Automated System for Accurate Determination of Activities of Daily Living for Independently-Living Persons with Alzheimers Disease and Related Dementias

用于准确确定患有阿尔茨海默病和相关痴呆症的独立生活者的日常生活活动的自动化系统

• 批准号: 10543933
• 负责人: Suneel Ismail Sheikh
• 金额: $ 43.95万
• 依托单位: ASTER LABS, INC.
• 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 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10543933
• 关键词: Accelerometer; Activities of Daily Living; Address; Algorithms; Alzheimer' s Disease; Alzheimer' s disease related dementia; American; Americas; Bathing; Behavior; Books; Calendar; Caregivers; Caring; Classification; Clinic; Clinical Research; Complement; Computer software; Critiques; Data; Dementia; Detection; Devices; Diagnosis; Disease Progression; Eating; Elderly; Electronics; Engineering; Evaluation; Florida; Focus Groups; Health; Health Personnel; Home; Hygiene; Independent Living; Individual; Infrastructure; Intelligence; Intervention; Life Style; Location; Manuals; Memory; Memory impairment; Monitor; Movement; Outcome; Paper; Patients; Performance; Persons; Phase; Physicians; Population; Privacy; Privatization; Process; Reporting; Research; Research Personnel; Risk; Shoes; Signal Transduction; Small Business Innovation Research Grant; Sterile coverings; System; Techniques; Technology; Thinking; Time; United States; Universities; Vision; aging in place; base; care providers; cognitive rehabilitation; community living; data handling; design; digital; efficacy evaluation; experience; experimental study; fitness; functional independence; human study; implementation intervention; individual patient; innovation; insight; patient privacy; phase 1 testing; preservation; prevent; programs; prototype; remote health care; sensor; signal processing; spatiotemporal; success; system architecture; tool; wearable device; wearable sensor technology

Project Abstract In this Phase I SBIR project, ASTER Labs will develop and evaluate an innovative system to automatically and accurately detect Activities of Daily Living (ADL) performed by persons with Alzheimer’s disease and related dementias. It will address a current need to equip caregivers and health care providers, including physicians and cognitive rehabilitation therapists, with reliable information on patients’ ongoing abilities to perform these important activities. The confirmation of these abilities will directly support the capability of a functioning independent lifestyle, while producing informed decisions on interventions and level of care based on disease progression. An estimated 5.8 million Americans in 2020 live with Alzheimer’s dementia. Nearly a third of these individuals live alone and are more likely to experience poorer health outcomes than cohabitating persons. Ongoing assessment of ADL is highly recommended for establishing diagnosis of dementia and progression of the disease over time. Existing and proposed approaches to automate this assessment in the home have ranged from cameras or vision-based sensors to beacon-based signal processing techniques. However, these approaches have been subject to limitations and critique due to privacy concerns, poor accuracy, limited coverage, and requirements of significant infrastructure alterations. Common commercial activity trackers have concentrated primarily on fitness activities, and typically rely on non-discreet wearable devices that, due to unfamiliarity, may be unacceptable to dementia patients. Clinical research has indicated interventions involving compensatory memory techniques and devices may help prevent or delay dementia onset, and preserve functional independence. Use of both manual and digital memory notebooks to help patients record when they performed certain activities have shown significant promise. However, seniors with memory impairment and dementia may risk inaccurate recollection of activities performed throughout the day, and have faced difficulty interacting with recent digital implementations of these interventions. An unmet need exists in the ability of those caring for these individuals to receive verifiable information on whether the activity was completed at the time reported by the patient, or at all. ASTER Labs’ proposed Activlog system leverages intelligent processing of WiFi, GPS, inertial, and audio sensor data from a small hardware suite concealed in a shoe insole, unnoticeable to the wearer, that uses high-precision location and multi-sensor association to accurately and continuously monitor and detect ADL. In Phase I, the prototype system will be assembled, with feasibility demonstrated by functional evaluation conducted through a focus group study with caregivers, physicians, and cognitive rehabilitation therapists of patients with dementia. Activity classification accuracy of the device will be determined in timed experiments by ASTER Labs’ engineers wearing the prototype insoles. Phase I testing will provide the success criteria for the start of the Phase II program, which will include a human study of the fully- operational system in home and independent living settings to establish the efficacy of this approach.

项目摘要 在这个第一阶段 SBIR 项目中，ASTER Labs 将开发和评估一个创新系统，以自动和 准确检测阿尔茨海默病及相关疾病患者的日常生活活动 (ADL) 痴呆症。它将满足当前为护理人员和医疗保健提供者（包括医生）提供装备的需求 和认知康复治疗师，提供有关患者持续执行这些治疗的能力的可靠信息 重要活动。这些能力的确认将直接支持一个功能的发挥 独立的生活方式，同时根据疾病对干预措施和护理水平做出明智的决定 进展。据估计，到 2020 年，将有 580 万美国人患有阿尔茨海默氏症。其中近三分之一 独居者的健康状况比同居者更可能较差。 强烈建议持续评估 ADL，以诊断痴呆症和病情进展 随着时间的推移，这种疾病。现有的和提议的在家中自动化评估的方法已经 范围从相机或基于视觉的传感器到基于信标的信号处理技术。然而，这些 由于隐私问题、准确性差、有限性等原因，这些方法受到了限制和批评。 覆盖范围以及重大基础设施改造的要求。常见的商业活动跟踪器有 主要集中于健身活动，并且通常依赖于非谨慎的可穿戴设备，由于 陌生的环境，对于痴呆症患者来说可能难以接受。临床研究表明干预措施涉及 补偿性记忆技术和设备可能有助于预防或延缓痴呆症的发作，并保留 功能独立。使用手动和数字记忆笔记本来帮助患者记录 所开展的某些活动已显示出重大前景。然而，记忆力减退的老年人 痴呆症可能会面临无法准确回忆全天活动的风险，并且面临困难 与这些干预措施的最新数字实施进行交互。能力方面存在未满足的需求 那些照顾这些人的人会收到有关活动是否在现场完成的可核实信息 患者报告的时间，或根本没有。 ASTER Labs 提出的 Activlog 系统利用智能处理 来自隐藏在鞋垫中的小型硬件套件的 WiFi、GPS、惯性和音频传感器数据， 佩戴者不易察觉，利用高精度定位和多传感器关联，准确无误地 持续监测和检测 ADL。第一阶段将组装原型系统，并具备可行性 通过与护理人员、医生和护理人员进行的焦点小组研究进行的功能评估来证明 痴呆症患者的认知康复治疗师。设备的活动分类准确度为 由穿着原型鞋垫的 ASTER 实验室工程师通过定时实验确定。第一阶段测试将 为第二阶段计划的启动提供成功标准，其中将包括对完全的人体研究 家庭和独立生活环境中的操作系统以确定这种方法的有效性。