Fall risk assessment and prevention in elderly with diabetes using wearable techn

描述(申请人提供)：这个跨学科的项目旨在开发一种创新的康复技术，通过结合可穿戴传感器技术和虚拟现实来预防老年人，更具体地说，老年人糖尿病患者的跌倒。老年人跌倒是一个主要的老年病问题，据估计，65岁以上的老年人中每年有30%摔倒。[1-3]跌倒的直接和间接社会代价是巨大的。据估计，仅在美国老年人中，每年因跌倒造成的损失就达200亿美元。[4]准确识别那些跌倒风险较高的参与者将有助于适当和及时的干预，并可由于入院人数减少和跌倒严重程度降低而提高护理质量和降低相关的医院费用。糖尿病在老年人中的患病率正在稳步上升。它的一些被低估的并发症，如身体功能受损和摔倒和骨折风险增加，尚未得到彻底的调查。据估计，美国的糖尿病患病率将增加到33%[5]。使用胰岛素会使截肢风险增加90%[6]，跌倒风险增加2.8[7]； 足部溃疡无法愈合的一个重要的新兴危险因素。[8]大约50%的糖尿病患者有糖尿病神经病变的证据，使其成为最常见的症状性并发症。[9]糖尿病相关周围神经病变(DPN)患者经常表现出伴随的姿势不稳，可能导致跌倒、骨折、抑郁、焦虑和生活质量下降。糖尿病患者经历意外跌倒或与跌倒相关的伤害的可能性是健康人的2.5倍[10]。这是一个经常被忽视的问题，在开发和测试创新策略以改善患者群体的平衡和体位稳定性方面，很少受到关注。这项拟议的技术利用可穿戴传感器，类似于iPhone(R)中使用的传感器，在虚拟环境中提供有关受试者在步态中的姿势稳定性和运动适应能力的实时信息。该策略的三个重要组成部分是：1)评估和改善患者在挑战条件下对腿部位置的感知；2)在诊所/家庭中使用基于交互虚拟奖励的方案来激励和指导简单的运动表现；以及3)改善感觉反馈条件改变的患者的姿势控制。建议的技术收集的信息为开发有效的康复策略提供了新的机会，以改善糖尿病/DPN患者的平衡和姿势稳定性。在这项研究的第一阶段，我们将改进 我们使用可穿戴技术实时测量腿部位置的初始原型系统的总体架构。设计的原型将在两项临床研究的背景下进行测试，以证明其在评估平衡和下肢位置方面的准确性，以及在诊断老年人神经病变并发症方面的敏感性和特异性。我们假设，在安全的虚拟环境中，在一系列穿越障碍的任务中，放大对腿部位置的视觉感知将有助于患者更好地协调他们的姿势控制、生活质量和步态稳定性。在本阶段建议的概念研究获得证实后，我们将在计划的第二阶段进行大型临床研究，以证明其益处。 在改善老年糖尿病患者步态和平衡方面的拟议技术。这项拟议的技术在老年护理、中风、神经退行性疾病、创伤性脑损伤(TBI)以及治疗平衡障碍和头晕方面有着非常广泛的应用。 公共卫生相关性：由于年龄、中风、糖尿病和帕金森氏症等原因导致步态受损的人，障碍和解可能会受到影响。在某些情况下，下肢位置判断受损--主要是由于本体感觉反馈受损(例如，患有糖尿病和神经病变的患者)--可能会导致障碍碰撞，导致摔倒，甚至严重受伤。我们提出了一种简单的模式来测量和训练下肢知觉障碍患者的平衡策略，它向受试者提供实时的视觉反馈。

DESCRIPTION (provided by applicant): This interdisciplinary project aims to develop an innovative rehabilitation technology for prevention of fall in elderly and more specifically elderl with diabetes by combining wearable sensor technology and virtual reality. Falls in the elderly are a major geriatric problem, with an estimated 30% of elderly adults over 65 years of age falling each year. [1-3] The direct and indirect societal costs of falls are enormous. Among elderly people in the US alone, the cost of falls has been estimated to be US$20 billion per year. [4] Accurate identification of those participants at high risk of falls would facilitate appropriat and timely intervention, and could lead to improved quality of care and reduced associated hospital costs, due to reduced admissions and reduced severity of falls. The prevalence of diabetes is steadily increasing in elderly people. Some of its under-appreciated complications, such as impaired physical functioning and increased risk of falls and fractures, have not been thoroughly investigated well. Diabetes prevalence is estimated to increase to 33% in US [5]. Insulin use is associated with a 90% increased amputation risk [6] and 2.8 increased fall risk [7]; an important emerging risk factor for foot ulcer non-healing.[8] Approximately 50% of patients with diabetes show evidence of diabetic neuropathy, making this the most common symptomatic complication. [9] People with diabetes-related peripheral neuropathy (DPN) frequently exhibit concomitant postural instability that can lead to falls, fracture, depression, anxiety, and decreased quality of life. Individuals with diabetes are 2.5-fold more likely to experience an accidental fall or a fall-related injury than healthy ones [10]. This is an often neglected problem, and has received little attention regarding development of and testing of innovative strategies to improve balance and postural stability in this patient population. The proposed technology utilizes wearable sensors, similar to those used in an iPhone(R), to provide real time information about a subject's postural stability and motor adaptation ability during gait in a virtual environment. Three important components of the proposed strategy are, 1) to assess and improve the perception of lower extremity position during challenging conditions; 2) to motivate and guide simple exercise performance in a clinic/home, using an interactive virtual reward-based scheme; and 3) to improve postural control in patients with altered sensory feedback condition. The information gathered by the proposed technology provides novel opportunities to develop effective rehabilitation strategies to improve balance and postural stability in diabetes/DPN patients. In the first phase of this study, we will improve the overall architecture of our initial prototype system for measuring lower extremity position in real time using wearable technology. The designed prototype will be tested in the context of two clinical studies to demonstrate its accuracy for assessing balance and lower extremity position as well as its sensitivity and specificity to diagnose neuropathy complication in older adults. We hypothesize that amplifying visual perception of the lower extremity position during a set of obstacle crossing tasks in a safe virtual environment will help patients better coordinate their postural control, quality of life and gait steadiness. After proof of concept study proposed in thi phase, we will conduct a large clinical study in phase II of the project to demonstrate the benefit of the proposed technology in improving gait and balance in elderly with diabetes. The proposed technology has a very wide range of applications in elderly care, stroke, neurodegenerative diseases, traumatic brain injury (TBI), and in treating balance disorders and dizziness. PUBLIC HEALTH RELEVANCE: Obstacle reconciliation can be compromised in people with impaired gait due to age, stroke, diabetes and Parkinson's disease amongst various others. In certain cases the impaired lower extremity position judgment - mainly due to impaired proprioceptive feedback (e.g. in patients suffering from diabetes and neuropathy) - can cause obstacle collision leading to falls or even serious injuries. We propose a simple modality to measure as well as train balance strategies in patients with impairment of lower extremity perception, which provides real time visual feedback to the subject.