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.
Interagency Autism Coordinating Committee (IACC)
Autism Research Database (AFD)
