The Impact of Wearable Devices and Big Data on Health

Mobile technology has been one of the largest contributors to big data for the past several years. Proliferation of mobile phones, the implementation of app-enabled smart phones, and now the growth of the wearable device market are all creating massive new data flows that can be put to use for health and other purposes.

One of the more interesting developments in this space is Apple’s ResearchKit – an open-source software framework launched by Apple in March 2015 that allows use of iOS devices to collect data for use in medical research and diagnostic apps. The goal is to not only make it easier to do medical research, but also to more effectively track patients and their activities using always-on medical devices.

Just last week Apple discussed the next step with ResearchKit and its sister product, CareKit. The newest updates will allow genetic data and medical test results to be combined with other data in the research context. The sheer volume and accessibility of the iPhone user base means these tools are powerful resources for medical studies. CareKit will allow users to share gathered research with their loved ones and healthcare providers, in addition to researchers.

Here is Apple’s video from that event describing the effectiveness of ResearchKit and their next steps:

Uses of ResearchKit in Medical Applications

In just under a year, the ResearchKit toolset has been used in several applications in the medical field. Two of them include:

  • mPower Parkinson’s Disease App – Launched by nonprofit research organization Sage Bioworks, the mPower Parkinson’s Disease app is part of a study that collects data on things like balance, speed of walking, and general dexterity from iOS accelerometer and other sensor data. More than 14,000 people signed up for the study in 2015 alone, making it one of the largest Parkinson’s studies ever conducted. This team will be developing a new CareKit app allowing users to share the research data with their caregivers.seizureapp
  • EpiWatch Epilepsy Tracking AppJohns Hopkins University created the EpiWatch application to gather data before, during, and after epileptic seizures. The app works with an iPhone and Apple Watch to gather this data from participating users. With the heart rate monitor in the Apple Watch, the app can collect this information, along with use of memory games and other activities that provide vital information about patients who suffer from epilepsy. Researchers at Hopkins hope to use the data they are collecting to eventually predict (rather than just report) seizures and related activities.

These two apps are among the first to tap into the powerful nature of ResearchKit. Connecting the iOS platform, and its hundreds of millions of active users, to medical researchers creates new opportunities to collect data that would never be possible otherwise. What once might have taken years and required careful validation and reporting that wasn’t always accurate, can now be done more broadly and accurately, and with minimal work required from the patient.

The Future of Wearable Devices and Big Data in Health

Wearable medical devices are not new, but they have long been expensive and not always viable for every patient or subject of a medical study to wear. That’s why the growth of the wearable personal electronic device market – and the lower prices that come with a higher volume of devices being sold –  is such a potentially game-changing moment for big data in the health industry.

As costs continue to drop, and functionality expands, the benefits to medical researchers – and to their patients – will continue to expand.

To learn more about how big data has become such an important tool and is currently being utilized in the health industry, download our white paper, Big Data and Health from the button below:

Report: Big Data and Health

We have more data than ever before. Nowhere is this more evident than in the health industry, where big data and the smarter technologies tapping into it are enabling rapid change and helping with outbreak controls, data tracking, and medical research.

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