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

使用可穿戴技术评估和预防老年糖尿病患者的跌倒风险

• 批准号: 8370475
• 负责人: Bor-rong Chen
• 金额: $ 14.99万
• 依托单位: BIOSENSICS, LLC
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2013-11-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8370475
• 关键词: Accidental Falls; Activities of Daily Living; Admission activity; Adult; Affect; Age; Age-Years; Aging; Algorithms; Amputation; Anxiety; Architecture; Arizona; Attention; Balance training; Biofeedback; Biomechanics; Caring; Clinic; Clinical Research; Comorbidity; Complication; Complications of Diabetes Mellitus; Development; Diabetes Mellitus; Diabetic Neuropathies; Diagnosis; Dizziness; Early Diagnosis; Early treatment; Elderly; Environment; Equilibrium; Evaluation; Exercise; Exhibits; Fall prevention; Feedback; Foot Ulcer; Fracture; Gait; Hand; Height; Hip Joint; Home environment; Hospital Costs; Imagery; Impairment; Individual; Injury; Insulin; Intervention; Joints; Judgment; Lead; Leg; Length; Limb structure; Lower Extremity; Measures; Mental Depression; Modality; Modeling; Motion; Motor; Musculoskeletal Equilibrium; Neurodegenerative Disorders; Neuropathy; Parkinson Disease; Participant; Patients; Perception; Performance; Peripheral Nervous System Diseases; Pharmaceutical Preparations; Phase; Physical Function; Physicians; Positioning Attribute; Prevalence; Prevention; Quality of Care; Quality of life; Reaction Time; Recruitment Activity; Rewards; Risk; Risk Assessment; Risk Factors; Sample Size; Scheme; Screening procedure; Sensitivity and Specificity; Series; Severities; Small Business Innovation Research Grant; Stroke; System; Technology; Testing; Time; Traumatic Brain Injury; Universities; Validation; Visual Perception; Walking; Wireless Technology; Work; aged; ankle joint; base; biomechanical engineering; cost; design; diabetic patient; equilibration disorder; experience; fall risk; falls; foot; graphical user interface; high risk; human old age (65+); improved; information gathering; innovation; kinematics; motor learning; neglect; novel; patient population; pressure; prototype; rehabilitation strategy; rehabilitation technology; sensor; sensory feedback; sensory neuropathy; somatosensory; success; time use; tool; virtual; virtual reality; visual feedback

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.

描述（由申请人提供）：该跨学科项目旨在通过结合可穿戴传感器技术和虚拟现实，开发一种创新的康复技术，用于预防老年人，特别是患有糖尿病的老年人跌倒。老年人跌倒是一个主要的老年问题，估计每年有 30% 的 65 岁以上老年人跌倒。 [1-3] 跌倒造成的直接和间接社会成本是巨大的。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] 准确识别跌倒高风险的参与者将有助于采取适当和及时的干预措施，并且由于减少了入院人数和降低了跌倒的严重程度，因此可以提高护理质量并降低相关的医院费用。老年人中糖尿病的患病率正在稳步上升。它的一些未被充分认识的并发症，例如身体功能受损以及跌倒和骨折风险增加，尚未得到充分调查。据估计，美国的糖尿病患病率将增至 33% [5]。使用胰岛素会导致截肢风险增加 90% [6]，跌倒风险增加 2.8% [7]； 足部溃疡不愈合的一个重要的新兴危险因素。 [8]大约 50% 的糖尿病患者表现出糖尿病神经病变的证据，使其成为最常见的症状并发症。 [9] 患有糖尿病相关周围神经病变 (DPN) 的人经常表现出伴随的姿势不稳定，可能导致跌倒、骨折、抑郁、焦虑和生活质量下降。糖尿病患者发生意外跌倒或跌倒相关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，并且在开发和测试改善该患者群体平衡和姿势稳定性的创新策略方面很少受到关注。 所提出的技术利用可穿戴传感器（类似于 iPhone(R) 中使用的传感器）来提供有关虚拟环境中步态期间主体的姿势稳定性和运动适应能力的实时信息。所提出策略的三个重要组成部分是：1）评估和改善挑战性条件下下肢位置的感知； 2) 使用交互式虚拟奖励方案来激励和指导诊所/家庭中的简单运动表现； 3) 改善感觉反馈状况改变的患者的姿势控制。该技术收集的信息为制定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。 在本研究的第一阶段，我们将改进 我们最初的原型系统的整体架构，用于使用可穿戴技术实时测量下肢位置。设计的原型将在两项临床研究的背景下进行测试，以证明其评估平衡和下肢位置的准确性以及诊断老年人神经病变并发症的敏感性和特异性。我们假设，在安全的虚拟环境中进行一系列越障任务时，增强下肢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。经过这一阶段提出的概念验证研究后，我们将在该项目的第二阶段进行大型临床研究以证明其益处 所提出的技术在改善患有糖尿病的老年人的步态和平衡方面的作用。该技术在老年护理、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具有非常广泛的应用。 公共卫生相关性：由于年龄、中风、糖尿病和帕金森病等原因导致步态受损的人，障碍协调可能会受到影响。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的患者）——可能会导致障碍物碰撞，导致跌倒甚至严重受伤。我们提出了一种简单的方法来测量下肢知觉受损的患者并训练平衡策略，为受试者提供实时视觉反馈。