Wearables & Other Emerging Technologies for Sleep Tracking. Anita Valanju Shelgikar, MD October 14, 2017

Transcription

1 Wearables & Other Emerging Technologies for Sleep Tracking Anita Valanju Shelgikar, MD October 14, 2017

2 Conflict of Interest Disclosure I do not have any relationships with any entities producing, marketing, re-selling, or distributing health care goods or services consumed by, or used on, patients, OR Type of Potential Conflict Grant/Research Support Consultant Speakers Bureaus Financial support Other Details of Potential Conflict N/A N/A N/A N/A N/A The material presented in this lecture has no relationship with any of these potential conflicts, OR

3 Objectives: Types of wearable technology Nonwearable modalities for sleep tracking Incorporation into clinical practice

4 Key points: Types of wearable technology Validation studies for sleep tracking: some exist, but we need more Expect more of our patients to use technology as part of their daily routine Non-wearable technologies for sleep tracking Incorporation into clinical practice Incorporation of patientspecific data from wearables may allow us to better serve each individual patient

5

6 Patient-driven monitoring Mobile applications (apps) Wearable technologies Images from

7 Artificial Intelligence in Medicine 56 (2012)

8 Actigraphy Image from CHEST 2011; 139( 6 ):

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

10 Accelerometer = movement monitor 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 Sensor converts movements into electrical signals (counts) that are proportional to the muscular force producing motion Many accelerometers have the storage capacity to assess physical activity over 21 day periods using a 30 or 60 second epoch Images from quantifiedself.com/gsr/

11 Actigraphy

12 Patient-driven monitoring Mobile applications (apps) Wearable technologies Images from

13 What are wearables? Apple Watch Digital Insoles Sony SmartEyeGlass 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 Jawbone UP Misfit Swarovski Shine Smarty Ring Implantables Samsung Gear VR MBody Bike & Run NFC Ring

14 CHEST 2016; 150(3):

15 Validation data activity monitor 24 healthy adults - Fitbit and Actigraph worn during polysomnography Data collection - Fitbit: 60 second epochs - Actigraph: 30 second epochs Conclusion: Fitbit vs PSG Actigraph vs PSG Fitbit vs Actigraph 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: Image from

16 Patient-driven monitoring Mobile applications (apps) Wearable technologies Images from

17

18 14 IEEE Pulse September/October 2014

19 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

20 Smartphone apps for OSA screening Physiol. Meas. 34 (2013) R29 R46

21 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). a p < b p = a p < c p = Hypnogram showing sleep stages recorded by simultaneous polysomnography. J Clin Sleep Med 2015;11(7):

22 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): J Clin Sleep Med 2015;11(7):

23 Image from

24 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.

25 Gartner Hype Cycle 5 key phases of a technology's life cycle Image from

26 Stated another way

27

28 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,

29 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, BMC Medicine (2015) 13:77

30

31 Concerns Patient-driven monitoring 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;(6):epub N Engl J Med 2014; 371:

32 Potential benefits Patient-driven monitoring 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. J Clin Sleep Med 2015;(6):epub N Engl J Med 2014; 371:

33 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,

34 Precision Medicine Precisely tailoring therapies to subcategories of disease Identification of patients via genomics, metabolomics, proteomics, diverse cellular assay Potential for health benefits and cost savings due to more effective selection of individuals Based on a priori potential for drug response or baseline disease risk Potential applications: Genetic diseases Oncology Disease prevention Medication prescription JAMA June 2, 2015 Volume 313, Number 21 N Engl J Med 372;9 February 26, 2015

35 Tech and precision medicine Can provide phenotypic information to complement available genotypic information Example: 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

36 Tangible benefits so far Health tracking and precision medicine 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 Ann Med. 2013;45: J Med Internet Res. 2014;16:192 BMC Medicine (2015) 13:77 Ann Thorac Surg. 2013;96:

37 Room for improvement Health tracking and precision medicine 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 problemsolving, 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 Ann Med. 2013;45: J Med Internet Res. 2014;16:192 BMC Medicine (2015) 13:77 Ann Thorac Surg. 2013;96:

38

39 How can I learn more about health tracking, mobile apps, and wearables?

40 The National Health Service (NHS) in England

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

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

43