Category: Data

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Conference Data Wearables

Big Data, AI and personalized healthcare

With the goal of personalizing healthcare, improving outcomes and cutting costs, IBM’s Watson Health will aggregate massive amounts of disparate patient data.  The company has struck deals with Apple, Johnson & Johnson and Medtronic to collect and use more information from devices.

To address privacy concerns, IBM is offering ways to strip personal information from wearables and plug that information into Watson to look for aggregate trends. Its health cloud will  be able to de-anonymize information when needed for doctors to see how to apply a patient’s specific health information to their care.

Wearable Tech + Digital Health NYC 2015 – June 30 @ The New York Academy of Sciences

 

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Asthma Cancer Data Diabetes Heart Parkinson's

ResearchKit can simplify, improve diagnostics

As a company devoted to improving the human condition through health innovation, ApplySci was delighted to hear yesterday’s ResearchKit announcement.  The framework allows people to easily join health studies, and simplifies the process by bringing research to one’s phone.

ResearchKit’s first tests detect Parkinson’s disease, diabetes, cardiovascular disease, asthma, and breast cancer.  Apple worked with 12 institutions to create the app, including some which will participate in ApplySci’s Wearable Tech + Digital Health NYC 2015 conference.

Apple’s (admirable) goal is to more easily recruit research subjects, and improve accuracy by increasing sample size and diversity.  Data is captured and recorded using iPhone sensors.  Examples include:

  • An iPhone’s microphone can detect tiny voice  fluctuations that may indicate Parkinson’s disease.
  • An iPhone’s screen can detect tapping inconsistencies associated with disease.
  • An iPhone accelerometer can compare one’s gait and balance against a healthy person’s speed and posture.

Users control their own data, and decide if, how, and when to share it.   Apple will not have access to it.  The company hopes that external developers will soon dramatically increase the number of tests available.

Wearable Tech + Digital Health NYC 2015 – June 30 @ New York Academy of Sciences .  Early registration rate available until March 27th.

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Apps Data Diabetes Wearables

Apple watch will track glucose

The forthcoming Apple Watch will include the DexCom glucose tracking app.  To use it, a tiny sensor must be placed under the skin to measure glucose levels every five minutes.  Results will be displayed on the watch with a simple graph.

While DexCom has FDA approval, due to recent a recent FDA clarification on wearable devices, other health apps can be included, and this will remain a “Low Risk” device, not requiring prior marketing approval.  This is great news for both device makers and consumers, as it will inspire a proliferation of health apps.  ApplySci hopes that the competition will ensure that the most accurate health trackers become the most popular, and will continue to curate this movement with that goal.

Wearable Tech + Digital Health NYC 2015 – June 30 @ New York Academy of Sciences.

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Apps Data fitness

Apple focuses on digital health

This week, Apple announced its Health app and Healthkit framework in an attempt to standardize and the collection, display, and interpretation of of personal health data.

In a new ad, aired yesterday, the company highlights fitness hardware, including Misfit Shine, Zepp Golf Sensor, Adidas miCoach Smart Ball, Wahoo Fitness Blue and Withings Healthmate, and health apps including Nike+ Running, Strong Lifts, Sprinttimer, Argus and Johnson & Johnson Official 7 Minute Workout App.

“Developers have created a vast array of healthcare devices and accompanying applications – everything from monitoring your activity level, to your heart rate, to your weight, and chronic medical conditions like high blood pressure and diabetes. But up until now the information gathered by those applications has lived in silos,” said Software Engineering SVP Craig Federighi. “You can’t get a single comprehensive picture of your health situation. But now you can with HealthKit.”

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Cancer Data Machine Learning

MD Anderson uses IBM’s Watson supercomputer to accelerate cancer fighting knowledge

http://www-03.ibm.com/press/us/en/pressrelease/42214.wss

Houston’s MD Anderson Cancer Center is feeding IBM’s Watson “cognitive computer” case histories on more than 1 million leukemia patients, along with information about the disease, research and treatment options. Hospital staff and doctors hope it will help guide care and reduce the death rate. They also hope the supercomputer will be able to spot trends missed by researchers, possibly leading to suggestions for new targets for cancer drugs.

The collaboration with IBM is part of MD Anderson’s Moon Shots Program designed to use innovative approaches to fight eight deadly cancers.

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Apps Data Heart mHealth Monitoring Sensors

Elfi-Tech – non-invasive sensor captures more meaningful health data

http://elfi-tech.com

Elfi-Tech of Israel, led by Dr. Ilya Fine,  has disrupted digital healthcare.  They are the only Israeli finalist in the Nokia XCHALLENGE competition, which “envisions a future of access to affordable, personalized healthcare through sophisticated sensing technologies”.  The company has developed a sensor that is more suitable as a continuous monitor with minimal discomfort. This is due to lower power consumption of the laser technology and less of a need to be very tightly secured to skin. Perhaps its most exciting feature is the non invasive measurement of many blood flow parameters, providing a more complete cardiac perspective at home.

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Apps Data Monitoring Wearables

Health tracking sensors embedded in commonly used items

http://teddytheguardian.com/fp-sections/about/

Health tracking technology is becoming increasingly accessible and aesthetically pleasing. Examples include Teddy the Guardian, a cute teddy bear used to monitor children’s health.  It measures a child’s heart rate, blood pressure, oxygen saturation, and body temperature, and sends the data using wireless technologies to a paqrent’s smartphone.  Miniature and advanced sensors will continue to enable product designers to discreetly incorporate vital sign sensing technology into commonly used objects.  We look forward to more developments in this fast-growing segment of the continuous monitoring industry.

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Apps Conference Crowdfunding Data fitness Monitoring Wearables

Angel Health Monitor – Open platform, wearable vital sign sensors

http://www.angelsensor.com/index.html

The Angel Health Monitor is an open platform and SDK that senses motion and acceleration, skin temperature, blood oxygen saturation, and heart rate.  It was created by Eugene Jorov in Israel and will launch a crowdfunding campaign soon.  Developers will be able to use Angel to create apps for iPhone, Android, and other devices that support Bluetooth 4.0. Their SDK, drivers and app templates will be released as open source.

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Apps Data fitness mHealth Monitoring Sensors Sleep Wearables

Home medical device data uploaded to EHRs; patient participation encourages behavior modification

http://www.bostonglobe.com/lifestyle/health-wellness/2013/07/28/century-house-call/tdupWvOQI6b3dKdKcEgdGM/story.html

Boston’s Partners HealthCare has launched a system that allows patients to upload information from their medical devices directly to their electronic records in doctors’ offices.  Patients can regularly use glucometers, blood pressure cuffs, bathroom scales, and pulse oximeters at home, and send the data to their doctors.  Doctors are also becoming increasingly interested in eating habit, movement, and sleep data collected by patients using consumer health-tracking devices.

A recent study by the company showed a significant decrease in diastolic blood pressure among participants who both took their readings and uploaded them to a web interface where they could track and monitor their progress.

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Data Eyes mHealth Monitoring Wearables

Contact lens continuously monitors intra-ocular pressure

http://www.sensimed.ch/en/products/sensimed-triggerfishr.html

The Sensimed Triggerfish combines a non-invasive wireless soft contact lens sensor with an automated system for recording IOP related patterns for up to 24 hours. The ambulatory patient wears the device during normal activity, including sleeping.  At the end of the session, the data is transferred from the recorder to an ophthalmologist’s computer for analysis of the circadian IOP-related pattern.

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Data Heart Machine Learning Monitoring Respiratory

Machine learning in the ICU

http://www.technologyreview.com/news/515461/machine-learning-and-risk-prediction-in-the-icu/

Etiometry is building a clinical-decision support system to interpret large volumes of real-time patient data and guide diagnosis and treatment.  It integrates and analyzes information from heart monitors, ventilators, and pressure sensors and plugs the data into predictive models that have been built on prior patient outcomes.

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Data Longevity

Protective genes vs lifestyle for longevity

http://ngm.nationalgeographic.com/2013/05/longevity/hall-text

Scientists studying longevity have begun using powerful genomic technologies, basic molecular research, and, most important, data on small, genetically isolated communities of people to gain increased insight into the maladies of old age and how they might be avoided.