A tool for high-throughput quantification of sleep-wake transitions in data from noninvasive piezoelectric cage systems

Quantifying sleep quality in rodent models is critical for understanding its impact on neurological health and disease. Piezoelectric cage systems enable rapid, noninvasive measurement of multiple sleep metrics for large sample sizes of rodents. Although sleep duration is commonly reported, sleep fragmentation, which is a key feature of sleep architecture implicated in neurodegenerative disease, circadian rhythm disruption, and injury models, is not produced. We developed a standardized Microsoft Excel™-based tool for quantifying sleep-wake transitions, a scalable proxy for sleep fragmentation, in data from rodents recorded by a piezoelectric cage system. The tool extracts transitions from 2-second binned activity data, which are output by the system’s software. The pipeline we developed that incorporates this tool enables high-throughput analysis of sleep fragmentation across large datasets with minimal user intervention. We demonstrate the applicability of this tool and associated pipeline by analyzing 24-hour sleep-wake behavior in wild-type male and female mice. The approach facilitated identification of biologically meaningful sex differences in sleep fragmentation patterns. Female mice exhibited more frequent transitions between sleep and wake states, particularly during the light period, consistent with increased sleep fragmentation. This is the first method developed for quantifying sleep fragmentation from activity data recorded by noninvasive piezoelectric cage systems, and represents a standardized, reproducible, and publicly accessible approach with wide application in rodent models. It enhances the utility of piezoelectric cage systems and supports noninvasive phenotyping of sleep architecture in neuroscience research, particularly where high-throughput or minimally invasive methods are required. • Sleep–wake transitions quantify fragmentation with high temporal resolution • GLMM validation confirms exceptional consistency across multiple cohorts • Open-source macro enables rapid, reproducible transition quantification • Sex differences in sleep fragmentation were detected using this transition-based method • Framework adaptable to other noninvasive sleep-monitoring systems