Understanding Real-Life Falls in Amputees using Mobile Phone Technology

描述（由申请人提供）：跌倒是造成死亡和重伤的重要原因，并导致巨额医疗费用。由于血管疾病而进行下肢截肢的患者绝大多数是老年人（至少65岁），他们摔倒的风险特别高。成功的跌倒预防策略取决于了解个体如何、为何、何时和在何处跌倒，以及在特定人群中可能发生何种类型的跌倒（例如，绊倒、滑倒或侧面跌倒）。迄今为止，大多数关于截肢者跌倒的研究都依赖于调查或问卷，这些调查或问卷通常是在跌倒后很长一段时间完成的，因此依赖于两种方法

DESCRIPTION (provided by applicant): Falls are a significant cause of death and serious injury and result in significant health-care costs. Individuals with a lower extremity amputation due to vascular disease are overwhelmingly elderly (at least 65 years of age) and are at especially high risk of falling. Successful fall prevention strategies depend on understanding how, why, when, and where individuals fall, and what types of falls (e.g., trip, slip, or lateral fll) are likely in a given population. Most studies on falls in amputees to date have relied surveys or questionnaires that are often completed a significant time after the fall and thus rely both on the individual's ability to remember the details of their fall and their willingness to be objective abut how and why they fell. Such approaches are susceptible both to inaccurate memories of the fall and to recall bias-for example, due to embarrassment about falling- and are especially unreliable in the elderly amputees. Mobile phones provide a simple, cost-effective method for detection and characterization of falls. Most available smart phones today have a tri-axial accelerometer, which provides highly accurate fall detection in real-time. Other available applications (or apps) can provide data on activity (running, walking etc.) and environment-such as the weather conditions or population density-that may have contributed to the fall and can pin-point the location of the fall-using GPS technology and highly accurate maps. Mobile phones also have inbuilt data storage and transfer capability, allowing for real-time acquisition and transmission of data. Additionally, mobile phones provide a simple means to contact the individual immediately after a suspected fall to confirm details of the fall (and to ascertain the need for medical assistance). Because mobile phone use is so widespread, there is no stigma associated with carrying such a device, which is likely to lead to high compliance. This study aims to use a mobile phone-based fall detection system in dysvascular amputees to detect falls, characterize the type of fall, analyze environmental conditions that may have contributed to the fall, and determine the longer-term consequences of each type of fall. Data acquired may be used to improve rehabilitation protocols or design better prostheses in order to prevent falls. This technology is ultimately transferrable to many populations with a high risk of falling-for example, the elderly, stroke survivors, or those with other musculoskeletal disorders or disabilities-leading to the design of specific fall prevention strategies for those populations.