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Sponsor study identifier
observational
500
1 country
2
Study Start
November 17, 2026
EstimatedPlanned date reported by the registry; this milestone is not confirmed as achieved.
Primary Completion
March 1, 2028
EstimatedPlanned date reported by the registry; this milestone is not confirmed as achieved.
Study Completion
March 1, 2028
EstimatedPlanned date reported by the registry; this milestone is not confirmed as achieved.
This project aims to develop and evaluate an innovative, non-invasive diagnostic system based on a smart mattress for detecting obstructive sleep apnea (OSA), as well as assessing overall sleep quality and identifying periodic limb movements. The main goal is to improve the accuracy of sleep apnea diagnosis while providing a less invasive solution suitable for home use, ultimately enhancing patients' quality of life. A descriptive, observational, prospective study will be conducted to analyze data obtained from diagnostic polysomnographies performed at the Sleep Unit of San Pedro Hospital between November 17, 2026, and March 1, 2028. Patients will use the smart mattress, and its measurements will be compared with polysomnography results. This comparison will allow for the optimization of the mattress's artificial intelligence, training it to accurately recognize respiratory patterns and sleep-related events, including positional apneas and periodic limb movements. Key technical objectives include: Determining the sensitivity, specificity, and predictive values of the mattress in detecting apneas, hypopneas, and limb movements compared to polysomnography. Evaluating the agreement between the mattress and polysomnography for sleep variables such as total sleep time, sleep efficiency, sleep stages, micro-arousals, and patient position. Assessing whether measurement accuracy varies by sleeping position or age group (adults vs. children). Measuring subjective sleep quality using the Groningen Sleep Quality Scale (GSQS-8). Performing a descriptive analysis of patient demographics. Hypotheses: The smart mattress will detect obstructive sleep apnea, sleep quality, and periodic limb movements with accuracy comparable to polysomnography. The system will provide a reliable, non-invasive, home-friendly diagnostic method. Measurements of the apnea-hypopnea index (AHI) and limb movements will show high sensitivity, specificity, and predictive values, both overall and according to OSA severity. There will be good agreement between mattress measurements and polysomnography for most sleep variables. Accuracy may vary depending on the patient's sleeping position. Measurements will correlate well across adults and pediatric patients. Subjective sleep quality scores (GSQS-8) will be consistent with objective mattress data. This project seeks to develop a more accurate, accessible, and non-invasive diagnostic system for OSA, combining advanced technology with ease of home use. By training the mattress's AI to recognize sleep patterns and events, it aims to optimize the detection of positional apneas, providing patients with better monitoring, early intervention, and improved quality of life.
Registry-reported information. Elapsed time and enrollment totals alone do not measure study progress or recruitment pace.
March 1, 2028
EstimatedPlanned date reported by the registry; this milestone is not confirmed as achieved.
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Dates and qualifiers reported by the registry. Estimated dates do not confirm that a milestone has occurred.
February 10, 2026
Actual (reported)February 25, 2026
Actual (reported)November 17, 2026
EstimatedPlanned date reported by the registry; this milestone is not confirmed as achieved.
March 1, 2028
EstimatedPlanned date reported by the registry; this milestone is not confirmed as achieved.
March 1, 2028
EstimatedPlanned date reported by the registry; this milestone is not confirmed as achieved.
Diagnostic accuracy of the smart mattress for detecting sleep apnea.
Measured by: Sensitivity Specificity Predictive values (PPV/NPV) Compared with polysomnography (PSG).
Night of simultaneous PSG and mattress recording (one night per participant).
Total sleep time
Night of simultaneous PSG and mattress recording (one night per participant).
Diagnostic accuracy according to sleep position.
Night of simultaneous PSG and mattress recording (one night per participant).
Diagnostic accuracy by age group.
Night of simultaneous PSG and mattress recording (one night per participant).
Subjective sleep quality (GSQS-8).
Night of simultaneous PSG and mattress recording (one night per participant).
Descriptive demographic data.
Night of simultaneous PSG and mattress recording (one night per participant).
Patients will undergo the PSG on a smart mattress, which will allow simultaneous recording of: Standard PSG data, considered the gold standard in sleep studies. Data generated by the smart mattress, including signals and metrics related to movement, breathing, and other physiological parameters detectable by the device. The data obtained from the mattress will be compared with the PSG results in order to: Validate the mattress's ability to detect respiratory patterns and events during sleep. Optimize and train the mattress's artificial intelligence system, improving its diagnostic accuracy in identifying respiratory events and other sleep disturbances.
During a single night of recording, the participant will sleep on a smart mattress equipped with sensors for the continuous monitoring of sleep parameters. The data obtained will subsequently be compared and validated against polysomnography (PSG) recordings, considered the gold-standard reference for the objective evaluation of sleep architecture and quality, as well as respiratory events.
Registry-reported names are shown in full. Names without a link have not yet been matched to a Syfrah profile.
Diagnostic polysomnographies performed at the Sleep Unit of San Pedro Hospital from November 17, 2026 to March 1, 2028.
Center for Biomedical Research of La Rioja
Logroño, La Rioja, 26006, Spain
San Pedro University Hospital
Logroño, La Rioja, 26006, Spain
Ding F, Cotton-Clay A, Fava L, Easwar V, Kinsolving A, Kahn P, Rama A, Kushida C. Polysomnographic validation of an under-mattress monitoring device in estimating sleep architecture and obstructive sleep apnea in adults. Sleep Med. 2022 Aug;96:20-27. doi: 10.1016/j.sleep.2022.04.010. Epub 2022 Apr 22.
Byun JH, Kim KT, Moon HJ, Motamedi GK, Cho YW. The first night effect during polysomnography, and patients' estimates of sleep quality. Psychiatry Res. 2019 Apr;274:27-29. doi: 10.1016/j.psychres.2019.02.011. Epub 2019 Feb 6.
Alejandra Roncero Lázaro, MD
Hospital Universitario San Pedro de Logroño
First Submitted
February 10, 2026
First Posted
February 25, 2026
Study Start
November 17, 2026
EstimatedPlanned date reported by the registry; this milestone is not confirmed as achieved.
Primary Completion
March 1, 2028
Contact the study team to confirm eligibility.
9. Welltech Electronics.
Kobayashi M, Namba K, Tsuiki S, Nakamura M, Hayashi M, Mieno Y, Imizu H, Fujita S, Yoshikawa A, Sakakibara H, Inoue Y. Validity of sheet-type portable monitoring device for screening obstructive sleep apnea syndrome. Sleep Breath. 2013 May;17(2):589-95. doi: 10.1007/s11325-012-0725-z. Epub 2012 Jun 16.
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Benjafield AV, Ayas NT, Eastwood PR, Heinzer R, Ip MSM, Morrell MJ, Nunez CM, Patel SR, Penzel T, Pepin JL, Peppard PE, Sinha S, Tufik S, Valentine K, Malhotra A. Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis. Lancet Respir Med. 2019 Aug;7(8):687-698. doi: 10.1016/S2213-2600(19)30198-5. Epub 2019 Jul 9.
Senaratna CV, Perret JL, Lodge CJ, Lowe AJ, Campbell BE, Matheson MC, Hamilton GS, Dharmage SC. Prevalence of obstructive sleep apnea in the general population: A systematic review. Sleep Med Rev. 2017 Aug;34:70-81. doi: 10.1016/j.smrv.2016.07.002. Epub 2016 Jul 18.
Duran J, Esnaola S, Rubio R, Iztueta A. Obstructive sleep apnea-hypopnea and related clinical features in a population-based sample of subjects aged 30 to 70 yr. Am J Respir Crit Care Med. 2001 Mar;163(3 Pt 1):685-9. doi: 10.1164/ajrccm.163.3.2005065.
Planned date reported by the registry; this milestone is not confirmed as achieved.
Study Completion
March 1, 2028
EstimatedPlanned date reported by the registry; this milestone is not confirmed as achieved.
Last Updated
March 3, 2026
Record last verified: 2026-02
Participant data is anonymized when obtained at the source.
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Source: ClinicalTrials.gov.
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