Device to control circadian-effective light in Alzheimer's disease environments

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Project Summary This proposed project will develop and field-test a device that accurately monitors and controls the circadian stimulus (CS) for Alzheimer disease (AD) and Alzheimer-disease-related dementia (ADRD) patients in nursing homes. Human biology has evolved to have two distinct optical systems: the visual system, by which we see and process images, and the circadian system, which regulates our biological clock and associated biological systems. These two systems have significantly different spectral and temporal responses to optical input. Specifically, circadian stimulation peaks at 460 nm and responds after several minutes of optical activation, while the visual system peaks at 555 nm and responds nearly instantaneously to inputs. All lighting systems are designed and installed in buildings with consideration only given to the photopic (visual) system and all light meters used to characterize lighting buildings are calibrated to measure photopic light, not CS. While a broad and growing body of research has documented the impacts of the circadian system on human health, including regulating sleep and improving cognition in AD/ADRD patients, research on the CS experienced by AD/ADRD patients is extremely limited. Researchers at the Lighting Research Center at Rensselaer Polytechnic Institute developed the Daysimeter, a calibrated light meter that measures circadian light and circadian stimulus. In Phase I of this project, researchers modified an existing workstation-based lighting control system they previously developed for the visual system to include Daysimeter technology, allowing this control system to record CS measurements. The accuracy of these CS measurements was confirmed in the laboratory and field-testing of 20 of devices is currently ongoing in AD/ADRD nursing homes. In this Phase II application, researchers propose adding control features to this device so that lighting can be controlled to optimize CS dosages in AD/ADRD patient environments. Machine learning-based lighting control algorithms will be driven by continuous light level and spectrum measurements as well as periodic (e.g., daily) patient health data. Data from these devices would be wirelessly transmitted to researchers via an Internet gateway and associated cloud-based data management systems. These data would be of immediate value for gaining a better understanding of AD/ADRD patients' CS exposure and could ultimately result in new lighting systems and/or building codes that consider both our visual and circadian systems. Following the development phase, 30 CS-enabled lighting control systems will be field tested over a 22-week test period. Researchers aim to commercialize this CS-enabled lighting control system shortly after the completion of this field test and the Phase II project specifically targeting AD/ADRD nursing home applications.