Mobile phones assisting with health self-care: a diabetes case study

ABSTRACT

The applicability of pervasive and mobile computing in the health care sector is beyond dispute. This paper explores the use of the mobile phone as a tool for personalized health care assistance for individuals diagnosed with diabetes. By monitoring user location and activity on the mobile phone, recognizing past behavior and augmenting the logging of blood glucose levels with context data, our prototype application assists with taking well-informed decisions on daily drug dosage to achieve and maintain stable blood glucose levels. Evaluation of the prototype application indicate that a brief training of the application suffices to capture patterns in the user's relevant context that simplify glucose level trends analysis. We describe some of the details of the user study and the prototype application, and conclude with plans to investigate context-driven activity prediction to further improve the decision support for the user.

REFERENCES

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.1 MODELS AND PRINCIPLES
      H.1.2 User/Machine Systems
          Subjects: Human information processing

Additional Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS
      H.4.2 Types of Systems
          Subjects: Decision support (e.g., MIS)

  J. Computer Applications
  J.3 LIFE AND MEDICAL SCIENCES

General Terms:
Algorithms, Human Factors, Management

Keywords:
activity recognition, health care, location awareness, mobile computing