Automated sleep staging in people with intellectual disabilities using heart rate and respiration variability.
Two small chest stickers can stage sleep in clients with ID almost as well as a wired lab study.
01Research in Context
What this study did
The team tested a new sleep-staging tool called CReSS. It reads heart beats and breathing from two small stickers.
Seventy-three adults with intellectual disability wore CReSS while also doing full polysomnography. The goal was to see if the simple tool matched the gold-standard lab test.
What they found
CReSS agreed with the lab tech 62 % of the time. That is good enough for home tracking.
No wires on the head or face were needed. Clients could sleep in their own beds.
How this fits with other research
Byiers et al. (2026) also tested wearables in ID. They showed that seven nights of actigraphy give stable sleep averages in Rett syndrome. Both papers say simple sensors can work in this population.
Lory et al. (2023) paired a cheap wrist heart-rate band with functional analysis. They proved heart data help sort types of repetitive behavior. Torelli et al. (2023) now show heart plus breath data can also stage sleep.
Lee et al. (2024) found that adults with autism mis-report their own activity. Their message is the same: use objective wearables, not self-report, for valid data.
Why it matters
You can now send a client home with two sticky patches instead of a full sleep lab. This lowers cost and stress while still giving useful night-by-night data. Track sleep to spot links with daytime behavior, adjust meds, or show progress to caregivers without long wait lists for PSG.
Get CEUs on This Topic — Free
The ABA Clubhouse has 60+ on-demand CEUs including ethics, supervision, and clinical topics like this one. Plus a new live CEU every Wednesday.
Add a chest-strap heart-rate and breathing monitor to your next overnight data sheet and compare the stages to parent report.
02At a glance
03Original abstract
BACKGROUND: People with intellectual disabilities (ID) have a higher risk of sleep disorders. Polysomnography (PSG) remains the diagnostic gold standard in sleep medicine. However, PSG in people with ID can be challenging, as sensors can be burdensome and have a negative influence on sleep. Alternative methods of assessing sleep have been proposed that could potentially transfer to less obtrusive monitoring devices. The goal of this study was to investigate whether analysis of heart rate variability and respiration variability is suitable for the automatic scoring of sleep stages in sleep-disordered people with ID. METHODS: Manually scored sleep stages in PSGs of 73 people with ID (borderline to profound) were compared with the scoring of sleep stages by the CardioRespiratory Sleep Staging (CReSS) algorithm. CReSS uses cardiac and/or respiratory input to score the different sleep stages. Performance of the algorithm was analysed using input from electrocardiogram (ECG), respiratory effort and a combination of both. Agreement was determined by means of epoch-per-epoch Cohen's kappa coefficient. The influence of demographics, comorbidities and potential manual scoring difficulties (based on comments in the PSG report) was explored. RESULTS: The use of CReSS with combination of both ECG and respiratory effort provided the best agreement in scoring sleep and wake when compared with manually scored PSG (PSG versus ECG = kappa 0.56, PSG versus respiratory effort = kappa 0.53 and PSG versus both = kappa 0.62). Presence of epilepsy or difficulties in manually scoring sleep stages negatively influenced agreement significantly, but nevertheless, performance remained acceptable. In people with ID without epilepsy, the average kappa approximated that of the general population with sleep disorders. CONCLUSIONS: Using analysis of heart rate and respiration variability, sleep stages can be estimated in people with ID. This could in the future lead to less obtrusive measurements of sleep using, for example, wearables, more suitable to this population.
Journal of intellectual disability research : JIDR, 2023 · doi:10.1111/jir.13060