NCT Number: NCT06606691
This project is an observational study that aims to evaluate the accuracy of wearable devices in detecting potential sleep-related breathing disorders (SRBD) in individuals visiting the Sleep-Related Breathing Disorders and Home Ventilation Unit. The main goal of the study is to determine if wearable devices, like sleep and activity-tracking wristbands and watches, can effectively supplement the detection of these disorders.
The study will analyze various variables related to sleep quality and quantity. Participants will be asked to wear a Xiaomi Mi Band 8 device during an overnight hospital polygraphy test, which will be conducted for one day in their usual daily environment. Additionally, at the beginning of their participation, they will need to complete a questionnaire collecting information about sociodemographic variables, daily habits, routines, and their assessment using the Epworth Sleepiness Scale.
After completing the polygraphy test and using the Xiaomi device, participants will be required to answer another questionnaire addressing aspects related to their sleep quality and habits during this period.
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Notify Me18 year and older
All sexes
Observational
Hospital Álvaro Cunqueiro, Vigo, Pontevedra, Spain
In recent years, sleep disorders have gained importance due to their high prevalence and impact on daily life, affecting people's ability to perform daily tasks and reducing quality of life. These disorders include difficulties falling asleep, respiratory interruptions, and poor sleep quality, with sleep-related breathing disorders (SRBD), such as obstructive sleep apnea (OSA), being particularly significant. OSA, which involves repeated airway obstructions during sleep, is especially common in older adults, individuals with obesity, and men, but it remains frequently underdiagnosed.
SRBD not only disrupts sleep but also increases the risk of chronic conditions like diabetes, hypertension, and strokes while creating an economic burden due to higher demand for medical resources. Their effects on physical and mental health lead to fatigue, reduced productivity, workplace accidents, and even disability, highlighting the need for more efficient diagnostic and management tools.
While polysomnography (PSG) is the gold standard for diagnosing sleep disorders, its high cost and invasive nature limit its accessibility. Wearable devices, such as wristbands and watches, offer a more accessible and non-invasive alternative, providing real-time data on sleep, heart rate, and activity. Though promising, these devices still require further research to confirm their accuracy in detecting SRBD. This project aims to evaluate the effectiveness of wearables as complementary tools in diagnosing and managing these disorders. Specifically, it has the following specific objectives: (1) To assess the accuracy, specificity, and sensitivity of wearable devices, such as wristbands and watches, in measuring blood oxygen saturation, heart rate, and activity, compared to nocturnal polygraphy. (2) To analyze the effectiveness of these devices in identifying individuals with potential sleep-related breathing disorders (SRBD) using unsupervised learning techniques. (3) To evaluate the impact and performance of an Artificial Intelligence model for detecting and classifying potential SRBD.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
The wearable device, Xiaomi Mi Smart Band 8, will be used solely for observational purposes to assess its accuracy in measuring sleep parameters, oxygen saturation, and heart rate in comparison to nocturnal polygraphy. Participants are receiving routine care as prescribed by their clinicians, and the wearable device is not part of their medical treatment but is being observed alongside standard polygraphy tests.
Time frame: 1 year
The Xiaomi Mi Smart Band 8 will record the duration of deep sleep, measured in minutes, to help estimate and identify potential sleep-related breathing disorders.
Time frame: 1 year
The Xiaomi Mi Smart Band 8 will record the duration of light sleep, measured in minutes, to assist in estimating and detecting potential sleep-related breathing disorders.
Time frame: 1 year
The Xiaomi Mi Smart Band 8 will record the duration of the REM sleep stage, measured in minutes, to help estimate and detect potential sleep-related breathing disorders.
Time frame: 1 year
The Xiaomi Mi Smart Band 8 will record the time spent awake after sleep onset, measured in minutes, to assist in estimating and detecting potential sleep-related breathing disorders.
Time frame: 1 year
The Xiaomi Mi Smart Band 8 device will track the total number of steps taken by the participant throughout a 24-hour period. The data will be used to assess physical activity levels and will be recorded as the total step count during the monitoring period.
Time frame: 1 year
The Xiaomi Mi Smart Band 8 device will measure the total distance covered by the participant, recorded in meters.
Time frame: 1 year
The Xiaomi Mi Smart Band 8 device will track the total duration of physical activity, recorded in minutes.
Time frame: 1 year
The nocturnal polygraph will track changes in body position of participants. This data will help assess physical activity, rest patterns, and potential sleep-related issues. The changes in position will be recorded without a specific unit of measurement.
Time frame: 1 year
The nocturnal polygraph will monitor and record body movements of the participants. These movements will be used to assess physical activity and rest patterns. The data will be recorded without a specific unit of measurement, focusing on the detection of movement occurrence and intensity.
Time frame: 1 year
Heart rate monitoring using the Xiaomi Mi Smart Band 8 device and nocturnal polygraph, to compare data from both devices. Both devices record the average heart rate, as well as the maximum and minimum (in BPM).
Time frame: 1 year
Oxygen saturation using the Xiaomi Mi Smart Band 8 device and nocturnal polygraph, to compare data from both devices. Both devices record the average oxygen saturation, as well as the maximum and minimum (in percentage).
Time frame: 1 year
This custom-designed questionnaire includes questions related to bedtime and wake-up time, time taken to fall asleep, number of nighttime awakenings, reasons for waking up, perceived sleep quality, pre-sleep activities, and perceived stress levels during the day. It also includes items assessing the quality and quantity of sleep using a 6-point Likert scale, ranging from 0 (strongly disagree) to 5 (strongly agree). The total score ranges from 0 to 45, with higher scores indicating a greater perception of sleep quality and quantity.
Universidade da Coruña
Other
Acronym: ReSTech
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