Smart driving technology for non-invasive detection of age-related cognitive decline

痴呆症和其他与年龄相关的神经退行性疾病，如阿尔茨海默病(AD)和阿尔茨海默病 疾病相关性痴呆(ADRD)导致患者的生活质量显著下降，增加了负担 对于65岁以上的成年人来说，这是导致死亡的主要原因。因此，更好地理解 痴呆症对于制定和评估有效的治疗方案至关重要。尽管有严酷的瞭望， 临床研究表明，在不可逆转的脑损伤发生之前对疾病进行干预是 改善AD/ADRD的结果。具体来说，轻度认知障碍(MCI)，发病前的阶段 痴呆症可能为延缓/预防MCI的生活方式干预提供最大的“机会之窗” 和痴呆症。我们的团队已经报告了生活方式的改变，这为这种疾病带来了机会之窗 在不可逆转的脑损伤之前进行治疗。 多项研究表明，MCI与包括驾驶在内的驾驶表现之间存在关系 行为。尽管驾驶功能为测试大脑提供了一个无障碍的机会之窗 在日常认知挑战下的反应，目前是不切实际的成本和劳动密集型 广泛部署。我们假设一个畅通无阻的、连续的、经济的系统能够评估 驾驶能够检测到神经退行性疾病早期阶段的信号将提供一个逆转的窗口 AD和ADRD。在这项工作中，我们建议开发并验证一种不引人注目的汽车制造不可知论者 名为Smart Pad的传感系统，用于在自由生活条件下对驾驶指标进行日常评估。这个 系统：1)利用集成的生物传感器阵列和移动App自动记录和分析数据 评估驾驶；2)使用生物传感器阵列，不仅可以检测驾驶习惯，还可以检测新驾驶 性能指标和前所未有的驾驶员生物标记物(姿势和代谢率)，它们是 与有害的认知阶段相关，以及3)由人工智能(AI)算法授权 预测认知表现和MCI。在此第一阶段计划中，我们将利用Smart Pad原型 我们开发和优化的用于驾驶员认知状态诊断的设计。 TF Health Co.-ASU-BNI团队将共同努力，建立基于车辆的非侵入性传感器 每日评估司机表现和生物特征的系统，以及与年龄相关的认知能力下降 开发自由生活条件下痴呆症早期诊断的新技术，寻求改善患者护理 选择并促进预防认知衰退的干预措施。

Dementia and other age-related neurodegenerative diseases such as Alzheimer’s Disease (AD) and Alzheimer’s Disease Related Dementias (ADRD) cause a marked decrease in quality of life for patients, an increased burden of care, and, for adults over 65, are a leading cause of death. Therefore, better understanding of the nature of dementia is vital to the development and assessment of effective treatment options. Despite the grim lookout, clinical research suggests that intervening the disease before irreversible brain damage occurs is a key step to improve the outcomes of AD/ADRD. Specifically, Mild Cognitive Impairment (MCI), the stage before the onset of dementia, could provide the largest “window of opportunity” for lifestyle interventions that can delay/prevent MCI and dementia. Our team has reported lifestyle changes which brings a window of opportunity for the disease treatment prior to irreversible brain damages. Several studies have demonstrated a relationship between MCI and driving performance including driving behaviors. Although driving features provide an unobstructive window of opportunity to test the brain responses under everyday cognitive challenges, it is currently unrealistically costly and labor-intensive to be widely deployed. We hypothesize an unobstructive, continuous, economical system capable of assessing driving signatures that can detect early stages of neurodegenerative diseases would offer a window to reverse AD and ADRD. In this work, we propose to develop and validate an unobtrusive and car-make agnostic sensing system, named Smart Pad, for daily assessment of driving indicators under free-living conditions. The system: 1) automatically records and analyzes data with the integrated biosensor array and a mobile App to evaluate driving; 2) uses the biosensors array to detect not only driving habits, but also new driving performance indicators and unprecedented driver’s biomarker (posture and metabolic rate), which are correlated with detrimental cognitive stages, and 3) is empowered by an Artificial Intelligence (AI) algorithm to predict cognitive performance and MCI. In this Phase I proposal, we will leverage the Smart Pad prototype design that we have developed and optimize it to for the diagnosis of driver’s cognitive status. The TF Health Co.-ASU-BNI team will work together to build the unobtrusive, vehicle-based sensing system for daily assessment of driver performance and biometrics, and age-related cognitive decline to develop new technology for early diagnosis of dementia in free-living condition, seeking to improve patient care options and promote cognitive decline prevention interventions.