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The Power of Sensors in health & healthcare

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In a series of reports we explore key digital health trends and related opportunities for technology companies, healthcare providers and patients-consumers. We take both an international and Flemish perspective, the latter based on interviews with local stakeholders. In this report we focus on sensor-based applications.

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The Power of Sensors in health & healthcare

  1. 1. the power of sensors in health & healthcare
  2. 2. Exploring Digital Health Trends Report #2: The Power of Sensors In a series of reports we explore key digital health trends and related opportunities for technology companies, healthcare providers and patients-consumers. We take both an international and Flemish perspective, the latter based on interviews with local stakeholders. In this report we focus on sensor-based applications. A big thanks to Chris Van Hoof (Imec), Julien Penders (Bloom Technologies), Lars Grieten (Uhasselt), Daniel Berckmans (KU Leuven) and Frederik Horemans (DSP Valley) for valuable input. You can read our interviews with them on the blog at www.micvlaanderen.be Author: Frank Boermeester About Microsoft Innovation Center Vlaanderen Our mission is to stimulate ICT-related innovation and entrepreneurship in Flanders, with a particular focus on healthcare. We do so by supporting high-potential technology startups. MIC Vlaanderen has two operational offices in the cities of Genk and Kortrijk, Belgium. www.micvlaanderen.be
  3. 3. The Promise Not so fast! Opportunities ahead! Conclusion AGENDA
  4. 4. The Promise Gartner Hype Cycle: A helpful framework
  5. 5. The Promise (or Peak of Inflated Expectations)
  6. 6. Dr. Algorithm is coming “In the next 10 years, data science and software will do more for medicine than all the biological sciences together.” – Vinod Khosla, Khosla Ventures http://techcrunch.com/2013/09/11/vinod-khosla-in-the-next-10-years-data- science-will-do-more-for-medicine-than-all-biological-sciences-combined/
  7. 7. But sensors underpin the promise of digital health Data-driven health applications require data. Sensors make possible automated, large-scale monitoring & measurement of health-related parameters
  8. 8. And what a promise it is, in all health domains! DIAGNOSIS MONITORING TREATMENT WELLNESS
  9. 9. Just imagine! DIAGNOSIS Sensors systems will make diagnosis easier, faster, cheaper and more accurate. They will also predict health problems giving people time to intervene Will X-Prize contestants like Scanadu (or one of the other 9 finalists) deliver Star Trek’s Tricorder?
  10. 10. Just imagine! Doctors will rely on sensors to monitor their chronically ill patients, providing early warning for any potential problems Will chronically ill patients benefit from a 24/7 connection to specialised medical care, as being pioneered by Cardiology at Ziekenhuis Oost Limburg? MONITORING
  11. 11. Just imagine! Sensors will help improve medication compliance and will be critical components in physical augmentation Will companies like BrainControl help people in a locked-in state to ‘speak’ by sensing their thoughts? TREATMENT
  12. 12. Just imagine! Mobile & wearable health trackers will help people overcome their lifestyle-based health risks Will your personal digital health coach become as ubiquitous as the mobile phone? WELLNESS
  13. 13. By 2017 the number of wearable wireless health and fitness devices will reach 169.5 million (90 mil fitness devices + 80 mil health-focused devices). (ABI Research) $47billion 44.4% 169million Great Market Expectations The sensor market in Consumer Healthcare is expected to reach $47.40 Billion by 2020 growing at an estimated CAGR of 5.56% from 2014-2020. (MarketsandMarkets) Approx. 3 million patients worldwide were using remote wireless devices to display health-monitoring results in 2013. It is estimated that the number will grow at a compound annual growth rate (CAGR) of 44.4 percent to 19.1 million in 2018. (Berg Insights)
  14. 14. Not so fast! (the Trough of Disillusionment)
  15. 15. User Disillusionment? PwC reported that mobile health apps show immense user drop-out: 67% of people who use an app with manual data entry stop in the first 6 months. Remarkably, for automated (sensor-based) apps the figure is even higher! 74%. 74% drop out PwC report Emerging mHealth: paths for growth (2013/EIU analysis)
  16. 16. Tracker Efficacy Questions “To date, no long-term, peer-reviewed study has shown that people using activity trackers become and remain more active.” – Well/New York Times, March 10 2014 "The durability of the effect is still in question. We don't have randomised [clinical] trials showing improved outcomes or durability in influencing behaviour.“ - Dr Eric Topol, author of The Creative Destruction of Medicine, director of the Scripps Translational Science Institute (as quoted in Wired.co.uk, 23 January 2013)
  17. 17. Doctor Resistance? 53% 24% PwC report Emerging mHealth: paths for growth (2013/EIU analysis) 53% of younger doctors (who one would think are more open to change) worry that mHealth will make patients too independent. (This compares to 42% for all age groups) And 24% of younger doctors actively discourage patients from using mHealth applications. (13% all age groups) Economist Intelligence Unit research (in PwC Report: Emerging mHealth) “Don’t come to us telling us you can upload [data] into our electronic medical record. We don’t necessarily want it there… Our physicians don’t want it all there. They really don’t need to know how much exercise each of their patients is getting on a daily basis; they just don’t have time to process all of that.” - Christine Folck, Lead Innovation Designer, Kaiser Permanente (quoted in mobihealthnews article July 9, 2013)
  18. 18. What are you measuring? Ebola airport screening using thermometers. Photo: Melissa Maraj/U.S. Customs and Border Protection Non-invasive, physical sensors are inherently limited in a health context. There is only so much that temperature, movement, light and electric current can tell you about a person’s health. The inherent limitations of physical sensors
  19. 19. What are you measuring? From sensor data to health interpretation is an arduous route Most fitness trackers and apps rely on a single sensor: an accelerometer which measures force along 3 axes { } An algorithm tries to make sense of this data, but cycling doesn’t generate the right sort of data “You’re being lazy, time to get moving!” And thus makes the wrong interpretation about energy use and physical activity Real-world behaviour generates data, much of which is ‘noise’
  20. 20. Prediction is difficult In a clinical setting, making complex interpretations and predictions on the basis of one or two parameters is a dangerous game. “Blood pressure alone can’t predict your health. In our clinical context we deal with patients who often have multiple diseases but we only focus on the cardiac issue, and that limits our ability to predict the general condition of the patient.” – Lars Grieten, Mobile Health Unit/Dept of Cardiology, University Hasselt Quoted from interview, published at http://www.micvlaanderen.be/word-geinspireerd/door-interviews/
  21. 21. Prediction is difficult Analytical approaches that are based on ‘snapshot’ measurements and comparisons against population norms are inadequate. To improve predictive power one has to model behaviour at the level of an individual “Population norms are not that relevant for the interpretation of individual data; the population average is a purely theoretical concept that in practice no individual will comply with. For example, there is little value in comparing the heart rate of a football player with the team average; you have to measure variation over time in the individual player and make conclusions on that basis.” - Prof Daniel Berckmans, Head M3-BIORES, KU Leuven, research group specialised in biological response monitoring and prediction A new analytical approach is required Quoted from interview, published at http://www.micvlaanderen.be/word-geinspireerd/door-interviews/
  22. 22. Security & Privacy Fears Hackers have demonstrated vulnerabilities in pacemakers, implantable defibrillators, and insulin pumps both by attacking wireless connections and by manipulating sensors with electromagnetic interference. Former Vice President Dick Cheney had his pacemaker’s wireless capabilities deactivated…
  23. 23. Changing the System is Hard “You have a research environment that produces papers, a business environment that produces expectations, and a healthcare environment that creates healthcare. But so far they have not met. This will happen, but how long it will take I’m not sure.” Widespread adoption of sensor-based technology, especially for remote monitoring, is hobbled by reimbursement gaps, regulatory issues, privacy & security fears, poor interoperability and a lack of clinical trials - Steinar Pederse, CEO Tromso Telemedicine Consult (in PwC paper: Emerging mHealth: Partners for Growth, 2013)
  24. 24. Opportunities Ahead! (or Scope of Enlightenment)
  25. 25. Smaller, More Accurate Sensors “The key enabling technologies have been miniaturization and low-power sensors. Sensors have got smaller and smaller and need very little electric power, and that makes possible wearable sensors, ingestible sensors, etc.” – Julien Penders, Biomedical Engineer, ex-Imec, co-founder Bloom Technologies Miniaturization and ultra low power sensor systems are enabling new formats and better integration with the human body, which also improves accuracy Murata's World's Smallest Chip Ferrite Bead (on the far right) (Photo: Business Wire) Quoted from interview, published at http://www.micvlaanderen.be/word-geinspireerd/door-interviews/
  26. 26. CASE MC10 www.mc10inc.com Stretchable skin patch sensor MC10 developed a flexible, stretchable patch (Biostamp) with sensors for monitoring temperature, movement and heart rate. MC10 is seeking FDA approval and recently announced a partnership with pharmaceutical company UCB to explore applications for neurological diseases (e.g. to better measure response to therapies). Ultimately, pharmaceutical companies could bundle such technologies with drugs or therapies to enable personalised therapies. Almost invisible. A sensor that is less obtrusive than a band-aid
  27. 27. CASE Imec and Dutch affiliate Holst Centre www.imec.be www.holstcentre.com Nanoelectronics research institute Holst Centre & Imec, with Shinki Electric Industries, have developed a flexible, low- power health patch that accurately measures physical activity through real-time ECG, tissue contact impedance and accelerometer data. Furthermore, data is processed locally and then transmitted via Bluetooth Smart. Taking accuracy to the next level
  28. 28. CASE Proteus Digital Health www.proteusdigitalhealth.com Developer of an ingestible sensor Proteus developed an ingestible sensor for medication adherence. The accompanying patch tracks the ingestible sensor and detects heart rate and activity. The ingestible sensor secured FDA clearance in 2012. Proteus is one of the best funded digital health companies (approx. $400 million). Medical grade ingestible sensor & patch “The information we measure is verifiably accurate and not just consumer-grade or a toy.” - Proteus CEO Andrew Thompson quoted in MobiHealthNews
  29. 29. CASE Google X www.google.com Google X life sciences division Google X is working on a system for detecting diseases like cancer early. It involves ingesting “painted” nanoparticles that target specific biomarkers. If they find such biomarkers they send out signals that can be picked up by a device such as a wristband. In another project, Google is testing a smart contact lens designed to measure glucose levels in tears. Early prototypes generate a reading once per second. Nanoparticles as sensors “We’ve done a lot, to be quite humble about it. Enough to give us great confidence that this is all likely to work.” - Andrew Conrad, Google X, talking about the nanoparticle project in an interview with Steven Levy, Oct 28, 2014, Medium/BackChannel
  30. 30. CASE Biocartis www.biocartis.com Automated, real-time molecular diagnostics systems Biocartis develops molecular diagnostics systems that integrate (and partly automate) multiple clinical tests in a single device. The systems can conduct diagnostic processes, from sampling to results in very short time frames (40-150 minutes) and with very little hands-on preparation time. Ultimately this promises faster testing, more accurate testing (less prone to human error) and more testing in primary care settings. Biosensors emerge: automating the lab
  31. 31. Combining Multiple Sensors “If you take an individual sensor I don’t see a lot of change there. What is changing is the ability to integrate the perspective from multiple sensors and come to new conclusions because of that integration, that's what changing.” – John Oliver, Senior System Architect, Intel (quoted from Curiosity.com video) Capturing and analysing data from multiple sensors improves predictive power and enables the measurement of more complex parameters. http://www.discovery.com/tv-shows/curiosity/topics/j-oliver-how-is-sensor- technology-evolving.htm
  32. 32. CASE Microsoft Band www.microsoft.com/microsoft-band/ Microsoft’s smartwatch with multiple health-related sensors Most fitness trackers have a single sensor. Microsoft Band includes an accelerometer, an optical heart rate sensor, GPS, an ambient light sensor, a skin temperature sensor, an ultraviolet light sensor, a galvanic skin sensor, and a capacitive sensor. It also has productivity functionality like messaging & notifications. And it connects to the broader HealthVault ecosystem. Multi-functional, multi-sensor, and platform based
  33. 33. CASE Sense www.hello.is A sleep analysis system that also collects environmental data Relying on multiple sensors, the Sense System tracks sleep behaviour (through a clip-on movement sensor) and monitors the bedroom environment (through a nightstand device that senses noise, light, temperature, humidity, and particles in air), to take sleep analysis to a next level. Also it replaces your classic bedside alarm, with the extra that it wakes you up at the right point in your sleep cycle. Sense raised a record $2.4 million on Kickstarter. Embracing contextual data and functionality
  34. 34. CASE Samsung Simband www.samsung.com Wristband sensor module Samsung (with Imec in Belgium) developed what is touted as the world’s most advanced wrist-based sensor module, an open reference design for 3rd party developers. The band is equipped with multiple sensors (optical, electrical, physical) that together enable new biometric measurements such as blood oxygen levels (and possibly other complex parameters such as blood pressure). The world’s most advanced wrist-based sensor module?
  35. 35. Interoperability & Platforms OPEN WINS! The Tech Boom is a story of platforms: the internet, the world wide web, mobile APIs/SDKs, app stores, open data, ... Digital Health is finally getting the message. “Data has traditionally resided in silos belonging to specific applications delivered primarily by device vendors themselves. New cloud platforms capable of collecting data from a range of vendor devices and sharing it securely with a range of related parties including patients, healthcare providers, and payers will drive adoption and bring more connected devices to market,” - Jonathan Collins, principal analyst ABI Research.
  36. 36. Interoperability & Platforms The “Connected Elite”: Best selling sensors connect to as many apps as possible
  37. 37. CASE Angel Sensor www.angelsensor.com Open health & fitness sensor Angel is a Kickstarter funded project to develop an open sensor for health and fitness. The band has sensors to measure heart rate, skin temperature, blood oxygen and physical activity. Contrary to most trackers which come with a proprietary app, Angel plans to open its communication protocols, API/SDK and sensor data streams. The goal is to attract developers and thus create a wide range of apps and application domains A sensor as platform for innovation
  38. 38. CASE Hexoskin www.hexoskin.com Biometric shirt Hexoskin developed a biometric (washable) shirt for tracking heart rate (with ECG precision), breathing, activity & sleep tracking. The product is an Open Platform for developers. Biometric clothing as Open Data platform “Hexoskin is an Open Data device.. We have an open web API that you can use to build 3rd party apps, because we’re not going to build all the health apps ourselves.” - Pierre-Alexander Fournier, Hexoskin, quoted in Montreal Tech Watch
  39. 39. CASE Samsung Digital Health Initiative www.samsung.com Open reference design wristband + open data platform Samsung’s Simband is an “Open Reference Design” so that others can build their own devices and applications without having to reinvent the wheel. Complimenting the Simband, Samsung has also developed a cloud- based and vendor-agnostic platform (S.A.M.I.) with open API that enables data exchange with any device/resource. Furthermore, the platform is equipped with a set of tools for running analytics on data. Building an open ecosystem
  40. 40. CASE Human API and Validic www.humanapi.co www.validic.com API aggregators Human API and Validic both aggregate APIs from multiple data sources (sensing devices mainly) so that app developers can easily integrate multiple data sources via a single authentication and API (as opposed to making direct connections to every device in the market). Letting apps connect to multiple devices with a single API
  41. 41. CASE Intel www.intel.com Hardware components Intel Edison is a low-cost ($50), low-power, stamp-sized microcomputer for wearable devices and Internet of Things. Microcomputer platform play "If you want to build something, doing your own board is expensive and time consuming. We've produced a fully power-managed operating system for this chip, and you can literally build something and go to market in months” - Mike Bell, head of new devices at Intel, quoted in CNET Sept 14, 2014.
  42. 42. CASE Qualcomm Digital Health Initiative www.qualcomm.com Healthcare data platforms Qualcomm launched two integrated cloud-based health information platforms. The 2net platform is an open, non-exclusive and interoperable platform that connects with multiple devices and applications. It enables users and healthcare professionals to collect, store and share biometric data securely. On the front-end, HealthyCircles is a suite of services for sharing data with care circles, logging medication, setting alerts, etc. Building the ecosystem
  43. 43. Making Business Sense Viable business models are possible by solving real, short-term user needs (as opposed to long-term unproven health benefits) and by working with clinicians and providers to integrate (validated) technology in clinical processes. Remote Monitoring is a key growth opportunity. “I think we’re entering a phase of application pull, instead of the earlier technology push phase.” - Prof. Daniel Berckmans, M3- BIORES, K.U. Leuven
  44. 44. CASE Bloom Technologies www.bloom-life.com Wearable sensor for measuring contractions To drive user adoption, Bloom targets an audience with a very specific short-term need: expectant mothers who want to know whether they are having contractions. Also, the company is seeking FDA approval and will rely on Samsung’s open data platform (SAMI). Addressing short-term need to drive adoption “The product we are developing will be able to measure contractions - that will drive adoption - but it will also be able to measure a range of other relevant parameters such as activity, stress, sleep and movement of the baby. We are using those five parameters to model the user's behaviour and subsequently push personalised messages.” - Julien Penders, co-founder, Bloom Technologies (Quoted in interview MIC Vlaanderen)
  45. 45. CASE Qompium www.qompium.com Smartphone app to detect irregular heart rhythms Qompium developed a smartphone app for detecting irregular heart rhythms. In lab conditions (using a high end Android phone) the app has a 93% reliability factor. No fear of the regulator “The app definitely tries to make a diagnosis and therefore will be classified as a medical device. That is exactly our ambition; we want to differentiate ourselves from the thousands of unregulated apps out there.” - Lars Grieten, Qompium, quoted from interview at MIC Vlaanderen
  46. 46. CASE Live!y www.mylively.com Elderly care monitoring solution Live!y developed a remote care solution targeting consumers (monthly subscription fee) using a simple and well-designed set of sensors and a wristband interface (for sending reminders and emergency response + a pedometer). Ingenuous remote care solution targeting consumers
  47. 47. CASE GrandCare Systems www.grandcare.com Elderly care monitoring solution GrandCare integrated multiple (mainly off the shelf) technologies to develop a complete remote care solution. The system includes a touchscreen providing communication tools, instructions, reminders and medication prompts. It also connects with wireless health devices (blood pressure, weight, pulse, glucose, temperature) and motion sensors (e.g. alert if no motion or wondering motion) Integrating today’s technologies to solve a problem today
  48. 48. CASE Healthsense www.healthsense.com Elderly care monitoring solution Healthsense developed a remote monitoring solution for senior living communities. Multiple wireless sensors are used to monitor a resident’s activity, and activity trend data (patterns over time) is then analysed to spot potential health problems. Healthsense has a strong market presence with B2B business model. Working with senior living communities to improve business
  49. 49. Key Lessons (Ride the Wave of Enlightenment)
  50. 50. Ride the Wave of Enlightenment 1.Harness the main technological advances: miniaturization, low- power sensors, more accurate sensors, better integration with human body (e.g., wristband, patch, textile, ingestible), emergence of biosensors) 2.Sensor-based technologies are rapidly turning into reusable, interoperable components and platforms. Exploit that trend. 3.Model individual behaviour and use data from multiple sources to maximise predictive power and thereby make possible actionable user feedback that is ‘surprising’ and relevant.
  51. 51. Ride the Wave of Enlightenment 4.Embrace the regulator. Sensor technologies have advanced sufficiently to compete on accuracy. Resist the ‘gadget’ label. 5.To drive adoption, look for ‘low-hanging fruit’ opportunities that address real, pressing needs among consumers and patients. And/or combine health functionality with functionality that is already ubiquitous (e.g. wristwatches, bedside alarm clocks). 6.Work with the process owners and payers to develop solutions that improve healthcare, streamline processes and reduce costs.
  52. 52. Thanks! Author: Frank Boermeester About Microsoft Innovation Center Vlaanderen Our mission is to stimulate ICT-related innovation and entrepreneurship in Flanders, with a particular focus on healthcare. We do so by supporting high-potential technology startups. MIC Vlaanderen has two operational offices in the cities of Genk and Kortrijk, Belgium. www.micvlaanderen.be

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