Harris Che, Tang Yingfei, Birnbaum Eliana, Cherian Christine, Mendhe Dinesh, Chen Michelle H
Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, USA.
Department of Neurology, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA.
Arch Clin Neuropsychol. 2024 Apr 24;39(3):290-304. doi: 10.1093/arclin/acae016.
Compared with other health disciplines, there is a stagnation in technological innovation in the field of clinical neuropsychology. Traditional paper-and-pencil tests have a number of shortcomings, such as low-frequency data collection and limitations in ecological validity. While computerized cognitive assessment may help overcome some of these issues, current computerized paradigms do not address the majority of these limitations. In this paper, we review recent literature on the applications of novel digital health approaches, including ecological momentary assessment, smartphone-based assessment and sensors, wearable devices, passive driving sensors, smart homes, voice biomarkers, and electronic health record mining, in neurological populations. We describe how each digital tool may be applied to neurologic care and overcome limitations of traditional neuropsychological assessment. Ethical considerations, limitations of current research, as well as our proposed future of neuropsychological practice are also discussed.
与其他健康学科相比,临床神经心理学领域的技术创新存在停滞。传统的纸笔测试存在诸多缺点,如数据收集频率低和生态效度受限。虽然计算机化认知评估可能有助于克服其中一些问题,但当前的计算机化范式并未解决这些局限性中的大部分。在本文中,我们回顾了近期关于新型数字健康方法应用的文献,这些方法包括生态瞬时评估、基于智能手机的评估与传感器、可穿戴设备、被动驾驶传感器、智能家居、语音生物标志物以及电子健康记录挖掘,应用于神经疾病人群。我们描述了每种数字工具如何应用于神经护理并克服传统神经心理学评估的局限性。还讨论了伦理考量、当前研究的局限性以及我们对神经心理学实践未来的建议。