1 / 42

Sleep Tracking and Wearable Tech Anita Valanju Shelgikar, MD October 20, 2016

Sleep Tracking and Wearable Tech Anita Valanju Shelgikar, MD October 20, 2016. Objectives:. Sleep tracking. Clinical Applications. Wearable tech. Key points:. Sleep tracking. Validation studies for sleep tracking: some exist, but we need more. Clinical Applications. Wearable tech.

mleak
Download Presentation

Sleep Tracking and Wearable Tech Anita Valanju Shelgikar, MD October 20, 2016

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Sleep Tracking and Wearable Tech Anita Valanju Shelgikar, MD October 20, 2016

  2. Objectives: Sleep tracking Clinical Applications Wearable tech

  3. Key points: Sleep tracking Validation studies for sleep tracking: some exist, but we need more Clinical Applications Wearable tech Expect more of our patients to use wearables as part of their daily routine Incorporation of patient- specific data from wearables may allow us to better serve each individual patient

  4. https://en.wikipedia.org

  5. Sleep monitoring

  6. Polysomnography Image from https://www.nhlbi.nih.gov http://www.newgate.uk.com/

  7. Home sleep apnea testing Images from http://yoursleep.aasmnet.org www.ppdsleep.com/

  8. Actigraphy Image from www.sleepdt.com/ CHEST 2011; 139( 6 ): 1514 – 1527

  9. Accelerometer = movement monitor • Measure acceleration along a given axis • Micro–mechanical springs • Changes in capacitance • Piezo–electric

  10. Accelerometer = movement monitor • Measure acceleration along a given axis • Micro–mechanical springs • Changes in capacitance • Piezo–electric • Multiple axis measurements can be bundled into a single monitor, allowing multiple planes of movement to be captured • Counts are summed over a specified period of time (epoch) and stored • Many accelerometers have the storage capacity to assess physical activity over 21 day periods using a 30 or 60 second epoch • Sensor converts movements into electrical signals (counts) that are proportional to the muscular force producing motion Images from www.qsportstechnology.com/ http://www.parcph.org/accDef.aspx quantifiedself.com/gsr/ www.firstcoastnews.com/

  11. Patient-driven monitoring Mobile applications (apps) Wearable technologies Images from www.businessinsider.com www.psfk.com

  12. 14 IEEE Pulse September/October 2014

  13. Cellphone accelerometers are based on semiconductor accelerometers • Microchips with all their components chemically etched onto the surface of a piece of silicon • Measure changes in capacitance between electrodes https://blogs.windows.com/buildingapps/2010/09/08/using-the-accelerometer-on-windows-phone-7/

  14. Patient-driven monitoring Mobile applications (apps) Wearable technologies Images from www.businessinsider.com www.psfk.com

  15. What are wearables? Digital Insoles Sony SmartEyeGlass Jawbone UP Apple Watch • Wearable technology • Electronic technologies or computers incorporated into clothing and accessories • Smart sensors use of a web connection, usually using Bluetooth to connect wirelessly to a smartphone Smarty Ring Misfit Swarovski Shine Samsung Gear VR MBody Bike & Run NFC Ring Implantables www.wareable.com

  16. Artificial Intelligence in Medicine 56 (2012) 137–156

  17. Wearable self-tracking devices and mobile apps CHEST 2016; http://dx.doi.org/10.1016/j.chest.2016.04.016

  18. ? Image from www.theatreatfirst.org

  19. “Quantified Self” • Coined by Wired magazine in 2007 • ‘A collaboration of users and tool makers who share an interest in self knowledge through self-tracking.’” http://www.healthworkscollective.com

  20. Gartner Hype Cycle 5 key phases of a technology's life cycle  Image from www.gartner.com

  21. Stated another way… https://www.linkedin.com/pulse/20140814105952-7082046-gartner-hype-cycle-2014

  22. Use of patient-driven monitoring • 2012 study from the Pew Research Center • Estimated that 7 out of 10 Americans were tracking health indicators, either for themselves or for a loved one • 21% of the respondents claimed to use some form of technology to record and store these data • Given the continued growth of health tracking technologies, these numbers are now likely greater than in 2012 J Sleep Res. (2015) 24, 121–123

  23. Use of patient-driven monitoring • Uptake of wearable devices is bimodally distributed • 25 to 34-year-olds use them for fitness enhancement • 55 to 64-year-olds use them to improve overall health • Worldwide it is estimated that about 100 million people track some form of fitness or health data on a regular basis • Hard to know which of these are related to sleep J Sleep Res. (2015) 24, 121–123 BMC Medicine (2015) 13:77

  24. Patient-driven monitoring Concerns • Some apps collect information from individuals and make pooled data publicly available for consumption, research, or marketing purposes, without each individual’s enduring consent or knowledge. • Legal accountability and regulation of consumer health technologies are developing but not fully implemented. • FDA oversight of mobile apps is being defined but will need to continually evolve as technology advances. • Many health-related technologies marketed directly to users claim to be “entertainment devices” and deny any official medical claims in fine print, though the public is generally unaware of this. J Clin Sleep Med 2015;11(12):1455–1461.

  25. Patient-driven monitoring Potential Benefits • Integrated use of mobile apps will allow patient data to be collected more frequently and more effectively, which may facilitate improvement in quality of patient care. • Patient-specific data from patient self-monitoring can be used to make individualized diagnoses and/or treatment plans. • Use of mobile apps and wearable tech may facilitate better chronic disease management via more real-time communication with patient and reduction of unnecessary office visits. • Use of patient-driven monitoring could impact population health management via increased access to care. N Engl J Med 2014; 371:372-379

  26. “Tonight, I’m launching a new Precision Medicine Initiative to bring us closer to curing diseases like cancer and diabetes — and to give all of us access to the personalized information we need to keep ourselves and our families healthier.” President Barack Obama, State of the Union Address, January 20, 2015 http://www.nih.gov/precisionmedicine

  27. Tech and precision medicine • Can provide phenotypic information to complement available genotypic information • Example: • Recent cardiovascular mobile health study(MyHeartCounts) recruited 30, 000 smartphone users in the first2 weeks after launch • Potential applications: • Disease prevention via continuous monitoring of activity, sleep, heart rate, etc. • Immediate, personalized feedback to help modify behavior • Assess effectiveness of an intervention • Individual or population JAMA June 2, 2015 Volume 313, Number 21

  28. Health tracking & precision medicine Tangible benefits so far • 2013 Data from the Pew Research Center indicate that people with more serious health problems are more likely to report benefits as a result of tracking their health • Meta-analysis of activity monitor-based counseling studies with diabetes patients • Activity monitor-based counseling had a beneficial effect on physical activity, blood glucose, systolic blood pressure, and body mass index • Use of a wearable activity tracker during inpatient post-surgical showed a significant relationship between the early recovery step count, hospital length of stay in a group of elderly cardiac surgery patients J Med Internet Res. 2014;16:192 Ann Med. 2013;45:397–412. Ann Thorac Surg. 2013;96:1057–61

  29. Health tracking & precision medicine Room for improvement • Review of popular activity monitors showed that that goal-setting, behavioral goal review, behavior feedback, self-monitoring, and rewards were generally included • Often lacked other important components, such as problem-solving, behavioral instruction, and commitment strategies • Need more evidence about effectiveness of health-tracking data in the management of chronic diseases • A survey of 2,000 individuals showed that 80% expressed concerns about privacy of personal data with use of wearable tech https://newsroom.accenture.com BMC Medicine (2015) 13:77

  30. How can I learn more about health tracking, mobile apps, and wearables? https://commonbond.co

  31. http://apps.nhs.uk/ The National Health Service (NHS) in England

  32. Local resources Patricia Anderson Emerging Technologies Informationist, Taubman Health Sciences Library Marc Stephens Instructional Designer – MSIS University of Michigan Medical School “Tech Savvy Fitness”

  33. Key points: Sleep tracking Validation studies for sleep tracking: some exist, but we need more Clinical Applications Wearable tech Expect more of our patients to use wearables as part of their daily routine Incorporation of patient- specific data from wearables may allow us to better serve each individual patient

  34. Screenshot of the graphical display of a whole-night recording from a study subject by the Sleep Time app on an iPhone. Comparison of absolute parameters obtained by polysomnography and provided by the app for subjects in the study (n = 20). ap < 0.0001 bp = 0.008 ap < 0.0001 cp = 0.015 Hypnogram showing sleep stages recorded by simultaneous polysomnography. J Clin Sleep Med 2015;11(7):709–715

  35. The app’s sleep vs. wake discrimination mirrored that reported for wrist actigraphy: • ~90% sensitive and ~50% specific for sleep • The app overestimated sleep (as does wrist actigraphy) • Likely because quiet wakefulness contains little movement • Conclusion: • Sleep Time app is insufficiently precise to serve as an alternative to polysomnography for sleep- wake cycle analysis • May serve as an alternative to actigraphy or subjective measurements of sleep (e.g. sleep diaries) J Clin Sleep Med 2015;11(7):695–696 J Clin Sleep Med 2015;11(7):709–715 Image from www.respitek.com.tr/

  36. Validation data – activity monitor Fitbit vs Actigraph Fitbit vs PSG Actigraph vs PSG • 24 healthy adults • Fitbit and Actigraph worn during polysomnography • Data collection • Fitbit: 60 second epochs • Actigraph: 30 second epochs • Conclusion: • Fitbit and Actigraph • Overestimated sleep efficiency and total sleep time (overcalling quiet wakefulness) • High sensitivity for accurately identifying sleep within all stages of sleep • Low specificity for accurately identifying wake Sleep Breath (2012) 16:913–917 Image from www.fitbit.com

  37. Validation of another wearable Sixty-five adolescents ages 12–22 years (28 females) SLEEP 2015;38(9):1461–1468 Image from http://activitytrackerworld.com/jawbone-up4-review/

  38. Validation data for a wireless system 29 healthy adults - Concurrent polysomnography, actigraphy, and wireless system (Zeo) in a sleep laboratory for one night [preceded by an acclimation night] *Performance negatively impacted by bruxism and by neuroactive medications - Altered forehead-based signal properties and algorithm output accuracy J Clin Sleep Med 2015;11(7):695–696 J. Sleep Res. (2012) 21, 221–230 Neurology 2012;2012:153745

  39. “Yet while it may have been the darling of sleep trackers, ‘consumers weren’t that interested in complex and relatively costly methods for tracking sleep,’ analyst Michael Gartenberg told Wired. Zeo sold for about $400 and required users to wear an uncomfortable elastic headband to sleep that by morning had left unsightly indentations on your forehead.” http://www.wired.com/2013/03/lights-out-for-zeo/

More Related