯干和双小腿上。所有参与者都进行了诸如坐立试验（STS）和计时起立行走试验（TUG）等姿势和运动任务。获取了时间和运动学参数。对获得的原始信号使用总体经验模态分解和Savitzky-Golay滤波进行去噪。发现参与者的TUG时间和STS完成时间的平均值及标准差分别为11.3±6.6秒和3.58±2.07秒。结果的高变异性可能是由于两名参与者使用了辅助设备（即拐杖和助行器）。本研究的目的是使用非侵入性系统对易跌倒的社区居住个体进行分类。根据客观评估和任务表现，四名参与者被分类为易跌倒，三名无跌倒风险，四名处于潜在风险。该系统为识别易跌倒个体提供了一个平台，可用于老年人跌倒的早期干预。
