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Data Driven Healthcare

Given the exponential increase in healthcare costs and steadily aging populations in many nations, organizations are turning to ICT companies to reduce the costs of care. Recognizing these trends, Fujitsu Laboratories of America launched the Data Driven Healthcare (DDHC) Project to research solutions that an ICT company can provide to address these challenges.

The DDHC project is currently investigating multiple problems and designing forward thinking solutions to those problems.

  • As physiological sensors are becoming smaller, cheaper, and more ubiquitous, quantification of a population is now becoming feasible. Multiple streams of data can be used in combination to generate insights that would not be available from analyzing single sensor streams. We are currently researching new methods for gathering, analyzing, and reporting this data.
  • As an increasing percentage of healthcare costs are attributed to chronic conditions and as various endeavors emerge to foster “fee for value,” clinicians are increasingly looking for ways to interact with patients and investigate a patient’s health between clinical visits. To address this challenge, we have developed the required infrastructure and platform for easily collecting and coordinating heterogeneous streams of sensor data. This data and any attendant analysis can then be shared with clinicians in a way that facilitate better collaboration between patients and providers.

The DDHC project has built a mobile, pocket-sized hardware and software platform for continuous monitoring and analysis of heterogeneous sensor streams. It can collect sensor data over multiple wireless and wired channels, process it locally, and display the raw or analyzed data via an onboard web server. Simultaneously, data can also be transmitted in real-time to a patient’s Universal Health Record account. Once the data has reached patients’ records, it is visible to both patients and their respective care providers.

Remote Monitoring PlatformThe platform was created from the ground up to accept input from a wide range of sensors. The current version can connect to various devices such as nasal pressure flow sensors, electrocardiograms (ECG),SPO2 sensors, blood pressure cuffs, and weight scales. Furthermore, the platform is manufacturer-agnostic – connecting to sensing devices provided by many different companies. Last, but not the least, the platform enables the creation of a wide variety of health and wellness apps through continuous real-time access to the sensor data streams stored on the platform.

It is the goal of our DDHC project to give providers and patients the tools necessary to foster the dialog around the continuum of care. Additionally, it is hoped that insights gained from this solution can be applied to better treat the chronic conditions that account for more than 70 percent of healthcare costs.

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More coverage


  1. Ajay Chander, Albert Braun, Rajalakshmi Balakrishnan, Alex Gilman, Stergios Stergiou, Dave Marvit, "A Mobile Platform for Real-time Continuous Monitoring," Fujitsu Scientific and Technical Journal 2014-1.
  2. Stergios Stergiou, Rajalakshmi Balakrishnan, "Streaming Updates for Heart Rate Variability Algorithms," IEEE Transactions on Biomedical Engineering, 2014.
  3. Shreyans Gandhi, Jawahar Jain, "Comparing stress markers across various cohorts in a Mobile Setting," 35th Annual International IEEE EMBS Conference.
  4. "Real-time physiological stream processing for health monitoring services," 15th IEEE Healthcom Conference, 2013.
  5. Rajalakshmi Balakrishnan, Albert Braun, Ajay Chander, Shreyans Gandhi, Alex Gilman, Jawahar Jain, Yasunori Kimura, Dave Marvit, Daiki Masumoto, Stergios Stergiou, "A Day in the Life in the Universal Village: Applications of a General Platform for Continuous Mobile Monitoring," Universal Village Conference, 2013.
  6. Stergios Stergiou, Jawahar Jain, “Manipulating Time-Series Datasets with Binary Decision Diagrams,” International Workshop on Logic and Synthesis, 2012.
  7. Stergios Stergiou, “Implicit Permutation Enumeration Networks and Binary Decision Diagrams Reordering,” In Proceedings of the 48th Design Automation Conference, 2011.
  8. Stergios Stergiou, Jawahar Jain, “Novel Applications of a Compact Binary Decision Diagrams Library to Important Industrial Applications,” Fujitsu Scientific and Technical Journal, 2010-1 (vol.46, No.1).
  9. Stergios Stergiou, Jawahar Jain, “Dynamically Resizable Binary Decision Diagrams,” In Proceedings of the 20th Great Lakes VLSI Conference, 2010.