UNS: GARDE: Research to Quantify the Health and Development of Children with Disabilities Around the Clock

UNS：GARDE：全天候量化残疾儿童健康和发展的研究

• 批准号: 1512564
• 负责人: Steven Warren
• 金额: $ 40万
• 依托单位: Kansas State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-15 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1512564&HistoricalAwards=false
• 关键词: UNS; GARDE; Research; Quantify; Health

1512564(Warren)Autism is the fastest growing developmental disability in the U.S., with a prevalence rate now estimated to be 1 in 68 individuals. Little is understood about the sleep habits of children with severe autism (who often exhibit additional disabilities) and how their sleep quality correlates with daytime well-being and development. Sensible tools to track sleep dynamics in these children are lacking, and they do not generally have the cognitive and/or physical means to describe the restfulness and duration of a night's sleep. Multi-parameter polysomnographs (PSGs) are typically used to evaluate sleep quality in adults and children, but PSG intrusiveness due to the required collection of sensors and wires can affect the ability of even neurotypical subjects to sleep. Such tools are intolerable for severely autistic children and therefore do not lend these systems well to either short- or long-term sleep studies that would purport to correlate sleep quality with daytime well-being and development in this population. Further, mechanisms to provide daytime information on the well-being of children with severe disabilities are generally labor-intensive, limiting the amount of data available for night/day correlation studies. The overall goal of this collaboration between Kansas State University (Manhattan, KS) and Heartspring (Wichita, KS) is to develop and evaluate a toolset to track the well-being of children with disabilities around the clock, offering clinicians and caregivers better means to assess and therefore accelerate the development of these children during their early years. The centerpiece of this toolset will be a sensor-laden bed that will gather multiple types of nighttime physiological and environmental data from a child without their knowledge. These data will then be aggregated into sleep-quality metrics that can be compared against daytime well-being and development parameters consistent with the child's individualized education plan. Anyone that works with children with disabilities will affirm that a positive change in their life leads to emotional, physical, and financial relief for their extended families and caregivers. This effort offers the potential for accelerated development during a time in a severely disabled child's life when the resulting life-long benefits for their family and community are the greatest in terms of quality of life and cost savings. Further, unobtrusive nighttime and daytime monitoring tools offer benefits for other populations, including neurotypical children and children/adults suffering from sleep apnea and other nighttime conditions. Such tools can be seen as "outcomes force multipliers" that address fundamental problems facing special education and, by extension, the disability services community by reducing the disproportionate cost of special education, increasing the base of resources available to meet the growing need, and providing solutions of scale that can be implemented and deployed quickly.The overall goal of this collaboration between Kansas State University (Manhattan, KS) and Heartspring (Wichita, KS) is to develop and evaluate a toolset to track the well-being of children with disabilities around the clock. Four research aims support this goal, which include elucidate the sleep habits of severely disabled children given data acquired from a new unobtrusive sensor suite and develop sleep-quality metrics based upon these data; acquire parameters to assess child daytime health/development using various modalities; develop statistical models linking sleep quality with daytime performance parameters to identify important relationships between sleep quality, learning, and development in severely disabled children; and share lessons learned with the broader disability research and services community. The nighttime monitoring system will be an unobtrusive, multi-parameter bed sensor suite populated with sensing devices that provide parameters such as heart rate, respiration rate, surface body temperature, movement, in/out of bed activity, seizure occurrence, sound, bedwetting frequency/timing, and ambient noise, temperature, humidity, pressure, and light levels. This parameter set can then be correlated with daytime biomedical, behavioral, and educational-performance metrics indicative of child well-being and development consistent with outcomes-based therapies employed by clinicians and paraeducators that work with these children. NSF GARDE funding will support hardware/software development, efficacy assessments involving Heartspring children, randomized nighttime studies with correlative daytime analyses, and salary support for KSU and Heartspring staff and students. These data-gathering mechanisms offer the potential for transformative improvements in terms of (a) quantifying the health and development of severely disabled children, many of whom are nonverbal, (b) understanding sleep quality as it relates to child well-being and development, (c) data that can inform and accelerate individualized education plan updates and positive changes in therapy and medication, (d) reduced burden of care, and (e) improved quality of life for severely disabled children and their care providers.

1512564（沃伦）自闭症是美国增长最快的发育障碍，目前估计患病率为68分之1。人们对严重自闭症儿童（他们经常表现出额外的残疾）的睡眠习惯以及他们的睡眠质量如何与白天的健康和发展相关知之甚少。缺乏跟踪这些儿童睡眠动态的合理工具，他们通常没有认知和/或物理手段来描述夜间睡眠的宁静和持续时间。多参数多导睡眠图（PSG）通常用于评估成人和儿童的睡眠质量，但由于所需的传感器和电线的收集而导致的PSG侵入性甚至会影响神经典型受试者的睡眠能力。这些工具对于严重自闭症儿童来说是无法忍受的，因此这些系统不能很好地用于短期或长期的睡眠研究，这些研究旨在将睡眠质量与这一人群的白天健康和发展联系起来。 此外，提供关于严重残疾儿童福祉的日间信息的机制通常是劳动密集型的，限制了可用于夜间/日间相关性研究的数据量。堪萨斯州立大学（曼哈顿，堪萨斯州）和Heartspring（威奇托，堪萨斯州）之间合作的总体目标是开发和评估一套工具，以全天候跟踪残疾儿童的福祉，为临床医生和护理人员提供更好的方法来评估，从而加速这些儿童在早期的发展。 该工具集的核心将是一个装有传感器的床，它将在儿童不知情的情况下收集多种类型的夜间生理和环境数据。然后，这些数据将被汇总为睡眠质量指标，这些指标可以与符合儿童个性化教育计划的日间健康和发展参数进行比较。任何从事残疾儿童工作的人都会肯定，他们生活中的积极变化会给他们的大家庭和照顾者带来情感、身体和经济上的缓解。 这一努力提供了在严重残疾儿童的一生中加速发展的可能性，在这段时间里，从生活质量和节省费用的角度来看，对他们的家庭和社区产生的终身利益最大。 此外，不显眼的夜间和日间监测工具为其他人群提供了益处，包括神经正常的儿童和患有睡眠呼吸暂停和其他夜间状况的儿童/成人。 这些工具可以被视为"结果力倍增器"，通过降低特殊教育的不成比例的成本，增加可用于满足日益增长的需求的资源基础，并提供可以快速实施和部署的规模解决方案，解决特殊教育面临的根本问题，并通过扩展，残疾服务社区。（曼哈顿，堪萨斯州）和Heartspring（威奇托，堪萨斯州）是开发和评估一套工具，以跟踪残疾儿童的福祉全天候。四个研究目标支持这一目标，其中包括阐明严重残疾儿童的睡眠习惯，从一个新的不引人注目的传感器套件获得的数据，并根据这些数据制定睡眠质量指标;获取参数，以评估儿童白天的健康/发展使用各种方式;开发将睡眠质量与日间表现参数联系起来的统计模型，以确定睡眠质量，学习，与残疾研究和服务界分享经验教训。夜间监测系统将是一个不显眼的多参数床传感器套件，其中装有传感设备，可提供心率、呼吸率、体表体温、运动、床上/下床活动、癫痫发作发生率、声音、尿床频率/时间以及环境噪声、温度、湿度、压力和光照水平等参数。 然后，该参数集可以与日间生物医学、行为和教育表现指标相关联，这些指标指示与临床医生和与这些儿童一起工作的辅助教育工作者采用的基于结果的疗法一致的儿童福祉和发展。 NSF GARDE资金将支持硬件/软件开发，涉及Heartspring儿童的疗效评估，随机夜间研究与相关的日间分析，以及KSU和Heartspring员工和学生的工资支持。这些数据收集机制在以下方面提供了变革性改进的潜力：（a）量化严重残疾儿童的健康和发展，其中许多儿童是非语言的，（B）了解睡眠质量，因为它与儿童的福祉和发展有关，（c）可以告知和加速个性化教育计划更新以及治疗和药物治疗的积极变化的数据，（d）减轻护理负担，以及（e）改善严重残疾儿童及其照料者的生活质量。