SCH: INT: VOLI: Voice Assistant for Quality of Life and Healthcare Improvement in Aging Populations

根据美国人口普查局的最新预测，到2035年，老年人口预计将超过 这是美国历史上第一次有孩子。这带来了重大的社会挑战，基于他们独特的 由于感觉、运动和认知能力降低而导致的与生活和健康有关的疾病，如 温氏为多种慢性病。我们提出了一种个性化和上下文感知的基于语音的数字 协助改善老年人的生活质量和医疗保健。Voli将利用不断增长的 现有技术的功能，如移动设备和智能扬声器，并远远超出 基本的天气预报，新闻服务，和简单的游戏，提供更复杂的基于语音的 并将重点放在具有许多挑战和限制的医疗保健领域。 我们将追求三个平行的研究目标：1)我们的技术目标将调查数字助理如何， 自然语言处理和机器学习可以产生与健康相关的有意义的对话 通过利用来自电子健康记录(EHR)的人口和患者级别的数据；2)我们的社会、 行为和认知目标将专注于根据老年人的需求设计服务 支持独立性，并调查数字助理对老龄化人口的可接受性；以及 3)我们的临床目标是研究数字助理如何检测新的症状并将它们联系起来 有药物副作用和相互作用，现有条件恶化，或出现新的疾病。 使用我们的Voli语音助手，老年人将能够获得药物提醒和说明 根据EHR的处方和临床记录，通知他们的家人/照顾者他们的健康状况 状态，与其医疗保健提供者互动，请求Uber/Lyft汽车或其他第三方服务， 参与认知游戏，在一天中和柜台上报告症状 他们服用的药物，询问有关症状和药物的问题，等等。 VOLI集成了来自电子病历、临床本体和患者级别术语的信息。这项工作将 在自然语言理解、深度学习和人机方面的创新提供支持 接口。我们的工作是由临床医生和研究人员在以人为中心的计算方面指导的。我们的团队 在医疗保健、临床护理专家系统、电子病历等领域拥有成功的跨学科工作经验 集成、患者监控和自我报告、无处不在的计算、数据分析和实地研究。

According to the latest US Census Bureau predictions, by 2035 older people are projected to outnumber children for the first time in US history. This brings significant societal challenges based on their unique living and health-related conditions stemming from reduced sensory, motor, and cognitive capabilities, as wen as multiple chronic conditions. We propose a personalized and context-aware voice-based digital assistant to improve the quality of life and the healthcare of older adults. VOLI will leverage the growing capabilities of existing technologies, such as mobile devices and smart speakers, and go well beyond the basics of weather reports, news services, and simple games, to provide more complex voice-based services and to focus on the healthcare domain with its many challenges and constraints. We will pursue three parallel research aims: 1) Our technical aim will investigate how digital assistants, natural language processing, and machine learning can produce meaningful health-related conversations by leveraging population- and patient-level data from Electronic Health Records (EHRs); 2) Our social, behavioral, and cognitive aim will focus on designing services for older adults based on their needs to support independence and investigate the acceptability of digital assistants for the aging population; and 3) Our clinical aim will investigate how digital assistants can detect new symptoms and correlate them with medication side effects and interactions, worsening of existing conditions, or onset of new illnesses. Using our VOLI voice-assistant, older adults will be able to get medication reminders and instructions based on prescriptions and clinical notes from EHRs, notify their family/caregiver about their well-being status, interact with their healthcare provider, request an Uber/Lyft car or other third-party services, engage in cognitive games, report symptoms as they occur throughout the day and over the counter medications they are taking, ask questions about symptoms and medications, and so on. VOLi integrates information from EHRs, clinical ontologies, and patient-level terminology. This work will be supported by innovations in natural language understanding, deep learning, and human-computer interfaces. Our work is guided by both clinicians and researchers in human-centered computing. Our team has a history of successful interdisciplinary work in healthcare, expert systems in clinical care, EHR integration, patient monitoring and self-report, ubiquitous computing, data analytics, and field studies.