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Gross-Isselmann JA, Eggert T, Wildenauer A, Dietz-Terjung S, Grosse Sundrup M, Schoebel C. Validation of the Sleepiz One + as a radar-based sensor for contactless diagnosis of sleep apnea. Sleep Breath 2024; 28:1691-1699. [PMID: 38744804 PMCID: PMC11303430 DOI: 10.1007/s11325-024-03057-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 04/17/2024] [Accepted: 05/08/2024] [Indexed: 05/16/2024]
Abstract
PURPOSE The cardiorespiratory polysomnography (PSG) is an expensive and limited resource. The Sleepiz One + is a novel radar-based contactless monitoring device that can be used e.g. for longitudinal detection of nocturnal respiratory events. The present study aimed to compare the performance of the Sleepiz One + device to the PSG regarding the accuracy of apnea-hypopnea index (AHI). METHODS From January to December 2021, a total of 141 adult volunteers who were either suspected of having sleep apnea or who were healthy sleepers took part in a sleep study. This examination served to validate the Sleepiz One + device in the presence and absence of additional SpO2 information. The AHI determined by the Sleepiz One + monitor was estimated automatically and compared with the AHI derived from manual PSG scoring. RESULTS The correlation between the Sleepiz-AHI and the PSG-AHI with and without additional SpO2 measurement was rp = 0.94 and rp = 0,87, respectively. In general, the Bland-Altman plots showed good agreement between the two methods of AHI measurement, though their deviations became larger with increasing sleep-disordered breathing. Sensitivity and specificity for recordings without additional SpO2 was 85% and 88%, respectively. Adding a SpO2 sensor increased the sensitivity to 88% and the specificity to 98%. CONCLUSION The Sleepiz One + device is a valid diagnostic tool for patients with moderate to severe OSA. It can also be easily used in the home environment and is therefore beneficial for e.g. immobile and infectious patients. TRIAL REGISTRATION NUMBER AND DATE OF REGISTRATION FOR PROSPECTIVELY REGISTERED TRIALS: This study was registered on clinicaltrials.gov (NCT04670848) on 2020-12-09.
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Affiliation(s)
| | - Torsten Eggert
- Devision of Sleep & Telemedicine, Ruhrlandklinik, University Medicine Essen, University of Duisburg-Essen, Essen, Germany
| | - Alina Wildenauer
- Devision of Sleep & Telemedicine, Ruhrlandklinik, University Medicine Essen, University of Duisburg-Essen, Essen, Germany
| | - Sarah Dietz-Terjung
- Devision of Sleep & Telemedicine, Ruhrlandklinik, University Medicine Essen, University of Duisburg-Essen, Essen, Germany
| | - Martina Grosse Sundrup
- Devision of Sleep & Telemedicine, Ruhrlandklinik, University Medicine Essen, University of Duisburg-Essen, Essen, Germany
| | - Christoph Schoebel
- Devision of Sleep & Telemedicine, Ruhrlandklinik, University Medicine Essen, University of Duisburg-Essen, Essen, Germany
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Tschopp S, Borner U, Caversaccio M, Tschopp K. Long-term night-to-night variability of sleep-disordered breathing using a radar-based home sleep apnea test: a prospective cohort study. J Clin Sleep Med 2024; 20:1079-1086. [PMID: 38415722 PMCID: PMC11217624 DOI: 10.5664/jcsm.11070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Revised: 02/04/2024] [Accepted: 02/07/2024] [Indexed: 02/29/2024]
Abstract
STUDY OBJECTIVES Night-to-night variability of sleep-disordered breathing limits the diagnostic accuracy of a single measurement. Multiple recordings using a reliable, affordable method could reduce the uncertainty and avoid misdiagnosis, which could be possible with radar-based home sleep apnea testing (HSAT). METHODS We recruited consecutive patients with suspected sleep-disordered breathing and performed contactless radar-based HSAT with automated scoring (Sleepiz One; Sleepiz AG, Zurich, Switzerland) over 10 nights. During the first night, patients were simultaneously measured with peripheral arterial tonometry. RESULTS Twenty-four of the 28 included patients could achieve a minimum of 4 measurements. The failure rate was 16% (37 of 238 measurements). The apnea-hypopnea index (AHI) and oxygen desaturation index were consistently lower with radar-based HSAT compared with peripheral arterial tonometry. The variability of the AHI was considerable, with a standard error of measurement of 5.2 events/h (95% confidence interval [CI]: 4.6-5.7 events/h) and a minimal detectable difference of 14.4 events/h (95% CI: 12.7-15.9 events/h). Alcohol consumption partially accounted for the variability, with an AHI increase of 1.7 events/h (95% CI: 0.6-2.8 events/h) for each standard drink. Based on a single measurement, 17% of patients were misdiagnosed and 32% were misclassified for sleep-disordered breathing severity. After 5 measurements, the mean AHI of the measured nights stabilized with no evidence of substantial changes with additional measurements. CONCLUSIONS Night-to-night variability is considerable and stable over 10 nights. HSAT using radar-based methods over multiple nights is feasible and well tolerated by patients. It could offer lower costs and allow for multiple-night testing to increase accuracy. However, validation and reducing the failure rate are necessary for implementation in the clinical routine. CLINICAL TRIAL REGISTRATION Registry: ClinicalTrials.gov; Name: Recording of Multiple Nights Using a New Contactless Device (Sleepiz One Connect) in Obstructive Sleep Apnea; URL: https://clinicaltrials.gov/study/NCT05134402; Identifier: NCT05134402. CITATION Tschopp S, Borner U, Caversaccio M, Tschopp K. Long-term night-to-night variability of sleep-disordered breathing using a radar-based home sleep apnea test: a prospective cohort study. J Clin Sleep Med. 2024;20(7):1079-1086.
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Affiliation(s)
- Samuel Tschopp
- Department of Otorhinolaryngology, Head and Neck Surgery, Inselspital, University Hospital and University of Bern, Bern, Switzerland
- Department of Otorhinolaryngology, Head and Neck Surgery, Kantonsspital Baselland, Liestal, Switzerland
| | - Urs Borner
- Department of Otorhinolaryngology, Head and Neck Surgery, Inselspital, University Hospital and University of Bern, Bern, Switzerland
| | - Marco Caversaccio
- Department of Otorhinolaryngology, Head and Neck Surgery, Inselspital, University Hospital and University of Bern, Bern, Switzerland
| | - Kurt Tschopp
- Department of Otorhinolaryngology, Head and Neck Surgery, Kantonsspital Baselland, Liestal, Switzerland
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Choo YJ, Lee GW, Moon JS, Chang MC. Application of non-contact sensors for health monitoring in hospitals: a narrative review. Front Med (Lausanne) 2024; 11:1421901. [PMID: 38933102 PMCID: PMC11199382 DOI: 10.3389/fmed.2024.1421901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 05/31/2024] [Indexed: 06/28/2024] Open
Abstract
The continuous monitoring of the health status of patients is essential for the effective monitoring of disease progression and the management of symptoms. Recently, health monitoring using non-contact sensors has gained interest. Therefore, this study aimed to investigate the use of non-contact sensors for health monitoring in hospital settings and evaluate their potential clinical applications. A comprehensive literature search was conducted using PubMed to identify relevant studies published up to February 26, 2024. The search terms included "hospital," "monitoring," "sensor," and "non-contact." Studies that used non-contact sensors to monitor health status in hospital settings were included in this review. Of the 38 search results, five studies met the inclusion criteria. The non-contact sensors described in the studies were radar, infrared, and microwave sensors. These non-contact sensors were used to obtain vital signs, such as respiratory rate, heart rate, and body temperature, and were then compared with the results from conventional measurement methods (polysomnography, nursing records, and electrocardiography). In all the included studies, non-contact sensors demonstrated a performance similar to that of conventional health-related parameter measurement methods. Non-contact sensors are expected to be a promising solution for health monitoring in hospital settings.
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Affiliation(s)
- Yoo Jin Choo
- Department of Physical Medicine and Rehabilitation, College of Medicine, Yeungnam University, Daegu, Republic of Korea
| | - Gun Woo Lee
- Department of Orthopaedic Surgery, College of Medicine, Yeungnam University, Daegu, Republic of Korea
| | - Jun Sung Moon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Yeungnam University, Daegu, Republic of Korea
| | - Min Cheol Chang
- Department of Physical Medicine and Rehabilitation, College of Medicine, Yeungnam University, Daegu, Republic of Korea
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Hayano J, Yamamoto H, Tanaka H, Yuda E. Piezoelectric rubber sheet sensor: a promising tool for home sleep apnea testing. Sleep Breath 2024; 28:1273-1283. [PMID: 38358413 PMCID: PMC11196299 DOI: 10.1007/s11325-024-02991-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 12/19/2023] [Accepted: 01/04/2024] [Indexed: 02/16/2024]
Abstract
PURPOSE This study aimed to develop an unobtrusive method for home sleep apnea testing (HSAT) utilizing micromotion signals obtained by a piezoelectric rubber sheet sensor. METHODS Algorithms were designated to extract respiratory and ballistocardiogram components from micromotion signals and to detect respiratory events as the characteristic separation of the fast envelope of the respiration component from the slow envelope. In 78 adults with diagnosed or suspected sleep apnea, micromotion signal was recorded with a piezoelectric rubber sheet sensor placed beneath the bedsheet during polysomnography. In a half of the subjects, the algorithms were optimized to calculate respiratory event index (REI), estimating apnea-hypopnea index (AHI). In the other half of subjects, the performance of REI in classifying sleep apnea severity was evaluated. Additionally, the predictive value of the frequency of cyclic variation in heart rate (Fcv) obtained from the ballistocardiogram was assessed. RESULTS In the training group, the optimized REI showed a strong correlation with the AHI (r = 0.93). Using the optimal cutoff of REI ≥ 14/h, subjects with an AHI ≥ 15 were identified with 77.8% sensitivity and 90.5% specificity. When applying this REI to the test group, it correlated closely with the AHI (r = 0.92) and identified subjects with an AHI ≥ 15 with 87.5% sensitivity and 91.3% specificity. While Fcv showed a modest correlation with AHI (r = 0.46 and 0.66 in the training and test groups), it lacked independent predictive power for AHI. CONCLUSION The analysis of respiratory component of micromotion using piezoelectric rubber sheet sensors presents a promising approach for HSAT, providing a practical and effective means of estimating sleep apnea severity.
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Affiliation(s)
| | | | - Haruhito Tanaka
- Gifu Mates Sleep Clinic, Gifu, Japan
- International Institute for Integrative Sleep Medicine (IIIS), University of Tsukuba, Tsukuba, Japan
| | - Emi Yuda
- Heart Beat Science Lab Inc., Sendai, Japan
- Graduate School of Information Sciences, Tohoku University, Sendai, Japan
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Khalil C, Zarabi S, Kirkham K, Soni V, Li Q, Huszti E, Yadollahi A, Taati B, Englesakis M, Singh M. Validity of non-contact methods for diagnosis of Obstructive Sleep Apnea: a systematic review and meta-analysis. J Clin Anesth 2023; 87:111087. [PMID: 36868010 DOI: 10.1016/j.jclinane.2023.111087] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 01/16/2023] [Accepted: 02/20/2023] [Indexed: 03/05/2023]
Abstract
STUDY OBJECTIVE Obstructive Sleep Apnea (OSA) is associated with increased perioperative cardiac, respiratory and neurological complications. Pre-operative OSA risk assessment is currently done through screening questionnaires with high sensitivity but poor specificity. The objective of this study was to evaluate the validity and diagnostic accuracy of portable, non-contact devices in the diagnosis of OSA as compared with polysomnography. DESIGN This study is a systematic review of English observational cohort studies with meta-analysis and risk of bias assessment. SETTING Pre-operative, including in the hospital and clinic setting. PATIENTS Adult patients undergoing sleep apnea assessment using polysomnography and an experimental non-contact tool. INTERVENTIONS A novel non-contact device, which does not utilize any monitor that makes direct contact with the patient's body, in conjunction with polysomnography. MEASUREMENTS Primary outcomes included pooled sensitivity and specificity of the experimental device in the diagnosis of obstructive sleep apnea, in comparison to gold-standard polysomnography. RESULTS Twenty-eight of 4929 screened studies were included in the meta-analysis. A total of 2653 patients were included with the majority being patients referred to a sleep clinic (88.8%). Average age was 49.7(SD±6.1) years, female sex (31%), average body mass index of 29.5(SD±3.2) kg/m2, average apnea-hypopnea index (AHI) of 24.7(SD±5.6) events/h, and pooled OSA prevalence of 72%. Non-contact technology used was mainly video, sound, or bio-motion analysis. Pooled sensitivity and specificity of non-contact methods in moderate to severe OSA diagnosis (AHI > 15) was 0.871 (95% CI 0.841,0.896, I2 0%) and 0.8 (95% CI 0.719,0.862), respectively (AUC 0.902). Risk of bias assessment showed an overall low risk of bias across all domains except for applicability concerns (none were conducted in the perioperative setting). CONCLUSION Available data indicate contactless methods have high pooled sensitivity and specificity for OSA diagnosis with moderate to high level of evidence. Future research is needed to evaluate these tools in the perioperative setting.
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Affiliation(s)
- Carlos Khalil
- University of Toronto, 27 King's College Cir, Toronto, ON M5S 1A1, Canada
| | - Sahar Zarabi
- University of Toronto, 27 King's College Cir, Toronto, ON M5S 1A1, Canada
| | - Kyle Kirkham
- University of Toronto, 27 King's College Cir, Toronto, ON M5S 1A1, Canada; Department of Anesthesiology and Pain Medicine, University Health Network, 200 Elizabeth Street, Toronto, ON M5G 2C4, Canada
| | - Vedish Soni
- McMaster University, 1280 Main Street West, Hamilton, ON, Canada, L8S 4L8
| | - Qixuan Li
- University of Toronto, 27 King's College Cir, Toronto, ON M5S 1A1, Canada; Biostatistics Research Unit, University Health Network; 200 Elizabeth Street, Toronto, ON M5G 2C4, Canada
| | - Ella Huszti
- University of Toronto, 27 King's College Cir, Toronto, ON M5S 1A1, Canada; Biostatistics Research Unit, University Health Network; 200 Elizabeth Street, Toronto, ON M5G 2C4, Canada
| | - Azadeh Yadollahi
- University of Toronto, 27 King's College Cir, Toronto, ON M5S 1A1, Canada; KITE-Toronto Rehabilitation Institute (TRI), University Health Network, 550 University Avenue, Toronto, ON M5G 2A2, Canada
| | - Babak Taati
- University of Toronto, 27 King's College Cir, Toronto, ON M5S 1A1, Canada; KITE-Toronto Rehabilitation Institute (TRI), University Health Network, 550 University Avenue, Toronto, ON M5G 2A2, Canada
| | - Marina Englesakis
- Library and Information Services, University Health Network, 200 Elizabeth St., Toronto, ON M5G 2C4, Canada
| | - Mandeep Singh
- University of Toronto, 27 King's College Cir, Toronto, ON M5S 1A1, Canada; Department of Anesthesiology and Pain Medicine, University Health Network, 200 Elizabeth Street, Toronto, ON M5G 2C4, Canada.
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Portable evaluation of obstructive sleep apnea in adults: A systematic review. Sleep Med Rev 2023; 68:101743. [PMID: 36657366 DOI: 10.1016/j.smrv.2022.101743] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 12/10/2022] [Accepted: 12/23/2022] [Indexed: 01/07/2023]
Abstract
Obstructive sleep apnea (OSA) is a significant healthcare burden affecting approximately one billion people worldwide. The prevalence of OSA is rising with the ongoing obesity epidemic, a key risk factor for its development. While in-laboratory polysomnography (PSG) is the gold standard for diagnosing OSA, it has significant drawbacks that prevent widespread use. Portable devices with different levels of monitoring are available to allow remote assessment for OSA. To better inform clinical practice and research, this comprehensive systematic review evaluated diagnostic performances, study cost and patients' experience of different levels of portable sleep studies (type 2, 3, and 4), as well as wearable devices and non-contact systems, in adults. Despite varying study designs and devices used, portable diagnostic tests are found to be sufficient for initial screening of patients at risk of OSA. Future studies are needed to evaluate cost effectiveness with the incorporation of portable diagnostic tests into the diagnostic pathway for OSA, as well as their application in patients with chronic respiratory diseases and other comorbidities that may affect test performance.
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A systematic review of the validity of non-invasive sleep-measuring devices in mid-to-late life adults: Future utility for Alzheimer's disease research. Sleep Med Rev 2022; 65:101665. [DOI: 10.1016/j.smrv.2022.101665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 06/21/2022] [Accepted: 06/23/2022] [Indexed: 11/24/2022]
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Sleep Position Detection with a Wireless Audio-Motion Sensor—A Validation Study. Diagnostics (Basel) 2022; 12:diagnostics12051195. [PMID: 35626350 PMCID: PMC9139663 DOI: 10.3390/diagnostics12051195] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 05/06/2022] [Accepted: 05/09/2022] [Indexed: 02/01/2023] Open
Abstract
It is well documented that body position significantly affects breathing indices during sleep in patients with obstructive sleep apnea. They usually worsen while changing from a non-supine to a supine position. Therefore, body position should be an accurately measured and credible parameter in all types of sleep studies. The aim of this study was to specify the accuracy of a neck-based monitoring device (Clebre, Olsztyn, Poland) mounted at the suprasternal notch, in determining a supine and non-supine sleeping position, as well as specific body positions during sleep, in comparison to polysomnography (PSG). A sleep study (PSG along with a neck-based audio-motion sensor) was performed on 89 consecutive patients. The accuracy in determining supine and non-supine positions was 96.9%±3.9% and 97.0%±3.6%, respectively. For lateral positions, the accuracy was 98.6%±2% and 97.4%±4.5% for the right and left side, respectively. The prone position was detected with an accuracy of 97.3%±5.6%. The study showed a high accuracy in detecting supine, as well as other gross positions, during sleep based on a sensor attached to the suprasternal notch, compared to the PSG study. We feel that the suprasternal notch is a promising area for placing wireless sleep study devices.
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Serrano Alarcón Á, Martínez Madrid N, Seepold R. A Minimum Set of Physiological Parameters to Diagnose Obstructive Sleep Apnea Syndrome Using Non-Invasive Portable Monitors. A Systematic Review. Life (Basel) 2021; 11:1249. [PMID: 34833126 PMCID: PMC8623368 DOI: 10.3390/life11111249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 11/08/2021] [Accepted: 11/13/2021] [Indexed: 11/17/2022] Open
Abstract
Introduction. Despite its high accuracy, polysomnography (PSG) has several drawbacks for diagnosing obstructive sleep apnea (OSA). Consequently, multiple portable monitors (PMs) have been proposed. Objective. This systematic review aims to investigate the current literature to analyze the sets of physiological parameters captured by a PM to select the minimum number of such physiological signals while maintaining accurate results in OSA detection. Methods. Inclusion and exclusion criteria for the selection of publications were established prior to the search. The evaluation of the publications was made based on one central question and several specific questions. Results. The abilities to detect hypopneas, sleep time, or awakenings were some of the features studied to investigate the full functionality of the PMs to select the most relevant set of physiological signals. Based on the physiological parameters collected (one to six), the PMs were classified into sets according to the level of evidence. The advantages and the disadvantages of each possible set of signals were explained by answering the research questions proposed in the methods. Conclusions. The minimum number of physiological signals detected by PMs for the detection of OSA depends mainly on the purpose and context of the sleep study. The set of three physiological signals showed the best results in the detection of OSA.
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Affiliation(s)
- Ángel Serrano Alarcón
- School of Informatics, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany;
| | - Natividad Martínez Madrid
- School of Informatics, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany;
- Institute of Digital Medicine, I.M. Sechenov First Moscow State Medical University, 2-4 Bolshaya Pirogovskaya st., 119435 Moscow, Russian Federation;
| | - Ralf Seepold
- Institute of Digital Medicine, I.M. Sechenov First Moscow State Medical University, 2-4 Bolshaya Pirogovskaya st., 119435 Moscow, Russian Federation;
- HTWG Konstanz, Department of Computer Science, Alfred-Wachtel-Str. 8, 78462 Konstanz, Germany
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Ong JC, Gamaldo C. Optimizing Behavioral Sleep Strategies. ACTA ACUST UNITED AC 2020; 26:1075-1081. [PMID: 32756237 DOI: 10.1212/con.0000000000000876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Patients are increasingly looking to optimize sleep as a health and wellness strategy. Sleep health is often individualized based on three elements that correspond to overall physical and mental well-being: (1) sleep quality, which refers to the continuity and depth of sleep as well as a feeling of restoration upon awakening; (2) sleep quantity, which refers to the duration of sleep that is appropriate for a given age group; and (3) timing of the sleep window, which refers to the positioning of sleep that is aligned with an individual's circadian rhythm for sleep or an ideal circadian zone. In the past, prescribing hypnotic medications was considered the primary approach for improving sleep. However, there has been a recent paradigm shift to favor behavioral approaches, particularly in the case of insomnia where cognitive-behavioral therapy has been shown to have a more favorable benefit-to-harm profile than medications. The clinical vignette is presented here as a springboard for discussion regarding the latest evidence and efficacy for sleep behavior techniques and consumer monitoring devices developed to improve sleep health and awareness for clinicians to consider when educating their patients on maximizing sleep health behaviors.
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Seidel S, Garn H, Gall M, Kohn B, Wiesmeyr C, Waser M, Coronel C, Stefanic A, Böck M, Wimmer M, Mandl M, Högl B, Klösch G. Contactless detection of periodic leg movements during sleep: A 3D video pilot study. J Sleep Res 2020; 29:e12986. [PMID: 32017288 PMCID: PMC7540172 DOI: 10.1111/jsr.12986] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 01/02/2020] [Accepted: 01/09/2020] [Indexed: 12/16/2022]
Abstract
In clinical practice, the quality of polysomnographic recordings in children and patients with neurodegenerative diseases may be affected by sensor displacement and diminished total sleep time due to stress during the recording. In the present study, we investigated if contactless three‐dimensional (3D) detection of periodic leg movements during sleep was comparable to polysomnography. We prospectively studied a sleep laboratory cohort from two Austrian sleep laboratories. Periodic leg movements during sleep were classified according to the standards of the World Association of Sleep Medicine and served as ground truth. Leg movements including respiratory‐related events (A1) and excluding respiratory‐related events (A2 and A3) were presented as A1, A2 and A3. Three‐dimensional movement analysis was carried out using an algorithm developed by the Austrian Institute of Technology. Fifty‐two patients (22 female, mean age 52.2 ± 15.1 years) were included. Periodic leg movement during sleep indexes were significantly higher with 3D detection compared to polysomnography (33.3 [8.1–97.2] vs. 30.7 [2.9–91.9]: +9.1%, p = .0055/27.8 [4.5–86.2] vs. 24.2 [0.00–88.7]: +8.2%, p = .0154/31.8 [8.1–89.5] vs. 29.6 [2.4–91.1]: +8.9%, p = .0129). Contactless automatic 3D analysis has the potential to detect restlessness mirrored by periodic leg movements during sleep reliably and may especially be suited for children and the elderly.
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Affiliation(s)
| | - Heinrich Garn
- AIT Austrian Institute of Technology GmbH, Vienna, Austria
| | - Markus Gall
- AIT Austrian Institute of Technology GmbH, Vienna, Austria
| | - Bernhard Kohn
- AIT Austrian Institute of Technology GmbH, Vienna, Austria
| | | | - Markus Waser
- AIT Austrian Institute of Technology GmbH, Vienna, Austria
| | | | | | - Marion Böck
- Medical University of Vienna, Vienna, Austria
| | | | | | - Birgit Högl
- Medical University of Innsbruck, Innsbruck, Austria
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Kurtis MM, Balestrino R, Rodriguez-Blazquez C, Forjaz MJ, Martinez-Martin P. A Review of Scales to Evaluate Sleep Disturbances in Movement Disorders. Front Neurol 2018; 9:369. [PMID: 29896152 PMCID: PMC5986889 DOI: 10.3389/fneur.2018.00369] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2018] [Accepted: 05/07/2018] [Indexed: 01/09/2023] Open
Abstract
Patients with movement disorders have a high prevalence of sleep disturbances that can be classified as (1) nocturnal sleep symptoms, such as insomnia, nocturia, restless legs syndrome (RLS), periodic limb movements (PLM), obstructive sleep apnea (OSA), and REM sleep behavior disorder; and (2) diurnal problems that include excessive daytime sleepiness (EDS) and sleep attacks. The objective of this review is to provide a practical overview of the most relevant scales that assess these disturbances to guide the choice of the most useful instrument/s depending on the line of research or clinical focus. For each scale, the reader will find a brief description of practicalities and psychometric properties, use in movement disorder cohorts and analyzed strengths and limitations. To assess insomnia, the Pittsburgh Sleep Quality Index, a generic scale, and three disease-specific scales: the Parkinson Disease Sleep Scale (PDSS), the PDSS-2, and Scales for outcomes in Parkinson's disease (PD)-Sleep-Nocturnal Sleep subscale are discussed. To evaluate nocturia, there are no specific tools, but some extensively validated generic urinary symptom scales (the Overall Bladder Questionnaire and the Overactive Bladder Symptom Score) and some PD-specific scales that include a nocturia item are available. To measure RLS severity, there are currently four domain-specific generic scales: The International Restless Legs Scale, the Johns Hopkins Restless Legs Severity Scale, the Restless Legs Syndrome-6 measure, a Pediatric RLS Severity Scale, and the Augmentation Severity Rating Scale (a scale to evaluate augmentation under treatment) and several instruments that assess impact on quality of sleep and health-related quality of life. To evaluate the presence of PLM, no clinical scales have been developed to date. As far as OSA, commonly used instruments such as the Sleep Apnea Scale of the Sleep Disorders Questionnaire, the STOP-Bang questionnaire, and the Berlin Questionnaire are reviewed. Three scales have been extensively used to assess EDS: the generic Epworth Sleepiness Scale, the Stanford Sleepiness Scale, and the PD-specific Scales for outcomes in PD-Sleep-Daytime sleepiness subscale. To date, only the Inappropriate Sleep Composite Score specifically evaluates propensity to sleep attacks.
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Affiliation(s)
- Mónica M. Kurtis
- Movement Disorders Unit, Neurology Department, Hospital Ruber Internacional, Madrid, Spain
| | - Roberta Balestrino
- Department of Neuroscience Rita Levi Montalcini, University of Turin, Turin, Italy
| | - Carmen Rodriguez-Blazquez
- National Center of Epidemiology and Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Institute of Health Carlos III, Madrid, Spain
| | - Maria João Forjaz
- National School of Public Health and Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Institute of Health Carlos III, Madrid, Spain
| | - Pablo Martinez-Martin
- National Center of Epidemiology and Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Institute of Health Carlos III, Madrid, Spain
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