COSC7388: Advanced Topics in Distributed Computing -- Mobile Computing in Smart Health and Well beings Rong Zheng Associate

Healthcare reality in US  25.8 million children and adults in the United States—8.3% of the population—have diabetes  0.26% of population 20 years of age or under  People 65+ represented 12.4% of the population in the year 2000 but are expected to grow to be 19% of the population by 2030 (Administration of Aging)  the United States spent $7,146 on health care per capita and 15.2% percentage of its GDP (WHO)  195,000 Americans die a year due to preventable errors (HealthGrades, 2004)  Life expectancy at birth in the USA, 78.49, is 50th in the world

Needs for better health delivery Overarching goal: Optimized care decisions by bringing all relevant evidence pertaining to the particular patient to the point of care anywhere and anytime and in user-appropriate forms for all members of the care team  Normalization and harmonization of electronic health records (HER)  Extraction and representation of data, information, and knowledge from diverse unstructured sources  Frequent and large-scale data collection and predictive modeling

Paradigm shifts Involvement and enabling of individuals to participate in their care  From reactive to preventive  From clinic-centric to patient-centric, and  From disease-centered to wellness centered

High penetration rate of mobile devices  64.7% of world population subscribe to mobile phone services in 2012 (wikipedia) 1 China 1,046,510,000 1,341,000, June India 934,094,206 1,211,929, June US 327,577, ,866, June Brazil 254,948, ,379, June Indonesia 250,100, ,556, May Russia 224,260, ,905, July Japan 121,246, ,628, June Pakistan 119,860, ,854, May Germany 107,000,000 81,882, Nigeria 101,271, ,000, May 2012

(Mobile) networking technologies in healthcare Sensing  Ubiquitous health data collection  Continuous sensing of physiological information  Monitoring of dietary behavior and activities Diagnosis and care delivery  Access of information at point of care  Cloud-assisted modeling and assessment  Early detection  Social networks  Patient & physician support group  Epidemic disease detection and modeling In home care In-hospital care

Scope of the class  Science and engineering side  Wireless technologies  Sensing technologies  Mobile platform programming (Windows Mobile 7, Android)  Cloud  Software engr. practice  Medical side  Viewpoints from medical practitioners  Case studies

Course format  Lectures  Guest lectures  Survey presentation  Project discussion and presentation

Semester-long Project  Innovative idea needed  Preferably decease-oriented  Survey to understand the state of the art  Design of experiments early on  Processing and interpretation of data  Oral presentation and written report  Use of SVN for code maintenance

Tentative Schedule DateTopicLecturer 08/27IntroductionRong Zheng 09/03Labor day holiday 09/10Window Mobile 7 programming/cloudHuy Nguyen 09/17Wireless standards related to medical applicationsRong Zheng 09/24Sensor design for medical devicesLuca Pollonini 10/01Resource-efficient activity recognition and monitoringRong Zheng 10/08Android programmingKhuong Vu 10/15Survey presentation & project proposalStudents 10/22Social networking in healthcareRong Zheng 10/29Home monitoring and care for cardiovascular diseasesCliff Dacso 11/05Privacy and security issues in healthcareRong Zheng 11/12Safety and compatibility of RF enabled medical devicesDavid Nghiem 11/19Case study in assisted livingRong Zheng 11/26TBD 12/03Final project presentationStudents