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

1512564（Warren）自闭症是美国增长最快的发育性残疾，目前的患病率估计为68人中有1人。对于患有严重自闭症的儿童（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与白天的健康和发展之间的关系，人们知之甚少。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/或身体手段来描述夜间睡眠的安宁和持续时间。多参数多导睡眠仪（PSG）通常用于评估成人和儿童的睡眠质量，但由于需要收集传感器和电线，PSG具有侵入性，甚至会影响神经正常受试者的睡眠能力。这些工具对严重自闭症儿童来说是无法忍受的，因此不能很好地将这些系统用于短期或长期睡眠研究，这些研究旨在将睡眠质量与白天的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，限制了用于昼夜相关性研究的数据量。堪萨斯州立大学（Manhattan， KS）和Heartspring （Wichita， KS）合作的总体目标是开发和评估一套工具，全天候跟踪残疾儿童的健康状况，为临床医生和护理人员提供更好的方法来评估并因此加速这些儿童在早期的发展。这套工具的核心将是一个装有传感器的床，它将在孩子不知情的情况下从孩子身上收集多种夜间生理和环境数据。然后，这些数据将被汇总成睡眠质量指标，可以与白天的健康状况和与儿童个性化教育计划相一致的发展参数进行比较。任何与残疾儿童打交道的人都会肯定，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。在严重残疾儿童的一生中，这种努力提供了加速发展的潜力，因为在生活质量和节省费用方面，这种努力给其家庭和社区带来的终身利益是最大的。此外，不引人注目的夜间和白天监测工具为其他人群提供了好处，包括神经性儿童和患有睡眠呼吸暂停和其他夜间疾病的儿童/成人。这些工具可以被视为“成果力量倍增器”，通过降低特殊教育不成比例的成本，增加可用于满足日益增长的需求的资源基础，并提供可快速实施和部署的大规模解决方案，解决特殊教育面临的根本问题，进而解决残疾服务社区面临的根本问题。堪萨斯州立大学（Manhattan， KS）和Heartspring （Wichita， KS）合作的总体目标是开发和评估一套工具，全天候跟踪残疾儿童的健康状况。四项研究旨在支持这一目标，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数据，并根据这些数据制定睡眠质量指标；获得使用各种方式评估儿童日间健康/发育的参数；建立将睡眠质量与白天表现参数联系起来的统计模型，以确定严重残疾儿童的睡眠质量、学习和发展之间的重要关系；并与更广泛的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，其中包含传感设备，可提供心率、呼吸率、体表温度、运动、床上/床下活动、癫痫发作、声音、尿床频率/时间、环境噪声、温度、湿度、压力和光照水平等参数。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，这些指标表明儿童的健康和发展与临床医生和辅助教育工作者所采用的基于结果的治疗方法相一致。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白天分析，以及为KSU和Heartspring员工和学生提供工资支持。这些数据收集机制在以下方面提供了革命性改进的潜力：(a)对严重残疾儿童的健康和发展进行量化，其中许多儿童不会说话；(b)了解睡眠质量，因为它与儿童福祉和发展有关；(c)可以提供信息和加速个性化教育计划的更新以及治疗和药物方面的积极变化的数据；(d)减轻护理负担。(e)改善严重残疾儿童及其照料者的生活质量。

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.