text:
// --------------------------------------------------------------------------------------------------------------------
// <copyright file="RectangleAnnotationExamples.cs" company="OxyPlot">
//   Copyright (c) 2014 OxyPlot contributors
// </copyright>
// --------------------------------------------------------------------------------------------------------------------

namespace ExampleLibrary
{
    using OxyPlot;
    using OxyPlot.Annotations;
    using OxyPlot.Axes;
    using OxyPlot.Series;

    [Examples("RectangleAnnotation"), Tags("Annotations")]
    public static class RectangleAnnotationExamples
    {
        [Example("RectangleAnnotation")]
        public static PlotModel RectangleAnnotation()
        {
            var model = new PlotModel { Title = "RectangleAnnotation" };
            model.Axes.Add(new LinearAxis { Position = AxisPosition.Bottom });
            model.Axes.Add(new LinearAxis { Position = AxisPosition.Left });
            model.Annotations.Add(new RectangleAnnotation { MinimumX = 20, MaximumX = 70, MinimumY = 10, MaximumY = 40, TextRotation = 10, Text = "RectangleAnnotation", Fill = OxyColor.FromAColor(99, OxyColors.Blue), Stroke = OxyColors.Black, StrokeThickness = 2 });
            return model;
        }

        [Example("RectangleAnnotations - vertical limit")]
        public static PlotModel RectangleAnnotationVerticalLimit()
        {
            var model = new PlotModel { Title = "RectangleAnnotations - vertical limit" };
            model.Axes.Add(new LinearAxis { Position = AxisPosition.Bottom });
            model.Axes.Add(new LinearAxis { Position = AxisPosition.Left });
            model.Annotations.Add(new RectangleAnnotation { MaximumY = 89.5, Text = "Valid area", Fill = OxyColor.FromAColor(99, OxyColors.Black) });
            return model;
        }

        [Example("RectangleAnnotation - horizontal bands")]
        public static PlotModel RectangleAnnotationHorizontals()
        {
            var model = new PlotModel { Title = "RectangleAnnotation - horizontal bands" };
            model.Axes.Add(new LinearAxis { Position = AxisPosition.Bottom, Minimum = 0, Maximum = 10 });
            model.Axes.Add(new LinearAxis { Position = AxisPosition.Left, Minimum = 87, Maximum = 97, MajorStep = 1, MinorStep = 1 });
            model.Annotations.Add(new RectangleAnnotation { MinimumY = 89.5, MaximumY = 90.8, Text = "Invalid", Fill = OxyColor.FromAColor(99, OxyColors.Red) });
            model.Annotations.Add(new RectangleAnnotation { MinimumY = 90.8, MaximumY = 92.1, Fill = OxyColor.FromAColor(99, OxyColors.Orange) });
            model.Annotations.Add(new RectangleAnnotation { MinimumY = 92.1, MaximumY = 94.6, Fill = OxyColor.FromAColor(99, OxyColors.Yellow) });
            model.Annotations.Add(new RectangleAnnotation { MinimumY = 94.6, MaximumY = 96, Text = "Ok", Fill = OxyColor.FromAColor(99, OxyColors.Green) });
            LineSeries series1;
            model.Series.Add(series1 = new LineSeries { Color = OxyColors.Black, StrokeThickness = 6.0, LineJoin = OxyPenLineJoin.Round });
            series1.Points.Add(new DataPoint(0.5, 90.7));
            series1.Points.Add(new DataPoint(1.5, 91.2));
            series1.Points.Add(new DataPoint(2.5, 91));
            series1.Points.Add(new DataPoint(3.5, 89.5));
            series1.Points.Add(new DataPoint(4.5, 92.5));
            series1.Points.Add(new DataPoint(5.5, 93.1));
            series1.Points.Add(new DataPoint(6.5, 94.5));
            series1.Points.Add(new DataPoint(7.5, 95.5));
            series1.Points.Add(new DataPoint(8.5, 95.7));
            series1.Points.Add(new DataPoint(9.5, 96.0));
            return model;
        }

        [Example("RectangleAnnotation - vertical bands")]
        public static PlotModel RectangleAnnotationVerticals()
        {
            var model = new PlotModel { Title = "RectangleAnnotation - vertical bands" };
            model.Axes.Add(new LinearAxis { Position = AxisPosition.Bottom, Minimum = 0, Maximum = 10 });
            model.Axes.Add(new LinearAxis { Position = AxisPosition.Left, Minimum = 87, Maximum = 97, MajorStep = 1, MinorStep = 1 });
            model.Annotations.Add(new RectangleAnnotation { MinimumX = 2.5, MaximumX = 2.8, TextRotation = 90, Text = "Red", Fill = OxyColor.FromAColor(99, OxyColors.Red) });
            model.Annotations.Add(new RectangleAnnotation { MinimumX = 2.8, MaximumX = 6.1, TextRotation = 90, Text = "Orange", Fill = OxyColor.FromAColor(99, OxyColors.Orange) });
            model.Annotations.Add(new RectangleAnnotation { MinimumX = 6.1, MaximumX = 7.6, TextRotation = 90, Text = "Yellow", Fill = OxyColor.FromAColor(99, OxyColors.Yellow) });
            model.Annotations.Add(new RectangleAnnotation { MinimumX = 7.6, MaximumX = 9.7, TextRotation = 270, Text = "Green", Fill = OxyColor.FromAColor(99, OxyColors.Green) });
            LineSeries series1;
            model.Series.Add(series1 = new LineSeries { Color = OxyColors.Black, StrokeThickness = 6.0, LineJoin = OxyPenLineJoin.Round });
            series1.Points.Add(new DataPoint(0.5, 90.7));
            series1.Points.Add(new DataPoint(1.5, 91.2));
            series1.Points.Add(new DataPoint(2.5, 91));
            series1.Points.Add(new DataPoint(3.5, 89.5));
            series1.Points.Add(new DataPoint(4.5, 92.5));
            series1.Points.Add(new DataPoint(5.5, 93.1));
            series1.Points.Add(new DataPoint(6.5, 94.5));
            series1.Points.Add(new DataPoint(7.5, 95.5));
            series1.Points.Add(new DataPoint(8.5, 95.7));
            series1.Points.Add(new DataPoint(9.5, 96.0));
            return model;
        }
    }
}


text:
Qatar- Sidra opens Paediatric Rehabilitation clinic| MENAFN.COM
Qatar- Sidra opens Paediatric Rehabilitation clinic
(MENAFN- The Peninsula) The Peninsula
Sidra Medicine, a member of the Qatar Foundation and Qatar's new hospital for children, young people, and women, is marking International Day of Persons with Disabilities (IDPD) today by announcing the launch of its Paediatric Rehabilitation Medicine clinic.
Dr Lisa Thornton (pictured) — the former University of Chicago, Director for Paediatric Rehabilitation — has been appointed as the Division Chief of Paediatric Rehabilitation Medicine.
The clinic helps manage the health of children with physical disabilities such as paralysis, cerebral palsy and brain damage. Patients are currently referred internally from Sidra Medicine's own in-house teams, as well as Hamad Medical Corporation (HMC) and Primary Health Care Corporation (PHCC). The service will be expanded to accept referrals from doctors who practice outside of these institutions in 2018. The clinic expects to see more than 1,000 patients in its first year.
The clinic's focus will be on a multidisciplinary, community-based approach - working with young patients and their families under the leadership of Dr Thornton, who has over 20 years of experience in the field. The IDPD's theme this year 'transformation towards sustainable and resilient society for all,' also aligns with Dr Thornton's philosophy of strengthening the support network around a child and helping parents throughout the journey by empowering them with knowledge and guidance.
'During my research before moving to Qatar, I found a series of favourable articles on Qatar supporting children with disabilities and the commitment made by H H Sheikha Mozah bint Nasser, to improving the lives of these children. I was grateful to see the kind of openness that Qatar has to this population and saw a chance to be part of its efforts. I feel privileged to be part of Qatar's strategy to help children with special needs get to adulthood with dignity and with family and community support. Sidra Medicine is most definitely a beacon of learning and discovery and I am delighted to be part of it and to join a diverse and dedicated team of specialists who are all committed to ensuring improved outcomes for patients and families alike, said Dr Thornton.
The Rehabilitation Clinic ensures the patient is seen by Dr Thornton together with a physical therapist and an occupational therapist. Combining the collective expertise of a child's rehabilitation team allows for the development of a more tailored, holistic approach for every child. As part of this wide-ranging spectrum of care and support, the family will also receive a personalised plan on what to expect regarding the impact their child's disability will have on their lives, and receive guidance on the best ways to help their child reach their full potential.
Speaking about the clinic's broader, long-term vision for creating a community-based ecosystem, Dr Thornton emphasised that a child with a disability is just as healthy and capable as those without physical disabilities and should be encouraged to pursue any interest, be it sports, music or travel. 'There are already a number of programs and activities in Qatar designed to enable participation for children with physical disabilities. More collaboration between the various program owners and healthcare entitities will help create a supportive and extensive community, said Dr Thornton.
Why Has The West Given Billions In Military Aid To Ukraine, But Virtua...
Ukrainian Servicemen Arrive In Britain For Training On Challenger 2 Ta...

redpajama_set_name: RedPajamaCommonCrawl


Declines in productivity have been implicated in population declines for greater sage-grouse (Centrocercus urophasianus) in several areas, but there is considerable variation in reproductive effort, reproductive success and female survival, both temporally and spatially, and more data are needed. Despite declining populations, sage grouse are still legally harvested in most of their current range, including Montana, and uncertainty about how harvest impacts sage grouse vital rates remains. The reproductive activity, survival rates, and causes of mortality of hunted and nonhunted sage grouse females were monitored year round using radio-telemetry in central Montana during 2004 and 2005. Data on nest survival and brood survival were also collected. Nest survival was greater for renests, 0.56, than for first nests, 0.32. Brood survival to 30 days posthatch was estimated as 0.79. Reproductive effort and reproductive success were higher in 2005. Female survival during the nesting season was constant, 0.94 monthly.
Female survival during July of both years was similar on both sites, 0.99 to nearly 1.00, but survival was lower during August and declined between 2004 and 2005 from 0.94 to 0.84 on the hunted site and declined from 0.98 to 0.94 on the nonhunted site. This decline in survival between years in August was likely due to West Nile virus, as it was first detected in sage grouse in this area in August 2005. Female survival during the hunting season was lower for females that spent more days brood-rearing than those that spent few or no days brood rearing, and females on the hunted site had lower survival than females on the nonhunted site. However, lower survival rates on the hunted site could not be attributed to hunter kill, because no radio-marked females were bagged or reported by hunters and no evidence of hunter kill was observed. During the hunting season, monthly survival estimates ranged from 0.87 for hunted-site females that invested heavily in brood rearing to 0.99 for nonhunted-site females that invested little or no time in brood rearing. Overwinter survival was different between years, and monthly survival during winter 2004-05 was estimated as 0.98 and as 0.97 during winter 2005-06.


Kevin Christie called the meeting to order at 7:05 PM.
Approval of Agenda: Peter Merrill asks for a report how HSD is dealing with the Government shut down. The item will be added under Items Requiring Board Action (SOS Update). Peter Merrill motions to approve the Agenda with the 1 addition. Eric Michaels seconds the motion. A unanimous verbal vote 5-0 passes the motion.
Executive Session- Personnel Matter-7:10 PM Peter Merrill motions to go into ES. Lori Dickerson seconds the motion. A unanimous verbal vote passes the motion 5-0.
Board Priorities- Action Plan Draft #2- Julia Haynes presents the second draft with revised Academic Rigor and the Graduation Project. Discussion included continued research of other Vermont schools, capstone process, updating handbooks etc. The Board directs Julia to update the document with the information discussed tonight.
The calendar discussion included switching (on the presented document) defining rationale for calendar changes with the Board defining what they want for a school calendar. The anticipated date of accomplishment for the two actions was moved from June 2014 to May 2014. A retreat for the Board was discussed, as was a survey of HSD teachers. Continued research and resources such as VSBA will continue. The Board agreed to set a retreat day after the November 13th meeting.
Facility Maintenance Plan Draft #1- Tom DeBalsi presented the itemized by school maintenance needs document. Discussion involved getting HSD on a cycle of maintenance for all buildings and grounds. The Board discussed with Mr. DeBalsi setting up "sinking"/reserve funds for specific maintenance such as paving, and roofing, flooring. After a lengthy discussion, Peter Merrill motions to direct the Superintendent to prepare a Bond package and a 5 year maintenance plan that goes into more detail than Draft #1. The package would include a 15 year regular maintenance plan with 2 year cycle reserve funds. Lori Dickerson seconds the motion. A unanimous verbal vote passes the motion 5-0 aye. (Mr. DeBalsi will check with the HSD attorney to make sure reserve funds would be available for all HSD buildings & not locked in to specific schools.) Mr. DeBalsi will put the Maintenance plan on the web site after it is revised per the Board's request.
Board member to suggest acquiring a commemorative plaque for Devoid painting. (The minutes were amended to read; Eric Michaels motions to accept the suggestion, the District acquire a plaque commemorating the contribution of Devoid Painting to hang in the HHS gym. Lori Dickerson seconds the motion. A unanimous verbal vote 5-0 passes the motion.) Lori Dickerson seconds the motion to accept the 9/28/13 minutes. A unanimous 5-0 vote passes the motion.
Mr. DeBalsi reports the Café Food Service is receiving comments the food is better. Each school is cooking (HMMS kitchen remains under construction). The District continues to have an issue with the PayPal software. Mr. DeBalsi hopes to have a more accurate report in January after all schools are up and running under the service.
An enrollment comparison is given by Mr. DeBalsi. Numbers would suggest a 45 student decrease from August 2012 to August 2013.
Mr. DeBalsi and Ms. Haynes report the Government shut down has not yet affected the school district as we have already received our funding. Should the shutdown go longer, we could be affected.
Board Meeting schedule presented. One correction March 27th not a meeting night. The Board is reminded the joint School/Town meeting is October 16th 6 PM @ the Getaway. The Board has no additions to the Agenda for the above mentioned meeting.
Adjournment- 9:02 PM Peter Merrill moves for adjournment, Lori Dickerson seconds and a unanimous verbal vote 5-0 passes the motion.


Azealia Banks has debuted a new song, 'Liquorice', online. Scroll down to listen to it.
The track sees the rapper rhyming over Lone's 2010 track 'Pineapple Crush'. The much hyped new artist posted the song on her Tumblr along with its lyrics.
Azealia Banks was among the acts named in the BBC's annual list of artists tipped to break through in the following year. She features in the BBC Sound of 2012 Longlist along with the likes of Niki & The Dove, Spector, Flux Pavillion and Jamie N Commons.
She is currently working with UK producer Paul Epworth on new material and plays alongside Two Door Cinema Club, Metronomy and Tribes on the NME Awards Tour 2012, which takes place in February.


Will Greenwald 27 Cool (and Wacky) Things We Spotted at E3 The video game industry's biggest trade show is a sight to behold. Here are some of the more interesting things we saw on the convention floor.
The video game industry's biggest trade show is a sight to behold. Here are some of the more interesting things we saw on the convention floor.
Another June means another E3, which means another week in Los Angeles seeing the biggest video game news of the year all in one place.
We hit the Los Angeles Convention Center to see the newest video games from Activision, Bethesda, Ubisoft, Microsoft, Nintendo, Sony, and other major developers and publishers. Our ongoing show coverage hits the big news stories, but that leaves plenty of spectacle to cover.
E3 is big on set pieces, with huge, complex booths filled with statues, signs, and screens. There are monuments. There are monsters. There are zombies. There are police cars. There are zombies in police cars, plural. There's plenty to see, so we put together some of the more eye-catching things we've seen at the show.
Industry and media attendees form the first wave in the hour before the show opened on Tuesday.
A Sonic the Hedgehog treadwheel between the South and West halls let Sega fans pretend to be the blue blur, while promoting the Puma/Sega collaborative Sonic and Dr. Eggman running shoes.
The PlayStation booth shows off Sony's biggest first-party-published upcoming games.
A wide swath of Sony's booth offers demos of several PlayStation VR games. The crowd is relatively thin.
A faux skyline on Sony's booth provides a look at Insomniac Games' upcoming Spider-Man game, coming out this September. The billboard indicates the Green Goblin is running for mayor.
A life-size statue of Norman Reedus' character in Hideo Kojima's upcoming game Death Stranding stands in Sony's booth. Sony showed a lengthy video of the game at its press conference, leaving us about as baffled as we were when the first trailer was released.
7 You Want To Touch?
Nintendo's booth features signature equipment from the wide roster of Super Smash Bros. Ultimate, like Bayonetta's revolvers, Love Is Blue.
This abandoned police car menaced by zombies is one of two zombie/police car combinations on the show floor. This one is for Overkill's The Walking Dead.
DisplayLink's booth shows off the HTC Vive Wireless Adaptor and Vive Pro, letting visitors try Serious Sam VR: The Last Hope with a custom gatling gun controller.
Shacknews' Alex Morrison has some amazing hair. This doesn't have anything to do with video games. I just saw him on the show floor and was impressed.
A duck in a chef's hat offers cakes to gamers walking between the halls. In unrelated news, 2018 marks the year California's recreational marijuana legalization fully comes into effect.
Andrew W.K. stands before the South Hall as photographers capture his awe at the show. His music is featured in Bethesda's upcoming Rage 2.
Ubisoft's Starlink: Battle For Atlas brings the toys-to-life concept to space exploration. The collectible ships in the game include the Arwing fighter from Nintendo's Star Fox.
This Raccoon City P.D. police car is the second zombie/cruiser combination on the show floor. This promotes the Resident Evil 2 remake, set to come out in January.
Capcom's booth features a haunted house maze based on the Raccoon City Police Department in Resident Evil 2, with actors dressed like zombies jumping out at visitors.
Thanks to its battle royale mode, Fortnite is one of the biggest online games right now. So of course there was an elaborate Fortnite booth, with battle bus.
Epic's Fortnite booth features a pinata-themed mechanical bull. Mechanical bulls are oddly popular at gaming cons and expos. I never quite figured out why.
The National Videogame Museum booth shows relics from ancient console generations.
Rage 2 and Fallout 76 are the centerpieces of Bethesda's booth. The Rage 2 part of the booth features a decorated truck and strength tester.
Mega Man 11 is one of the pillars of Capcom's E3 booth, with an elaborate set for taking photos. Around the corner, a Mega Man-themed wall shows the series' history against kiosks with the Mega Man and Mega Man X Legacy Collections.
A Jurassic World gate leads visitors to demos of Jurassic World: Evolution, a park management sim. It is unrelated to DinoPark Tycoon, another dinosaur-themed park management sim that is 25 years old, released between Jurassic Park and Jurassic Park 2: The Lost World. Dinosaurs were big in the early 90s.
A hulking demon towers over the Los Angeles Convention Center lobby, showing off From Software's Sekiro: Shadows Die Twice. Man on left for scale.
23 Robot Drill Arms Aren't the Highlight?
A display for Tom Clancy's The Division 2 in the Los Angeles Convention Center lobby is carved in real time with the randomly selected names of beta users signing up for the game, by robot arms with drilling and cutting attachments.
Artists Humberto Ramos and Francisco Herrera hand-paint a Volkswagen Jetta with Captain Marvel art. It isn't immediately clear if this is meant to promote Volkswagen, Marvel Comics, or art for art's sake.
Outside the convention, a bear dances to get people to buy PlayStation merchandise.
Actors dressed as the characters from Code: Vein and Soul Calibur 6 pose at Bandai Namco's booth. Siegfried's hair is particularly lustrous.
Microsoft's Mixer booth features a MacLaren supercar, to promote Forza Horizon 4.


text:
"Oscar Viewing Party" By Sandy Zimmerman
March 18, 2020 Sandy Zimmerman ENTERTAINMENT, Local News 0
You never know who will be walking the Academy Award's Red Carpet, Hollywood film stars, the stars of Las Vegas' shows, VIP'S, and the public can also join the Red Carpet Experience. The Academy Awards honor the great talent involved in all of the areas of producing these films, it's a very special time that everyone can enjoy. The annual Variety Salutes Hollywood Oscar viewing party is held at the Brenden Theater, at the Palms Hotel/Casino.
I feel it's always interesting to interview the entertainers along the red carpet.
Darrin Race, a magician/illusionist, and he builds his own props! If Darrin thinks of a new magical concept, he puts it together, tests and modifies "His way."
Darrin Race explained, "I'm proud to go around with Lance Burton and perform my magic show for Variety, the Children's Charity. My favorite illusion is levitation, having a girl appear out of an empty box."
Darrin's long-time dream is to have a magic and movie exhibit with authentic, recreation props, wardrobe, and scenes from famous movies past and present. It will also house some of the finest magic props and costumes ever made, some used by famous magicians from the past.
The exhibit and showroom for live magic and Elvis shows, a magic / gift shop, a Hollywood themed Miniature Golf course, a 1950s style diner, and for fine dining, a steak house named after Hollywood's original Brown Derby. Darrin, he has recently acquired numerous autographs including those of Steven Spielberg, Charles Bronson and Tony Curtis include Ghost Ship, The Last Samurai, and Richard Dreyfus' outfit from "Poseidon". A target date to open is the near future.
That sounds like an exhibit everyone would like to see! I have been reviewing celebrities since the 1985 and always enjoy something new.
Variety – The Children's Charity participates by raising funds at the Academy Awards. Variety — The Children's Charity is an enthusiastic group of business leaders who donate their time, resources and energy to positively impact the lives of children in their own communities and around the world.
All of the donations to the Academy Awards were for Variety—The Children's Charity, an enthusiastic group of business leaders who donate their time, resources and energy to positively impact the lives of children in their own communities and around the world. VARIETY Southern Nevada has served more than 20,000 children and raised and distributed more than $7,000,000 in grants and specialized equipment in our community. If you would like to get involved or for information about Variety The Children's Charity events during the year, contact Variety of Southern Nevada, at 3401 Sirius Ave., Suite 1, Las Vegas. Tel: (702)383-8466; Email: http://onalv.org/ andwww.varietysn.org
Award winning Sandy Zimmerman is a syndicated columnist featuring Show and Dining reviews, travel, health, spas, luxury and more. Sandy is talk show host of Sandy Zimmerman's Las Vegas TV television programs and Discover the Ultimate Vacation travel television specials. Sggest topics for articles, or to ask any questions, call 702-515-0846 or sandyzimm2003@yahoo.com.
They don't want to build their own newspaper, they want to take mine
Mosaic Theater Opens with Aussie Heat By Sandy Zimmerman


One thing that people like to be able to do for themselves and make sure that they are so you are that's Tulsa fire damage restoration was be able to call especially knowing they are EPA certified firm that they have been told to the clean trust certified. These things and many small be able to help you understand that we able to not only help you write your now, but also as we look to the future different ways we might be able in a more applicable fashion.
To make sure that these things are doing it that much more better we want to be able to get all the different possibilities right here might now to the amazing way that will look to all of things to come. Many people think of these things as something that is so uncertain that people be only able to see them and many different aspects as unhelpful. We're going to make sure that these things are so off of the many people cannot even have all the things that would like to be able to do the first place.
One thing that we would like to be able to make sure Tulsa fire damage restoration is that we're giving you all the different opportunities to be able to make sure that the things you're right. What this means is that through everything that we're doing were giving people such an attitude of greatness that many people cannot even more about themselves and in many cases are being done so with amazing customer service. Whenever they realize that there actually is customer service they would like to be able to understand all these things for themselves in a much better fashion.
We able to make sure that your life is going in a Tulsa fire damage restoration will be able to do this is to the many different services and additives that we do have to be able to make your life better. What this means is that we're going to be able to give you all the different ways such as with fire and ash making sure that the debris is gone and taking care of, all the way to making sure that if storms come your way and something happens that we were able to not only blow over everything that has this happen but also make sure that is put back in the proper way.
More questions about this and anything that you like to be able to ask us about you can definitely do so at the phone number which is going to be (918) 779-4900 in which you can get immediate response especially if you something is currently right now. Or you can also go to our website which is going to be 247disastergroup.com we hope to hear from you soon. And to be one possibilities what they want to make sure is that everything we're doing is done in such a way with excellence and that the standpoint of helping you understand the different possibilities that we are able to bring with you especially never going to a very hard time.
Many people find it very hard to be able to a call but all the things that they would like to in life especially whenever you're trying to fix problems that happen in the past. Whenever these things happens and you have had a great disaster we want to be able to make sure that we able to help you at Tulsa fire damage restoration because we understand that going to such a hard time and can actually be very hurtful to every other aspect of your own personal life.
We want to make sure that this is happening in such a way that using all of the benefits to your own ability and to be able to make sure that this is happening at a wonderful a great many people cannot even my run the first places something that we would love to be able to help show you the ways in which we actually do things here. If we able to do so with Tulsa fire damage restoration we would love to be able to show these things and many more as a kid I give you an amazing way to be able to do all the things that you love to do instead of focusing on the negative which is actually not can be very beneficial at all.
Giving all these opportunities as is a one side the coin and the other said the coin is making sure that we hold to our word. What in the world your word we're showing a great customer service and to be able to make sure that we fulfill his promises were actually in adult things that we say that we were because we understand that having the same problems as something that is going to actually show us whether or not we're doing my job properly this is some of that we would like to be able to see from a critical sampling because we understand that it is very vital to understand all these things right here and right now.
To make sure that all these things are going correctly we want to also give you certain ideas that we have about the future. These ideas can major many differences and to be able to actually make them and get them on paper is a man many people think that is not possible. And the reason why is because of these things are revolutionary not only now, but will be from time to time because the day it utilize different ideas that have not become mainstream.
To to be able to help you at Tulsa fire damage restoration one thing that we would like to be able to show you an image in your own lives is how we can be able to give you direct access to us storefront and that is going to be at (918) 779-4900. If you have an immediate emergency would love to be able to get in contact was or you could even go to 247disastergroup.com or going to be able to give you that same information and help you understand all the better what things we actually do here.


text:
Detection of obstructive sleep apnea using Belun Sleep Platform wearable with neural network-based algorithm and its combined use with STOP-Bang questionnaire
Eric Yeh,
Roles Data curation, Investigation, Methodology, Visualization, Writing – original draft
Affiliation Division of Pulmonary, Critical Care, and Sleep Medicine, University Hospitals Cleveland Medical Center and Department of Medicine, Case Western Reserve University, Cleveland, Ohio, United States of America
Eileen Wong,
Roles Data curation, Investigation, Methodology, Project administration, Visualization, Writing – review & editing
Chih-Wei Tsai,
Roles Formal analysis, Writing – original draft, Writing – review & editing
Affiliation Belun Technology Company Limited, Sha Tin, Hong Kong
Wenbo Gu,
Roles Conceptualization, Software, Writing – review & editing
Affiliations Belun Technology Company Limited, Sha Tin, Hong Kong, Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
Pai-Lien Chen,
Affiliation FHI360, Durham, NC, United States of America
Lydia Leung,
Roles Conceptualization, Writing – original draft, Writing – review & editing
I-Chen Wu,
Affiliation Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
Kingman P. Strohl,
Roles Conceptualization, Writing – review & editing
Affiliations Division of Pulmonary, Critical Care, and Sleep Medicine, University Hospitals Cleveland Medical Center and Department of Medicine, Case Western Reserve University, Cleveland, Ohio, United States of America, Division of Sleep Medicine, Louis Stokes Cleveland VA Medical Center, Cleveland, Ohio, United States of America
Rodney J. Folz,
Wail Yar,
Roles Data curation, Investigation, Methodology, Writing – review & editing
Affiliation Department of Family Medicine, University Hospitals Cleveland Medical Center, Cleveland, Ohio United States of America
Ambrose A. Chiang
Roles Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing – original draft, Writing – review & editing
* E-mail: Ambrose.chiang@va.gov, ambrose.chiang@uhhospitals.org
Wail Yar
Eric Yeh Eileen Wong ... Ambrose A. Chiang
Many wearables allow physiological data acquisition in sleep and enable clinicians to assess sleep outside of sleep labs. Belun Sleep Platform (BSP) is a novel neural network-based home sleep apnea testing system utilizing a wearable ring device to detect obstructive sleep apnea (OSA). The objective of the study is to assess the performance of BSP for the evaluation of OSA. Subjects who take heart rate-affecting medications and those with non-arrhythmic comorbidities were included in this cohort. Polysomnography (PSG) studies were performed simultaneously with the Belun Ring in individuals who were referred to the sleep lab for an overnight sleep study. The sleep studies were manually scored using the American Academy of Sleep Medicine Scoring Manual (version 2.4) with 4% desaturation hypopnea criteria. A total of 78 subjects were recruited. Of these, 45% had AHI < 5; 18% had AHI 5–15; 19% had AHI 15–30; 18% had AHI ≥ 30. The Belun apnea-hypopnea index (bAHI) correlated well with the PSG-AHI (r = 0.888, P < 0.001). The Belun total sleep time (bTST) and PSG-TST had a high correlation coefficient (r = 0.967, P < 0.001). The accuracy, sensitivity, specificity in categorizing AHI ≥ 15 were 0.808 [95% CI, 0.703–0.888], 0.931 [95% CI, 0.772–0.992], and 0.735 [95% CI, 0.589–0.850], respectively. The use of beta-blocker/calcium-receptor antagonist and the presence of comorbidities did not negatively affect the sensitivity and specificity of BSP in predicting OSA. A diagnostic algorithm combining STOP-Bang cutoff of 5 and bAHI cutoff of 15 events/h demonstrated an accuracy, sensitivity, specificity of 0.938 [95% CI, 0.828–0.987], 0.944 [95% CI, 0.727–0.999], and 0.933 [95% CI, 0.779–0.992], respectively, for the diagnosis of moderate to severe OSA. BSP is a promising testing tool for OSA assessment and can potentially be incorporated into clinical practices for the identification of OSA.
Trial registration: ClinicalTrial.org NCT03997916 https://clinicaltrials.gov/ct2/show/NCT03997916?term=belun+ring&draw=2&rank=1
Citation: Yeh E, Wong E, Tsai C-W, Gu W, Chen P-L, Leung L, et al. (2021) Detection of obstructive sleep apnea using Belun Sleep Platform wearable with neural network-based algorithm and its combined use with STOP-Bang questionnaire. PLoS ONE 16(10): e0258040. https://doi.org/10.1371/journal.pone.0258040
Editor: Heming Wang, Brigham and Women's Hospital and Harvard Medical School, UNITED STATES
Received: April 27, 2021; Accepted: September 16, 2021; Published: October 11, 2021
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: This clinical research was supported by grant BL2018/1001 from the Belun Technology Company Limited, Hong Kong. https://urldefense.com/ https://beluntech.com. The Belun Sleep platform devices used in this study were provided by the company. Belun Technology agreed with the design of the study and had no role in the data collection. The sponsor did contribute to the data analysis, decision to publish, and manuscript preparation. The funder, Belun Technology Company, provided support in the form of salaries for authors C. W. Tsai, W. Gu, and L. Leung, but did not have any additional role other than described above. The specific roles of these authors are articulated in the Author Contributions section. This commercial affiliation does not alter our adherence to PLOS ONE policies on sharing data and material.
Competing interests: A. A. C. received grant BL2018/1001 from Belun Technology for conducting this study at University Hospitals Cleveland Medical Center but otherwise has no financial conflicts of interest. I. W. is a professor in Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan, and has received research funding from Belun Technology. W. G. is a PhD student at the Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan, and is also an engineer of Belun Technology. L. L. and C. T. are Belun Technology Company employees. E. Y., E. W., W. Y., K. P. S., R. J. F., and P. C. have no financial conflicts of interest for the submitted work.
Obstructive Sleep Apnea (OSA) is a challenging sleep disorder associated with increased cardiovascular and metabolic morbidities as well as increased mortality [1–7]. In the general adult population, the prevalence of OSA defined by apnea-hypopnea index (AHI) ≥ 5 events/h ranges from 9% to 38% and the prevalence is likely to further increase due to both the obesity epidemic and aging of society [8–10].
The current gold standard for the diagnosis of OSA requires overnight multi-channel polysomnography (PSG) in the sleep lab. Type 3 home sleep apnea testing (HSAT) devices are now widely used despite concerns of false negative results [11–14]. Technologies that analyze peripheral arterial tone (PAT) signal are considered acceptable alternatives [15, 16]. In the recent Peripheal Arterial Tonometry Evaluation of Reliability (PATER) study, Ioachimescu et al. conducted a large cohort comparing WatchPAT with synchronous PSG in 500 consecutive veterans [17]. Using a 3% desaturation threshold, the WatchPAT-200 automated algorithm overestimated severity by an average of +4 events/h, and the 4% threshold underestimated severity by −6 events/h. Diagnostic concordance was found in 42%, 41%, and 83% of mild, moderate, and severe OSA. These authors recommended that those with no OSA or mild OSA, assessed by WatchPAT, undergo in-lab PSG testing.
Wearable devices now exert a significant impact in medicine and healthcare [18, 19]. Many wearables allow physiological data acquisition in sleep and enable clinicians to assess sleep outside of sleep labs [20–28]. The recent advances of wearable technology arise largely from the miniaturization of biosensors, low-power computation, and the application of artificial intelligence, particularly machine learning [29, 30]. The Belun Sleep Platform (BSP, Belun Technology Company Limited, Hong Kong) consists of a patented wearable ring device, a charging cradle, and cloud-based software. The Belun Ring, an FDA-cleared pulse oximeter, acquires pulse oximetry, photoplethysmography (PPG), and 3-axis accelerometer signals from the radialis indicis artery of the proximal index finger. The BSP proprietary OSA detection algorithm was built using neural networks and trained with a dataset of 5,783 patients and 8,417 records of overnight sleep studies scored with the 4% oxygen desaturation hypopnea criteria [31]. Two fully connected neural networks for respiratory event detection and total sleep time estimation were trained respectively to learn features and patterns from SpO2, pulse rate, heart rate variability (HRV), accelerometry signal, and PPG waveform to detect respiratory events and total sleep time by 5-minute segments. Features were extracted from overnight data, current segment, and consecutive prior segments. Both the respiratory event detection model and total sleep time estimation model have three fully connected hidden layers. The respiratory event detection model contains 160, 80, and 20 neurons in each layer while the total sleep time estimation model contains 160, 80, and 5 neurons (Fig 1). The activation functions used in both models are the sigmoid function. The outputs of the respiratory event detection model are the predicted number of respiratory events in each segment.
Fig 1. BSP neural network architecture diagram.
The BSP proprietary OSA detection algorithm was built using neural networks and trained with a dataset of 5,783 patients and 8,417 records of overnight sleep studies. (A) Respiratory event detection model containing 160, 80, and 20 neurons; (B) Total sleep time estimation model containing 160, 80, and 5 neurons.
A recent proof-of-concept study in adult subjects not taking heart-rate affecting medications and having no significant comorbidities showed a good correlation between the Belun apnea-hypopnea index (bAHI) and the PSG-AHI as well as good sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) in categorizing AHI ≥ 15 events/h. The Belun total sleep time (bTST) also correlated well with the PSG-TST [32].
In this current study, we hypothesized that BSP can reliably identify moderate to severe OSA in a sleep lab patient population including those who take heart rate-affecting medications and have non-arrhythmic comorbidities. We specifically studied the accuracy of bAHI and bTST by comparing them directly to concurrent in-lab PSG-AHI and PSG-TST. We also investigated the performance of a diagnostic algorithm incorporating STOP-Bang to predict moderate to severe OSA. STOP-Bang was selected in this study over Berlin Questionnaire (BQ) and Epworth Sleepiness Score (ESS) as studies have shown that STOP-Bang is more accurate than ESS and BQ in predicting OSA of various severity as ESS only assesses sleepiness and BQ focuses primarily on OSA-related symptoms as opposed to STOP-Bang questionnaire, which includes demographic and anthropometric characteristics such as BMI, age, neck circumference, and gender [33–35]. We hypothesized that the addition of STOP-Bang may improve the diagnostic precision as well as the categorization of OSA severity.
A total of 336 consecutive subjects who were referred to the American Academy of Sleep Medicine (AASM)-accredited University Hospitals Cleveland Medical Center labs (Beachwood and Cleveland, Ohio) for evaluation of sleep disorders were screened; 206 adult subjects met the eligibility criteria; 113 signed informed consent and participated in the study. Seventy-eight subjects who passed the 2-step ring size optimization protocol and had a recording time ≥ 4 hours were enrolled (Fig 2) [32]. Patients who were on heart-rate altering medications such as beta-blockers and/or calcium channel antagonists were included in this study. All underwent BSP testing with simultaneous overnight PSG.
Fig 2. CONSORT flow diagram.
The inclusion criteria were adults age 18–80 with a valid email address who are willing to provide written informed consent and complete STOP-Bang questionnaire. The exclusion criteria included subjects who were referred for positive airway pressure titration study; those with atrial fibrillation, pacemaker, defibrillator, left ventricular assist device, or status post-cardiac transplantation; patients on home O2, non-invasive ventilator, diaphragmatic pacing, or any form of nerve stimulator; patients with hospitalization in the prior 30 days or unstable cardiopulmonary status judged to be unsafe for a sleep study by the sleep tech or the on-call sleep physician on the night of the study; those with heart rate outside the 50–100 per minute range at the time of testing, and those unable to complete the required study. Patients with atrial fibrillation were excluded from this study as the BSP analysis algorithm has not been tested in this specific population.
BSP algorithm and data collection
In this study, the neural network algorithm used in the BSP is the same as that used in the proof-of-concept study [32]. The BSP ring captures oxygen saturation (SpO2), photoplethysmography (PPG), and accelerometer signals. The bTST is derived from features extracted from accelerometer, SpO2, and PPG signals. The bAHI is derived from bTST and features extracted from heart rate variability and SpO2 changes [32].
STOP-Bang data were collected on the night of the sleep study. There are seven different ring sizes (sizes 5, 7, 9, 10, 11, 13, and 15) available. A 2-step ring selection approach was used to ensure the appropriate ring size as described in the proof-of-concept study [32]. Once the ring selection is optimized, the ring is securely placed on the proximal phalanx of the non-dominant hand index finger and left in place overnight. At the conclusion of the sleep study, the ring is removed and placed back on the cradle connected to a PC laptop using a USB cable. The acquired data are then uploaded to the cloud via the internet and the neural network algorithm automatically calculates and generates a report that can be downloaded immediately. To assess the accuracy of bTST, sleep stages in 30-second epochs from PSG were extracted according to the valid sleep period of BSP for comparison with the PSG-TST. The bAHI is defined as the number of respiratory events estimated by the BSP algorithm divided by the bTST. The PSG scoring technicians and the interpreting physician (AAC) were blinded to the BSP results.
Polysomnography scoring and statistical analysis
Attended in-lab PSG (SleepWorks, Natus, Pleasanton, CA) was performed in all patients in a standard fashion. The PSG montage includes EEG leads (O1M2, O2M1, C1M2, C2M1, F1M2, F2M1), right electrooculogram, left electrooculogram, chin electromyogram, nasal pressure airflow, thermistor airflow, chest and abdominal respiratory efforts, pulse oximetry, left leg electromyogram, right leg electromyogram, and electrocardiogram. CPAP flow was also monitored for split night studies. All studies were manually scored in 30-sec epochs according to the AASM Scoring Manual, version 2.4 [36, 37]. An obstructive apnea event is defined as a decrease in the thermistor airflow to < 10% of the baseline for ≥ 10 seconds with continued respiratory effort. A hypopnea event is defined as a decrease in nasal pressure signal excursions by 30% to 90% of the baseline for ≥ 10 seconds accompanied by oxygen desaturation ≥ 4%. The Belun Technology Company staff were blinded to the in-lab PSG results.
Statistical analysis was performed using R (R Core Team) to assess the accuracy of BSP in predicting OSA [38]. We used the Kruskal-Wallis test by ranks to compare the medians of age, body mass index (BMI), AHI, central apnea index (CAI), and STOP-Bang score among OSA severities as these data are not normally distributed. Mantel-Haenszel Chi-Squared test was used to compare frequencies in gender, and race among OSA severities [39]. Agreements between results derived from PSG-AHI versus bAHI and PSG-TST versus bTST were determined by Pearson's correlation and Bland-Altman method [40]. Statistical measures including accuracy, sensitivity, specificity, PPV, NPV, positive likelihood ratio (LR+), negative likelihood ratio (LR-), Cohen's Kappa coefficient (Kappa), and area under the receiver operator Curve (AUCROC) were computed at PSG-AHI cutoffs of 5, 15, and 30 events/h. Fisher's exact test was used to compare sensitivity and specificity between subjects with and without heart rate-affecting medications and those with and without comorbidities. Statistical measures of diagnostic algorithms combining STOP-Bang score cutoffs of 3, 4, and 5 with a bAHI cutoff of 15 events/h were compared for accuracy in predicting moderate to severe OSA. The diagnostic algorithm yielding the best results was internally validated using bootstrapping with 1,000 samples [41].
The study protocol was approved by the University Hospitals Institutional Review Board (STUDY20181042). All ongoing and related BSP trials are registered at ClinicalTrials.org. This trial was registered after recruitment of participants began due to clerical error.
A total of 78 adult subjects were included. Baseline data including gender, race, BMI, STOP-Bang, AHI, CAI are shown in Table 1. This sampled population was unbalanced and skewed towards female subjects (65%) and those with normal and mild OSA (63%). There were 22% with STOP-Bang score < 3 and only 36% of subjects had STOP-Bang ≥ 5. Concerning comorbidities, 29% of subjects had diabetes, 58% hypertension, 49% hyperlipidemia, and 31% asthma/chronic obstructive pulmonary disease. Echocardiography report was available in 40% of subjects with 4% having systolic dysfunction and 20% having diastolic dysfunction. There were 32% taking beta-blockers and/or calcium channel antagonists.
Table 1. Summary of subject characteristics and PSG results.
Comparing BSP to PSG
The bAHI correlated well with the PSG-AHI (r = 0.888, P < 0.001; Fig 3A). The mean difference between bAHI and PSG-AHI was +4.2 events/h with a 1.96 standard deviation of 17.8 events/h (Fig 4A). The bTST is also highly correlated with PSG-TST (r = 0.967, P < 0.001; Fig 3B). The mean difference between bTST and PSG-TST was -24.8 minutes with a 1.96 SD of 30.2 minutes (Fig 4B). The receiver operator curve (ROC) was plotted at three different PSG-AHI cutoffs of 5, 15, and 30 events/h and is shown in Fig 5. The overall performance of the BSP including accuracy, sensitivity, specificity, PPV, NPV, LR+, LR-, kappa, and AUROC for AHI of 5, 15, and 30 events/h are summarized in Table 2. The optimal bAHI cutoff for prediction of moderate or severe OSA was 16 events/h with a sensitivity, specificity, PPV, and NPV of 0.929, 0.820, 0.744, and 0.954. The contingency table comparing OSA severity measured by PSG and BSP is shown in Table 3. Statistical measures for the subjects taking heart-rate affecting medications and for those with comorbidities are summarized in Table 4. Fisher's exact test indicated no significant difference in sensitivity and specificity between subjects with and without heart rate-affecting medications (P = 0.192 for sensitivity; P = 0.474 for specificity). Comorbidities also did not affect the performance of BSP testing (P = 1.000 for sensitivity; P = 0.410 for specificity).
Fig 3. Scatterplots.
(A) Scatterplot comparing bAHI to PSG-AHI; (B) Scatterplot comparing bTST to PSG-TST. bAHI = Belun apnea-hypopnea index; PSG-AHI = polysomnography apnea-hypopnea index; bTST = Belun total sleep time; PSG-TST = polysomnography total sleep time.
Fig 4. Bland-Altman plots.
(A) Bland-Altman plot for bAHI vs. PSG-AHI; (B) Bland-Altman plot for bTST vs. PSG-TST. bAHI = Belun apnea-hypopnea index; PSG-AHI = polysomnography apnea-hypopnea index; bTST = Belun total sleep time; PSG-TST = polysomnography total sleep time.
Fig 5. ROC curves for bAHI vs. PSG-AHI at PSG-AHI Cutoffs of 5, 15, and 30 events/h (N = 78).
ROC = receiver operator characteristic; bAHI = Belun apnea-hypopnea index; PSG-AHI = polysomnography apnea-hypopnea index.
Table 2. Performance (mean with 95% CI) of bAHI at PSG-AHI cutoffs of 5, 15, and 30 (all subjects, N = 78).
Table 3. Contingency table of OSA severity measured by PSG and BSP (all subjects, N = 78).
Table 4. Performance (mean with 95% CI) of bAHI at PSG-AHI cutoff of 15 for subjects taking heart-rate affecting medicines and subjects with comorbidities.
Combining STOP-Bang and bAHI
We assessed the performance of a diagnostic algorithm incorporating STOP-Bang with a bAHI cutoff of 15 events/h. We tested STOP-Bang score cutoffs of 3, 4, and 5, and a cutoff of 5 had the best performance in stratifying subjects into three categories: (1) positive for moderate or severe OSA (STOP-Bang ≥ 5 with bAHI ≥ 15 events/h); (2) negative for moderate or severe OSA (STOP-Bang < 5 with bAHI < 15 events/h); and (3) indeterminate (STOP-Bang < 5 with bAHI ≥ 15 events/h, or STOP-Bang ≥ 5 with bAHI < 15 events/h). With this combined diagnostic algorithm, 61% of the subjects need no further sleep testing (Fig 6). Compared to the STOP-Bang cutoff of 5 alone (Table 5), this diagnostic algorithm using STOP-Bang cutoff of 5 and bAHI cutoff of 15 events/h yielded better performance in assessing moderate to severe OSA (original dataset, Table 6). Internal validation of the diagnostic algorithm was performed by bootstrapping with 1,000 samples which showed small 95% bootstrapped confidence intervals around the original coefficients (bootstrapping re-sampling, Table 6).
Fig 6. The combined diagnostic algorithm using STOP-Bang cutoff of 5 and bAHI cutoff of 15 events/h curtailed the need for further sleep testing by 61%.
bAHI = Belun apnea-hypopnea index. a This false negative case had a PSG-AHI of 17.6 events/h; b These two false positive cases had mild OSA with PSG-AHI ≥ 5 events/h.
Table 5. Performance (mean with 95% CI) of STOP-Bang score of 5 at PSG-AHI cutoffs of 5, 15, and 30 (N = 78).
Table 6. Performance (mean with 95% CI) of the combined approach using STOP-Bang cutoff of 5 and bAHI cutoff of 15 (N = 48).
This study assessed the performance of BSP in detecting OSA in adult patients referred to sleep labs for in-lab PSG. Unlike the proof-of-concept study, this cohort included patients taking medications known to affect heart rate and those with non-arrhythmic comorbidities. The bAHI and bTST derived from BSP correlated well with PSG-AHI and PSG-TST with a correlation coefficient of 0.888 and 0.967, respectively. The use of heart rate-affecting medications did not negatively influence the performance of BSP testing. Despite the presence of a relatively low overall OSA prevalence and an unusually high female-male ratio uncharacteristic for an in-lab study population, the performance of BSP remains reasonably robust.
This study again demonstrated that although BSP has a good overall performance, diagnostic discordance exists. BSP tends to overestimate AHI in individuals with AHI under 15 events/h and underestimate AHI in those with an AHI over 15 events/h [32]. Similar diagnostic discordances between PSG-AHI and HSAT respiratory event index have been described in other PAT/PPG-based devices including WatchPAT and NightOwl [16, 32, 42–44]. This overestimation of AHI in the low AHI range is likely due to the identification of RERAs and autonomic arousals from other causes by the BSP algorithm. On the other hand, the underestimation at high AHI range may be due to misses of the respiratory events when consecutive respiratory events occur over a short period, or this may be attributable to the rejection of motion artifact-related poor PPG signals in patients with very severe OSA. Overall, BSP demonstrated satisfactory performance in detecting moderate or severe OSA despite the presence of severity discordance, which is more prominent in patients with no OSA or mild OSA.
Compared to other PAT/PPG-based devices
Several studies have investigated the performance of PAT/PPG-based HSAT. Choi et al. used WatchPAT-100 in 25 subjects and showed a sensitivity and specificity of 0.810 and 0.770 in a population with a prevalence of 68% for AHI ≥ 15 events/h [45]. Li et al. studied WatchPAT-200 performance in 43 individuals with suspected OSA and revealed a sensitivity and specificity of 0.938 and 0.667 in a population with a prevalence of 57% for AHI ≥ 15 events/h [42]. Ioachimescu et al. recently conducted a study using WatchPAT-200 in 500 consecutive veterans and reported a sensitivity and specificity of 0.910 and 0.610 with a prevalence of 58% for AHI ≥ 15 events/h [17]. Massie et al. compared NightOwl with simultaneous PSG with automated scoring in 101 subjects and showed a sensitivity and specificity of 0.970 and 0.830 in a population with a prevalence of 59% for AHI ≥ 15 events/h [44]. The current study demonstrated a comparable sensitivity of 0.931 [95% CI, 0.772–0.992] and specificity of 0.735 [95% CI, 0.589–0.850] in a population with a relatively low prevalence of moderate to severe disease (37%).
Methods to improve diagnostic precision in PAT/PPG-based testing
Overall, PAT/PPG-based testing has a sensitivity and specificity in the range of 0.810 to 0.970 and 0.610 to 0.830 for moderate to severe OSA and has the potential to significantly misclassify OSA severity [17, 42, 44, 45]. A couple of approaches have recently been developed to improve the performance and diagnostic concordance of PAT/PPG-based testing. Zhang et al. developed and validated a manual algorithm for visual editing of WatchPAT automated scoring and assessed its accuracy in an unselected clinical population [46]. The authors concluded that a 10–15 minute manual editing of automatic scored data can improve correlation and agreement with PSG as well as a concordance for categorical agreement of OSA severity. Alternatively, Ioachimescu et al. explored statistical models to predict AHI by using robust functional parameters from WatchPAT-200 in concert with available demographic and anthropometric data including age, gender, neck circumference, and body mass index [47]. In this cohort of 500 patients with a high pretest probability of OSA, the mean diagnostic accuracy of WatchPAT was improved to 67%, 81%, and 85% in mild, moderate-severe, or no OSA, respectively. The authors concluded that these models can be used to improve the diagnostic precision of the PAT-based testing, thus ameliorating the high rates of misclassification for OSA presence or disease severity.
Our study demonstrated that another feasible approach to improve diagnostic precision is to simply combine PAT/PPG-based testing with STOP-Bang questionnaire, which is ubiquitously used for OSA screening in clinical practice. The concept of combining a prediction score and portable testing for diagnosis and screening of OSA is not new [48–50]. Morales et al. addressed the diagnosis of severe OSA in a sleepy elderly population with a two-stage strategy using Multivariable Apnea Prediction score followed by nasal pressure-based HSAT [48]. Gurubhagavatula et al., using the same approach, screened internal medicine outpatients with hypertension for severe OSA. Both studies concluded that a two-stage approach performed better in identifying severe OSA than the single-stage approach [49]. More recently, Mashaqi et al. reported that the combined use of STOP-Bang and nocturnal oximetry measures improved the accuracy of severe OSA screening in both inpatient and outpatient settings [50]. Our combined approach provides an easy method to better predict moderate to severe OSA with high precision in the majority of subjects even in the setting of a relatively low prevalence and allows further stratification, with which an appropriate clinical course of action can be consequently taken. This proposed approach can potentially curtail the need for more sophisticated sleep testing, which may lead to significant healthcare cost savings.
Strengths and weaknesses
This study is the first investigation to use a combination of a sleep questionnaire and a medical-grade wearable using neural network algorithm to identify OSA. One of the strengths of this study is the concurrent recording of both in-lab PSG and BSP. All sleep studies were manually scored based on the most current AASM scoring manual by one of our two senior registered sleep technicians and reviewed by an experienced board-certified sleep specialist. The scoring technicians and the sleep specialist reviewing the sleep studies were blinded to the BSP results.
As far as the limitations are concerned, readers should take into account that this sampled population, unlike a typical sleep lab population with high OSA prevalence, skewed towards females and those with no OSA or mild OSA. This could have resulted from a high percentage of male patients with severe OSA declining to consent. This made the comparison of this study with other studies difficult, but nonetheless allows us an opportunity to project how BSP may perform in a non-sleep clinic where the prevalence of moderate to severe OSA is relatively low. Another limitation of this study is that this study was not performed in an unattended home setting but a sleep lab setting. Further investigation in the home setting in comparison to established HST devices is warranted. Finally, this diagnostic algorithm combining STOP-Bang and bAHI requires further validation in various patient populations and clinical settings.
BSP is a promising wearable sleep technology that can potentially be incorporated into clinical practice for detecting OSA. Combining STOP-Bang cutoff of 5 with a bAHI cutoff of 15 events/h improves prediction precision and diagnostic concordance in detecting moderate or severe OSA, which may be used to streamline the clinical practice. Further clinical investigation for the diagnosis and screening of moderate to severe OSA using BSP with or without the combination with STOP-Bang is warranted.
S1 Data.
(XLS)
The authors gratefully acknowledge Dr. Frances Chung and UHN as the owner of STOP-BANG questionnaire, www.stopbang.ca. We also acknowledge Jessica Guggenbiller and the sleep tech team of University Hospitals Sleep Lab for their expertise and assistance in data collection.
1. Gami AS, Howard DE, Olson EJ, Somers VK. Day–night pattern of sudden death in obstructive sleep apnea. N. Engl. J. Med. 2005; 352(12): 1206–1214. pmid:15788497
2. Punjabi NM, Caffo BS, Goodwin JL, Gottlieb DJ, Newman AB, O'Connor GT, et al. Sleep-disordered breathing and mortality: a prospective cohort study. PLOS Med. 2009; 6(8): e1000132. pmid:19688045
3. Young T, Finn L, Peppard PE, Szklo-Coxe M, Austin D, Nieto FJ, et al. Sleep disordered breathing and mortality: eighteen-year follow-up of the Wisconsin sleep cohort. Sleep. 2008; 31(8): 1071–1078. pmid:18714778
4. Marin JM, Agusti A, Villar I, Forner M, Nieto D, Carrizo SJ, et al. Association between treated and untreated obstructive sleep apnea and risk of hypertension. JAMA. 2012; 307(20): 2169–2176. pmid:22618924
5. Gottlieb DJ, Yenokyan G, Newman AB, O'Connor GT, Punjabi NM, Quan SF, et al. Prospective study of obstructive sleep apnea and incident coronary heart disease and heart failure. Circulation. 2010; 122(4): 352–360. pmid:20625114
6. Arzt M, Young T, Finn L, Skatrud JB, Bradley TD. Association of sleep-disordered breathing and the occurrence of stroke. Am. J. Respir. Crit. Care Med. 2005; 172(11): 1447–1451. pmid:16141444
7. Marin JM, Carrizo SJ, Vicente E, Agusti AGN. Long-term cardiovascular outcomes in men with obstructive sleep apnoea-hypopnoea with or without treatment with continuous positive airway pressure: an observational study. Lancet. 2005; 365(9464): 1046–1053. pmid:15781100
8. Peppard PE, Young T, Barnet JH, Palta M, Hagen EW, Hla KM. Increased prevalence of sleep-disordered breathing in adults. Am. J. Epidemiol. 2013; 177(9): 1006–1014. pmid:23589584
9. Heinzer R, Vat S, Marques-Vidal P, Marti-Soler H, Andries D, Tobback N, et al. Prevalence of sleep-disordered breathing in the general population: the HypnoLaus study. Lancet Respir. Med. 2015; 3(4): 310–318. pmid:25682233
10. Senaratna C V, Perret JL, Lodge CJ, Lowe AJ, Campbell BE, Matheson MC, et al. Prevalence of obstructive sleep apnea in the general population: a systematic review. Sleep Med. Rev. 2017; 34: 70–81. pmid:27568340
11. Collop AN, Tracy LS, Kapur V, Mehra R, Kuhlmann D, Fleishman AS, et al. Obstructive sleep apnea devices for out-of-center (OOC) testing: technology evaluation. J. Clin. Sleep Med. 2011; 07(05): 531–548. pmid:22003351
12. Kapur VK, Auckley DH, Chowdhuri S, Kuhlmann DC, Mehra R, Ramar K, et al. Clinical practice guideline for diagnostic testing for adult obstructive sleep apnea: an American Academy of Sleep Medicine clinical practice guideline. J. Clin. Sleep Med. 2017; 13: 479–504. pmid:28162150
13. Rosen I, Kirsch D, Chervin R, Carden K, Ramar K, Aurora R, et al. Clinical use of a home sleep apnea test: an American Academy of Sleep Medicine position statement. J. Clin. Sleep Med. 2017; 13: 1205–1207. pmid:28942762
14. Mysliwiec V, Martin JL, Ulmer CS, Chowdhuri S, Brock MS, Spevak C, et al. The Management of chronic insomnia disorder and obstructive sleep apnea: synopsis of the 2019 U.S. Department of Veterans Affairs and U.S. Department of Defense clinical practice guidelines. Ann. Intern. Med. 2020; 172(5): 325–336. pmid:32066145
15. Schnall RP, Shlitner A, Sheffy J, Kedar R, Lavie P. Periodic, Profound peripheral vasoconstriction—a new marker of obstructive sleep apnea. Sleep. 1999; 22(7): 939–946. pmid:10566912
16. Ayas NT, Pittman S, MacDonald M, White DP. Assessment of a wrist-worn device in the detection of obstructive sleep apnea. Sleep Med. 2003; 4(5): 435–442. pmid:14592285
17. Ioachimescu OC, Allam JS, Samarghandi A, Anand N, Fields BG, Dholakia SA, et al. Performance of peripheral arterial tonometry—based testing for the diagnosis of obstructive sleep apnea in a large sleep clinic cohort. J. Clin. Sleep Med. 2020; 16(10). pmid:32515348
18. Peake JM, Kerr G, Sullivan JP. A critical review of consumer wearables, mobile applications, and equipment for providing biofeedback, monitoring stress, and sleep in physically active populations. Front. Physiol. 2018; 9: 743. pmid:30002629
19. Dunn J, Runge R, Snyder M. Wearables and the medical revolution. Per. Med. 2018; 15(5): 429–448. pmid:30259801
20. Ko P-RT, Kientz J, Choe EK, Kay M, Carol LA, Watson NF. Consumer sleep technologies: a review of the landscape. J. Clin. Sleep Med. 2021; 11(12): 1455–1461. pmid:26156958
21. de Zambotti M, Cellini N, Goldstone A, Colrain I, Baker F. Wearable sleep technology in clinical and research settings. Med. Sci. Sports Exerc. 2019; 51(7): 1538–1557. pmid:30789439
22. de Zambotti M, Cellini N, Menghini L, Sarlo M, Baker FC. Sensors capabilities, performance, and use of consumer sleep technology. Sleep Med. Clin. 2020; 15(1): 1–30. pmid:32005346
23. O'Mahony AM, Garvey JF, McNicholas WT. Technologic advances in the assessment and management of obstructive sleep apnoea beyond the apnoea-hypopnoea index: a narrative review. J. Thorac. Dis. Vol 12, No 9 (September 2020) J. Thorac. Dis. 2020. pmid:33145074
24. Papini GB, Fonseca P, van Gilst MM, Bergmans JWM, Vullings R, Overeem S. Wearable monitoring of sleep-disordered breathing: estimation of the apnea–hypopnea index using wrist-worn reflective photoplethysmography. Sci. Rep. 2020; 10(1): 13512. pmid:32782313
25. Randerath W, Bassetti CL, Bonsignore MR, Farre R, Ferini-Strambi L, Grote L, et al. Challenges and perspectives in obstructive sleep apnoea. Eur. Respir. J. 2018; 52(3): 1702616. pmid:29853491
26. Scott H, Lack L, Lovato N. A systematic review of the accuracy of sleep wearable devices for estimating sleep onset. Sleep Med. Rev. 2020; 49: 101227. pmid:31901524
27. Perez-Pozuelo I, Zhai B, Palotti J, Mall R, Aupetit M, Garcia-Gomez JM, et al. The future of sleep health: a data-driven revolution in sleep science and medicine. npj Digit. Med. 2020; 3(1): 42. pmid:32219183
28. Hicks JL, Althoff T, Sosic R, Kuhar P, Bostjancic B, King AC, et al. Best practices for analyzing large-scale health data from wearables and smartphone apps. npj Digit. Med. 2019; 2(1): 45. pmid:31304391
29. He J, Baxter SL, Xu J, Xu J, Zhou X, Zhang K. The practical implementation of artificial intelligence technologies in medicine. Nat. Med. 2019; 25(1): 30–36. pmid:30617336
30. Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat. Med. 2019; 25(1): 44–56. pmid:30617339
31. Gu W, Leung L. A novel home screening platform for obstructive sleep apnea through wearable ring-type pulse oximeter. Sleep. 2018; 41(Apr 2018).
32. Gu W, Leung L, Kwok KC, Wu I-C, Folz RJ, Chiang AA. Belun Ring Platform: a novel home sleep apnea testing system for assessment of obstructive sleep apnea. J. Clin. Sleep Med. 2020; 16(9): 1611–1617. pmid:32464087
33. Chiu H-Y, Chen P-Y, Chuang L-P, Chen N-H, Tu Y-K, Hsieh Y-J, et al. Diagnostic accuracy of the Berlin questionnaire, STOP-BANG, STOP, and Epworth sleepiness scale in detecting obstructive sleep apnea: A bivariate meta-analysis. Sleep Med. Rev. 2017; 36: 57–70. pmid:27919588
34. Chung F, Abdullah HR, Liao P. STOP-Bang questionnaire: a practical approach to screen for obstructive sleep apnea. Chest. 2016; 149(3): 631–638. pmid:26378880
35. Nagappa M, Liao P, Wong J, Auckley D, Ramachandran SK, Memtsoudis S, et al. Validation of the STOP-Bang questionnaire as a screening tool for obstructive sleep apnea among different populations: a systematic review and meta-analysis. PLOS One. 2015; 10(12): e0143697. pmid:26658438
36. Berry R, Brooks R, Gamaldo C, Harding S, Lloyd R, Marcus C, et al. The AASM manual for the scoring of sleep and associated events: rules, terminology and technical specifications. Version 2.4. 2017.
37. Berry R, Budhiraja R, Gottlieb D, Gozal D, Iber C, Kapur V, et al. Rules for scoring respiratory events in sleep: update of the 2007 AASM manual for the scoring of sleep and associated events. J. Clin. Sleep Med. 2012; 08(05): 597–619. pmid:23066376
38. R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing, 2021 Feb 15. Available from: https://cran.r-project.org/doc/manuals/r-release/fullrefman.pdf
39. Mantel N, Haenszel W. Statistical aspects of the analysis of data from retrospective studies of disease. JNCI J. Natl. Cancer Inst. 1959; 22(4): 719–748. pmid:13655060
40. Bland JM, Altman D. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986; 327(8476): 307–310. pmid:2868172
41. Efron B. Nonparametric standard errors and confidence Intervals. Can. J. Stat. 1981; 9(2): 139–158.
42. Li W, Wang R, Huang D, Liu X, Jin W, Yang S. Assessment of a portable monitoring device Watch PAT 200 in the diagnosis of obstructive sleep apnea. Eur. Arch. Oto-Rhino-Laryngology. 2013; 270: 3099–3105. pmid:23708441
43. Gan YJ, Lim L, Chong YK. Validation study of WatchPat 200 for diagnosis of OSA in an Asian cohort. Eur. Arch. Oto-Rhino-Laryngology. 2017; 274(3): 1741–1745. pmid:27796555
44. Massie F, de Almeida DM, Dreesen P, Thijs I, Vranken J, Klerkx S. An evaluation of the NightOwl home sleep apnea testing system. J. Clin. Sleep Med. 2018; 14: 1791–1796. pmid:30353811
45. Choi JH, Kim EJ, Kim YS, Choi J, Kim TH, Kwon SY, et al. Validation study of portable device for the diagnosis of obstructive sleep apnea according to the new AASM scoring criteria: Watch-PAT 100. Acta Otolaryngol. 2010; 130(7): 838–843. pmid:20082567
46. Zhang Z, Sowho M, Otvos T, Sperandio LS, East J, Sgambati F, et al. A comparison of automated and manual sleep staging and respiratory event recognition in a portable sleep diagnostic device with in-lab sleep study. J. Clin. Sleep Med. 2020. pmid:32022670
47. Ioachimescu OC, Dholakia SA, Venkateshiah SB, Fields B, Samarghandi A, Anand N, et al. Improving the performance of peripheral arterial tonometry-based testing for the diagnosis of obstructive sleep apnea. J. Investig. Med. 2020; jim-2020-001448. pmid:32900784
48. Morales CR, Hurley S, Wick LC, Staley B, Pack FM, Gooneratne NS, et al. In-home, self-assembled sleep studies are useful in diagnosing sleep apnea in the elderly. Sleep. 2012; 35(11): 1491–1501. pmid:23115398
49. Gurubhagavatula I, Fields BG, Morales CR, Hurley S, Pien GW, Wick LC, et al. Screening for severe obstructive sleep apnea syndrome in hypertensive outpatients. J. Clin. Hypertens. 2013; 15(4): 279–288. pmid:23551728
50. Mashaqi S, Staebler D, Mehra R. Combined nocturnal pulse oximetry and questionnaire-based obstructive sleep apnea screening–A cohort study. Sleep Med. 2020; 72: 157–163. pmid:32653766
Is the Subject Area "Sleep" applicable to this article?
Polysomnography
Is the Subject Area "Polysomnography" applicable to this article?
Is the Subject Area "Algorithms" applicable to this article?
Is the Subject Area "Sleep apnea" applicable to this article?
Is the Subject Area "Heart" applicable to this article?
Is the Subject Area "Heart rate" applicable to this article?
Is the Subject Area "Artificial neural networks" applicable to this article?
Is the Subject Area "Neurons" applicable to this article?