FW-HTF: Collaborative Research: An Embodied Intelligent Cognitive Assistant to Enhance Cognitive Performance of Shift Workers

FW-HTF：协作研究：增强轮班工人认知表现的具体智能认知助手

• 批准号: 1840025
• 负责人: Tanzeem Choudhury
• 金额: $ 58.99万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1840025&HistoricalAwards=false
• 关键词: FW; HTF; Collaborative; Research; Embodied

The Future of Work at the Human-Technology Frontier (FW-HTF) is one of 10 new Big Ideas for Future Investment announced by NSF. The FW-HTF cross-directorate program aims to respond to the challenges and opportunities of the changing landscape of jobs and work by supporting convergent research. This award fulfills part of that aim.This project develops a closed-loop embodied Intelligent Cognitive Assistant (e-ICA) to infer circadian rhythm, alertness, and stress levels and to provide personalized feedback to enhance users' cognitive ability and wellbeing in an unobtrusive and effortless manner. Approximately 20% of the labor force engages in shift work, which often leads to inadequate and poor sleep. Being out of synch with one's natural body clock, or circadian rhythm, can lead to many complications over time, including a higher likelihood for cardiovascular disease, cancer, obesity, and mental health problems. In addition, there can be serious deficits in cognitive performance, with productivity loss and more accidents in the workplace. This research program will design and develop a novel sensor-based e-ICA that can monitor shift workers' circadian rhythms, sleep patterns, and stress levels. The platform will be flexible so that it can be used to study broad populations in addition to shift workers. Given that 70 percent of the population suffers from circadian rhythm disruption, this technology has the potential to impact a wide range of workers and firms. In addition, the anonymized data and information about developed hardware and software will be shared in the community. The technology will impact the needs of a broad cross-section of stakeholders, but will be tested initially with medical residents and other health practitioners who typically work long shift that change every few weeks. Moreover, this project will also allow interdisciplinary cross fertilization between science, engineering, psychology, sleep and circadian biology, and psychiatry.The investigators explore ways to provide biologically and physiologically attuned support in the areas of cognitive ability, performance, sleep, and well-being based on the inferred individual circadian rhythm and personalized embodied assistance by: a) passively and continuously gathering behavioral and physiological streams through wearable, mobile and remote devices from workers in an effortless manner; b) continuously inferring each person's individual circadian rhythm, alertness, and stress in daily life settings; and c) providing personalized multi-sensory feedback or actionable behavioral suggestions to modulate circadian rhythm, alertness and stress levels with the aim of enhancing cognitive ability, performance and wellbeing. The investigators will test the efficacy, usability and acceptability of the system both in a series of laboratory studies and in an in-situ work environment.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

人类技术前沿的未来工作（FW-HTF）是NSF宣布的10个未来投资新想法之一。FW-HTF跨董事会计划旨在通过支持融合研究来应对不断变化的就业和工作环境的挑战和机遇。该项目开发了一种闭环嵌入式智能认知助手（e-ICA），可以推断昼夜节律、警觉性和压力水平，并提供个性化反馈，以不引人注目和轻松的方式增强用户的认知能力和健康。大约20%的劳动力从事轮班工作，这往往导致睡眠不足和睡眠不足。与一个人的自然生物钟或昼夜节律不同步，随着时间的推移会导致许多并发症，包括更高的心血管疾病，癌症，肥胖和心理健康问题的可能性。此外，认知能力可能严重不足，生产力下降，工作场所发生更多事故。这项研究计划将设计和开发一种新的基于传感器的e-ICA，可以监测轮班工人的昼夜节律，睡眠模式和压力水平。该平台将是灵活的，因此除了轮班工人外，它还可以用于研究广泛的人群。鉴于70%的人口患有昼夜节律紊乱，这项技术有可能影响广泛的工人和公司。此外，有关开发的硬件和软件的匿名数据和信息将在社区中共享。该技术将影响广泛的利益相关者的需求，但最初将在住院医生和其他健康从业者中进行测试，这些人通常每隔几周就会换一次班。此外，该项目还将允许科学，工程，心理学，睡眠和昼夜节律生物学以及精神病学之间的跨学科交叉施肥。研究人员探索如何根据推断的个人昼夜节律和个性化的具体帮助，在认知能力，表现，睡眠和健康领域提供生物和生理协调的支持：a）通过可穿戴的、移动的和远程设备以毫不费力的方式被动地和连续地从工作人员收集行为和生理流; B）连续地推断每个人在日常生活环境中的个人昼夜节律、警觉性和压力;以及c）提供个性化的多感官反馈或可操作的行为建议以调节昼夜节律、警觉性和压力水平，目的是增强认知能力、表现和健康。调查人员将在一系列实验室研究和现场工作环境中测试该系统的有效性、可用性和可接受性。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Using behavioral rhythms and multi-task learning to predict fine-grained symptoms of schizophrenia

• DOI: 10.1038/s41598-020-71689-1
• 发表时间: 2020-09-15
• 期刊: SCIENTIFIC REPORTS
• 影响因子: 4.6
• 作者: Tseng, Vincent W. -S.;Sano, Akane;Choudhury, Tanzeem
• 通讯作者: Choudhury, Tanzeem