Stevens Researcher Wins NSF Grant for Mobile Healthcare Application

Mobile phones are ubiquitous in our society. They are marvels of modern technology, commonly equipped with a dazzling array of high-tech sensors: accelerometers, gyroscopes, GPS, microphones, ambient light detectors, and proximity detectors, just to name a few. In a recent survey, 33% of Americans say they cannot live without them. A smartphone can now serve as a movie theater, jukebox, video game console, and personal assistant, all in one package that fits in a pocket.

Researchers at Stevens Institute of Technology are now making cellular phones personal health consultants as well. Funded by the National Science Foundation (NSF), Dr. Yingying Chen of the Department of Electrical and Computer Engineering is improving consumer healthcare by leveraging the advanced sensors in mobile smart phones in novel ways to provide users with relevant health recommendations that are specifically tailored to them based on automatically collected data. This type of active monitoring and guidance on essential health factors represents an important method of preventative care (i.e. healthcare concerned with prevention of disease). These measures have tremendous potential to improve a US healthcare landscape where costs continue to grow faster than the economy.

“Stevens research is always at the forefront of innovation, leveraging the latest in technology to improve and enhance our modern society,”says Dr. Michael Bruno, Dean of the Charles V. Schaefer, Jr. School of Engineering and Science. “As healthcare costs rise, policy-makers and researchers are increasingly looking to methods of preventative care to alleviate the burden on the economy and healthcare infrastructure. With 35% of American adults owning a smartphone, Dr. Chen’s research in mobile health could improve quality of life for millions.”

Though there are a number of mobile health applications currently available, they all rely on the user to manually enter data to properly function. Research shows it is now possible to infer in real-time a range of human behaviors, allowing users to receive feedback responses to everyday lifestyle choices and better manage their health. For vulnerable populations who may not have the capacity to take care of themselves—such as seniors and children with emotional behavior disorders (EBDs)—and the professionals charged with caring for them, automatic sensor data collection and analysis would be particularly beneficial.

Dr. Chen uses a new and advanced smartphone-enabled social and physical compass system (SENSCOPS) to collect the relevant data. SENSCOPS continuously collects measurements of daily activities. In addition to the sensors built into smartphones, external wearable sensors are used to collect specialized physiological information, such as heart rate, respiratory rate, and temperature.

In order to reduce power consumption and optimize data analysis, SENSCOPS uses a distributed architecture where some functions are performed on smartphones or sensors, and others are carried out by a remote server. The information collected by the sensors is partially pre-processed on the phone, and then wirelessly transmitted via Wifi, cellular networks, or Bluetooth. The data is comprehensively analyzed by the server to infer useful information about the user such as behavioral side effects of certain drugs, environments that trigger certain stereotypical behaviors of children with EBDs, and social interactions in which the user participates. This important information is used to provide feedback to users about further actions they can take to proactively limit activities that may lead to future illnesses or methods of adapting problematic behaviors into socially acceptable responses in the case of children with EBDs.

As modern wireless technology develops, information security continues to be a concern. “SENSCOPS maintains privacy and security by encrypting and storing data collected as secure personal health records in the server,” says Dr. Yu-Dong Yao, Director of the Department of Electrical and Computer Engineering. “Only authorized healthcare providers, such as nurses and doctors, can review the data.”

With the potential to reduce healthcare costs, SENSCOPS has insurance and marketplace potential. Medical costs in 2013 are expected to grow by 7.5%, which is more than three times the projected rate of inflation or economic growth (2.0% and 2.4%, respectively). Methods of preventative and proactive care can therefore provide tremendous value for individuals and society at large. “SENSCOPS allows users to better manage their health using personal feedback provided by mobile applications,” says Dr. Chen. “With medical costs continuing to rise, a smartphone based healthcare system which monitors users’ mental, cognitive, and physical well-being and facilitate early diagnosis of potential illnesses and taking preventive measures is of increasing interest to healthcare providers and insurance companies.”

Dr. Chen is the director of the Data Analysis and Information Security (DAISY) Lab. She is an expert on the use of machine learning techniques and data mining methods to classify and model security, system, network and healthcare related problems. Her research group develops algorithms with an emphasis on system implementation and validation in real-world scenarios. She recently developed a mobile phone application that senses a driver’s cell phone use and intervenes for safety. She and two colleagues received an “Innovator’s Award” from the New Jersey Inventors Hall of Fame for the safe driving application. Dr. Chen’s research is supported by the National Science Foundation (NSF), Army Armament Research, Development and Engineering Center (ARDEC), Department of Defense (DoD), Air Force Research Laboratory (AFRL), and Google, Inc.

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