IBM and EarlySense Use Big Data to Help Improve Sleep Patterns and Promote Good Heal
13/03/2014
New global trends are driving the importance of wellness services, including an increasing population of the elderly and overloaded medical systems. Recent consumer studies indicate that revenue from wellness software, services, and products is expected to reach $8B in the United States by 2018 (CEA Whitepaper on Connected Health and Wellness Market).
The research prototype being demonstrated collects data from EarlySense's Wellness solution, which uses a contact free sensor placed under any standard mattress. During sleep, the sensors communicate wirelessly with smartphone and tablets to offer information such as sleep analysis, recording heart and breathing rates and patterns. It can also offer trending graphs, as well as an evaluation of restlessness and stress levels for personal use at home.
Heart and breathing rates, as well as our sleep efficiency, especially when tracked over a period of time, can tell us a great deal about how healthy we are, said Guy Meger, VP of R&D EarlySense. The EarlySense Wellness solution, based on the company's experience in the hospital environment and over 5,000,000 hours of cumulative patient monitoring, is intended for individual use at home and is a natural fit for Big Data analysis.
Sleep well, live well helping people reach their optimal physical and emotional states has become a vital step in helping to prevent illness and the need for treatment, noted Aya Soffer, Director of Big Data Analytics for IBM Research, and senior manager of Cognitive Solutions at IBM Research Haifa, where the platform was developed. The next step would be to introduce cognitive algorithms into the platform so the system can help a person learn what might indicate a potential wellness concern such as sleeplessness.
Mobile and sensor technologies are revolutionizing our personal lives and opening new opportunities for supporting healthy life styles. The IBM research platform can also use anonymized data from wellness sensors for further management, analysis and consumption. The open and standards-based platform combines the scale and robustness of IBM Big Insights, InfoSphere Streams, Netezza for data warehousing and Cognos for data intelligence, with analytics from IBM Research and EarlySense's wellness sensing technology.
The IBM platform can examine anonymized data offline to help discover patterns in local regions. For example, a very large number of people suffering from respiratory problems in a certain neighborhood could indicate a rise in air pollution. The IBM analytics could be used to identify where population-based data deviates from the norm captured by wellness sensors, or could be compared with data to aid in understanding trends in disease patterns.
Using the analytics provided by the IBM solution, organizations or municipal bodies could gain statistical insight into the overall health status of their communities. The prototype solution is designed to be consent-based with the data collected only on an opt-in basis, so a municipality can elect how to use the solution with its local population. The solution, which works with anonymized and de-identified data, could also provide analysis of trends in organizations or regions.
The IBM research platform for Big Data wellness is being demonstrated at CeBIT 2014 in Hanover, Germany. As part of the demo, visitors are invited to check their own heart rate, breathing rate motion and sleeping patterns. This information is collected and displayed on a centralized monitor and then compared to other volunteers' information collected during CeBIT.
The IBM prototype solution and the EarlySense wellness system is not intended for medical use.
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