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用于非侵入性检测与年龄相关认知衰退的智能驾驶技术。

Smart Driving Technology for Non-Invasive Detection of Age-Related Cognitive Decline.

作者信息

Serhan Peter, Victor Shaun, Osorio Perez Oscar, Abi Karam Kevin, Elghoul Anthony, Ransdell Madison, Al-Hindawi Firas, Geda Yonas, Chahal Geetika, Eagan Danielle, Wu Teresa, Tsow Francis, Forzani Erica

机构信息

School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85281, USA.

Center for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, 1001 S McAllister Ave, Tempe, AZ 85281, USA.

出版信息

Sensors (Basel). 2024 Dec 18;24(24):8062. doi: 10.3390/s24248062.

DOI:10.3390/s24248062
PMID:39771798
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11679439/
Abstract

Alzheimer's disease (AD) and Alzheimer's Related Dementias (ADRD) are projected to affect 50 million people globally in the coming decades. Clinical research suggests that Mild Cognitive Impairment (MCI), a precursor to dementia, offers a critical window of opportunity for lifestyle interventions to delay or prevent the progression of AD/ADRD. Previous research indicates that lifestyle changes, including increased physical exercise, reduced caloric intake, and mentally stimulating activities, can reduce the risk of MCI. Early detection of MCI is challenging due to subtle and often unnoticed cognitive decline and is traditionally monitored through infrequent clinical tests. In this research, the Smart Driving System, a novel, unobtrusive, and economical technology to detect early stages of neurodegenerative diseases, is presented. The system comprises a multi-modal biosensing array (MMS) and AI algorithms, including driving performance and driver's biometrics, offering insights into a driver's cognitive function. This publication is the first work reported towards the ultimate goal of developing the Smart Driving Device and App, integrating it into vehicles, and validating its effectiveness in detecting MCI through comprehensive pilot studies.

摘要

预计在未来几十年里，全球将有5000万人受到阿尔茨海默病（AD）和阿尔茨海默病相关痴呆症（ADRD）的影响。临床研究表明，轻度认知障碍（MCI）作为痴呆症的前驱症状，为通过生活方式干预来延缓或预防AD/ADRD的进展提供了一个关键的机会窗口。先前的研究表明，生活方式的改变，包括增加体育锻炼、减少热量摄入以及进行益智活动，可以降低患MCI的风险。由于认知能力下降较为细微且常常不易被察觉，早期检测MCI具有挑战性，传统上是通过不频繁的临床测试来进行监测的。在这项研究中，提出了一种智能驾驶系统，这是一种用于检测神经退行性疾病早期阶段的新颖、非侵入性且经济的技术。该系统包括一个多模态生物传感阵列（MMS）和人工智能算法，其中包括驾驶性能和驾驶员生物特征识别，能够提供有关驾驶员认知功能的见解。本出版物是朝着开发智能驾驶设备和应用程序、将其集成到车辆中并通过全面的试点研究验证其在检测MCI方面的有效性这一最终目标所报告的第一项工作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9203/11679439/119e5ed28bc8/sensors-24-08062-g010.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9203/11679439/df715bec5907/sensors-24-08062-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9203/11679439/da9f24915f64/sensors-24-08062-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9203/11679439/ca631753191b/sensors-24-08062-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9203/11679439/b6dc4ad59294/sensors-24-08062-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9203/11679439/119e5ed28bc8/sensors-24-08062-g010.jpg

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