Evaluating Sleep Quality With Emerging Technologies
Conditions: Snoring, Sleep Disturbances, Hypoxia, Obstructive Sleep Apnea (OSA)
Sponsor: Case Western Reserve University

 
 
 
STUDY20221147 
 
Evaluating Sleep Quality with Emerging Technologies 
 
Document Date 2/17/2023 
 

 
Evaluating the Sleep of an Orthodontic Population Using Emerging Technologies 
 
Sleep disordered breathing is a highly prevalent indication of airflow limitation. Airflow limitations 
can occur at the level of the nasopharynx, oropharynx, or hypopharynx. Sleep disordered breathing 
has a multifactorial etiology, including large fat deposits, a large tongue, consumption of alcohol or 
sedatives, illness, or excessive relaxation of pharyngeal musculature, among others. These airflow 
limitations can cause daytime sleepiness, a decrease in productivity, increased blood pressure, or 
automobile accidents. 
Severe airflow limitations can be categorized as either apneas or hypopneas. An apnea involves 
total breathing cessation for over 10 seconds. A hypopnea involves a partial blockage of airflow for 
over 10 seconds. These events can culminate in arousal from sleep and gasping for air. The Apnea 
Hypopnea Index (AHI) is the number of events that occur per hour. 
A diagnosis of obstructive sleep apnea involves an AHI score of at least 5. Sleep apnea diagnosis is 
separated into three categories: mild, moderate, or severe. Mild sleep apnea consists of an AHI 
score of 5-15 events per hour. Moderate sleep apnea consists of an AHI score of 15-30 events per 
hour. Severe sleep apnea has an AHI score of over 30 events per hour.  
Risk factors for sleep disordered breathing include the male sex, age over 50, BMI >35, a large neck 
circumference, nasal congestion, diabetes, family history of OSA, and smoking. 
Obstructive sleep apnea is highly prevalent, as an estimated 29.4 million adults in the United States 
have obstructive sleep apnea, though 23.5 million are undiagnosed. This points to the importance 
of accurate screening tools. 
Sleep apnea can be treated using Continuous Positive Airway Pressure (CPAP), oral appliances such 
as mandibular advancement devices, a hypoglossal nerve stimulation device, lifestyle changes, or 
surgical intervention such as maxillomandibular advancement, removal of palatine tonsils/adenoids, 
tongue reduction surgery, or septoplasty. 
Untreated sleep disordered breathing can cause many negative effects, including weight gain, 
cognitive impairment, memory loss, and increased daytime sleepiness. It can also lead to an 
increased risk of comorbidities, including hypertension, atrial fibrillation, heart attack, stroke, Type 
2 diabetes, and depression. 
The gold standard for diagnosing obstructive sleep apnea is in-lab polysomnography. In-lab 
polysomnography records body movement, breathing rate, respiratory effort, nasal airflow, oxygen 
saturation, blood pressure, heart rate, eye movement, and electroencephalography. The results are 
interpreted by a sleep technician. Although polysomnography is highly accurate, it is also time-
consuming, uncomfortable for the participants, and expensive. 
An alternative to in-lab polysomnography is the home sleep apnea test (HSAT). A flow-based HSAT 
device typically consists of a small wearable monitor with leads, a nasal cannula, chest/abdomen 
belts, and a pulse oximeter. It records breathing rate, respiratory effort, nasal airflow, oxygen 

 
saturation, and heart rate. It generates a sleep report and can be used for the diagnosis of 
obstructive sleep apnea. It is a convenient option when compared to polysomnography, but it can 
be uncomfortable and requires participant compliance. Home sleep apnea tests have lower 
accuracy than in-lab polysomnography and depend on the participant for proper use. 
Questionnaires can also be used to identify obstructive sleep apnea risk factors. There are a variety 
of questionnaires that can be used, including the NOSE Score Questionnaire, Pittsburgh Sleep 
Quality Index, STOP-Bang Questionnaire, Insomnia Severity Index, PROMIS Sleep Disturbance 
Questionnaire, and Epworth Sleepiness Scale. 
The STOP-Bang Questionnaire provides a score of “low risk,” “intermediate risk,” or “high risk” for 
the participant’s risk of an Obstructive Sleep Apnea diagnosis. The participant will check either “yes” 
or “no” as a response to a series of questions. Each positive response will add one point to the 
participant’s overall score, which is used for the determination of OSA risk. An overall score of 0 – 2 
is “low risk,” a score of 3 – 4 is “intermediate risk,” and a score of 5 or greater is “high risk.” 
 
The NOSE Score Questionnaire involves a series of responses that yield a numerical score 
representative of the severity of nasal obstruction. The participant provides their responses to a 
variety of prompts using a ranking system from “Not a problem” (0 points) to “Severe problem” (4 
points). The numerical responses are added, then the sum is multiplied by 5, to provide a result of 
“mild,” “moderate,” “severe,” or “extreme” nasal obstruction. 
 

 
The PROMIS Sleep Disturbance Questionnaire evaluates the subject’s sleep quality through a series 
of statements that a subject ranks their agreement from 1 (not at all) through 5 (very much) for the 
past 7 days. After adding up the numerical values associated with each response, the subject will 
receive a raw score from 8-40. A conversion chart is used to convert from the raw score to the T 
Score. A T-Score of <55 is associated with no to slight sleep disturbance, 55.0-59.9 is associated with 
mild sleep disturbance, 60.0-69.9 is associated with moderate sleep disturbance, and ³70 is 
associated with severe sleep disturbance.  
 
 
The Epworth Sleepiness Scale determines the participant’s level of daytime sleepiness. It asks the 
participant to rank their likelihood of falling asleep during a variety of common activities on a scale 
from 0-3, where 0 is “would never doze,” and 3 is “high chance of dozing.” After adding up the 
numerical value of all their responses, the result will determine whether the participant exhibits 
excessive sleepiness. 
 

 
 
 
The Insomnia Severity Index (ISI) asks the subject to respond with their level of agreement to a 
series of prompts related to their sleep habits. The possible responses are on a scale of 0 – 4, where 
the lower numerical responses indicate little to no presence of insomnia symptoms. After 
completing the questionnaire, the numerical responses are summed for interpretation. An overall 
score of 0-7 indicates “no clinically significant insomnia,” a score of 8-14 indicates “subthreshold 
insomnia,” a score of 15-21 indicates clinical insomnia of moderate severity, and a score of 22-28 is 
severe clinical insomnia. 

 
 
Novel wearable technology has been developed that gives information about sleep habits, and 
some that have the potential to screen for Obstructive Sleep Apnea. Examples of some of these 
“wearables” include the Oura Smart Ring, Apple Watch, and Belun Ring. 
The Belun Ring (formally, Belun Sleep System BLS-100, Belun Technology Co. Ltd., Hong Kong) is a 
deep learning-facilitated, PPG and accelerometry-based medical-grade wearable, which was 
recently cleared by the US FDA for the diagnosis of moderate to severe OSA and sleep stage 
classification in subjects suspicious of OSA (K222579). A recent Belun Ring validation study 
demonstrated a moderate-to-substantial OSA diagnostic concordance and good overall accuracy in 
3-sleep stage classification (REM, non-REM, and wake).8 

 
 
The Belun Ring captures a variety of data points during each night of sleep. One such value is the 
Respiratory Event Index (REI), which is derived from the total recorded sleep time, heart rate 
variability, and oxygen saturation changes. The Belun Ring also captures sleep efficiency, which is 
calculated by dividing the time the participant is asleep by the total time in bed. The Belun Ring’s  
AHI score, “bAHI,” has been proven to have a high correlation with a polysomnography-obtained 
AHI score.5 
Smart phone apps have also been developed as a new technology used to screen for snoring or 
sleep apnea. For example, Sleep Cycle, SnoreLab, SleepScore, Drowzle, and Sleep Check Rx are 
available to the public and produce sleep data after nighttime use for the user’s interpretation. The 
Sleep Cycle app tracks time asleep, stages “Awake, Sleep, and Deep Sleep,” sleep regularity, time to 
bed, time woken up, time in bed, sleep efficiency, heart rate, and time snoring, and also records 
audio. A score report is generated from each night of sleep, and data are aggregated over time for 
pattern analysis. Sleep Cycle users also have the ability to add “sleep notes,” in which they may 
record outside factors that may have affected their night of sleep, for example, whether alcohol or 
caffeine was consumed, if they did a workout that day, if they were feeling sick, etc. Sleep Cycle is 
available in Apple App Store and Google Play store. The audio recordings are stored in the app, and 
are automatically deleted after 20 nights. 
 
Objectives 
 
To investigate the sleep of the adult orthodontic patient population at the Case Western Reserve 
University School of Dental Medicine using the NOSE Questionnaire, STOP-Bang Questionnaire, 
Epworth Sleepiness Scale, Insomnia Severity Index, PROMIS Sleep Disturbance Questionnaire, Sleep 
Cycle app, and Belun Ring. 
 
Experimental design 
 
The project will be a descriptive cross-sectional study. 
A total of 55 adult participants will be recruited from the Case Western Reserve Orthodontics Clinic, 
based on the sample size calculation with a power of 80%. Inclusion criteria: current adult patients 
in the Case Western Reserve Orthodontics Clinic, ages 20-75, willingness to give informed consent 

 
and participate in study, owner of a smartphone, and ability to return the Belun Ring and complete 
follow-up questionnaire. Exclusion criteria: age <20, currently or with history of taking blood 
pressure medication, currently undergoing transverse or anterior-posterior orthodontic correction, 
and currently pregnant or trying to become pregnant. 
Participants will provide informed consent and will be instructed on the steps of the study. 
Demographic information will be collected, including a participant identifier, age of participant, and 
sex of participant. The use of the Belun Ring will be demonstrated, and they will be instructed on 
use of the Sleep Cycle app. They will complete the NOSE ScoreQuestionnaire, STOP-Bang 
Questionnaire, Insomnia Severity Index, PROMIS Sleep Disturbance Questionnaire, and the Epworth 
Sleepiness Scale (ESS). 
Data collected from the STOP-Bang Questionnaire includes positive/negative responses to: snoring, 
tired, observed, pressure, BMI >35, age over 50, neck size large, male gender, and the resulting OSA 
risk assessment of low, intermediate, or high. 
Data collected from the NOSE Questionnaire includes positive or negative responses to: nasal 
congestion or stuffiness, nasal blockage or obstruction, trouble breathing through my nose, trouble 
sleeping, unable to get enough air through my nose during exercise or exertion, and the resulting 
classification of severity of nasal obstruction (mild, moderate, severe, extreme). 
Data collected from the Insomnia Severity Index include difficulty falling or staying asleep, problem 
with waking up too early, satisfaction level with current sleep pattern, noticeability of subject’s 
sleep problem to others, and amount of distress regarding current sleep habits. 
Data collected from the PROMIS Sleep Disturbance Questionnaire includes level of agreement with 
statements about the subject’s ability to fall asleep, quality of sleep, amount of sleep, level of 
satisfaction with their sleep, ability to stay asleep throughout the night.  
The Epworth Sleepiness Scale collects information regarding the subject’s likelihood of falling asleep 
during the following activities: sitting and reading, watching television, sitting in public, sitting in a 
car, lying down to rest, sitting and talking to someone, sitting quietly after lunch without alcohol, 
and while sitting in a car stopped in traffic. 
The participants are then instructed to wear the Belun Ring for seven nights and simultaneously use 
the Sleep Cycle app.  
Data collected from the Belun Ring includes the Respiratory Event Index (REI) (derived from total 
sleep time, heart rate variability, and O2 saturation changes), Sleep Efficiency (time participant is 
asleep divided by total time in bed), stress level, mean spO2 (%), Sleep Score (bAHI, Belun Ring’s 
version of AHI), REM sleep (percentage), minimum spO2 (%), mean pulse rate (bpm), percent of 
time below 90% oxygen saturation, and total sleep time (minutes).  
The Sleep Cycle app will collect the subject’s time asleep, stages “Awake, Sleep, and Deep Sleep,” 
sleep regularity, time to bed, time woken up, time in bed, sleep efficiency, heart rate, and time 
snoring. It also will record audio while the subject is asleep. During the night, the subject’s 

 
smartphone will be placed on their nightstand. The subjects also have the option to add “sleep 
notes” to give additional information about their night of sleep, for example, if they were feeling 
sick or if they exercised right before bed. 
The subjects will return to the Case Western Reserve Orthodontic Clinic for their next orthodontic 
adjustment appointment. The subjects will return the Belun Ring to the clinic and we will download 
the data. The Sleep Cycle Score Report from each night will be collected by either sharing via 
WhatsApp, an encrypted messaging service, or recording the data points manually into an Excel 
spreadsheet. 
Subjects will then complete a Follow-Up Questionnaire. They will record the dates they used the 
devices during sleep. Subjects will also indicate whether they had a “normal” night of sleep, or if 
they were experiencing sickness, allergies, or any other sleep disruptions that may have affected 
the data collected. They will also indicate whether they have a bed partner. 
Participants will be referred for further evaluation, if needed. 
 
Statistical Analysis Design 
 
Out of the seven nights of sleep studied, the five with the longest night of sleep will be used for 
analysis. The values from those five nights will be averaged for each patient.  
Descriptive statistics will be applied to the data, in order to determine reliability and consistency 
among different data collection methods, since similar variables are collected by different means.  
Correlation of data collected by different methods will be performed in order to cross examine and 
further validate results. 
We will compare the accuracy of the response to the STOP-Bang question “Do you snore?” to audio 
data from the Sleep Cycle app. We will also compare the amount of snoring reported to the nasal 
obstruction score of the NOSE questionnaire. We will compare the distribution of the STOP-Bang 
questionnaire results (low/medium/high risk of Obstructive Sleep Apnea) to the distribution of 
results from the sensors. We will compare the agreement in recommendation for follow-up 
between the STOP-Bang Questionnaire and the sensors. Last, we will collect the percentage of 
people in the adult orthodontic clinic that should be referred for further evaluation for potential 
intervention. 
 
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