Mobile Device Biomonitoring to Prevent and Treat Obesity in Underserved Youth
Condition: Obesity
MeSH terms: Obesity
Study type: Interventional

Summary: 
      This project proposes to use mobile devices to develop new tools for pediatric obesity
      prevention and treatment targeting underserved minority adolescent populations at high risk
      for obesity and related diseases. We will use off the shelf, validated and wearable wireless
      sensors to measure physical activity, blood pressure, sleep, heart rate, galvanic skin
      response and blood glucose levels and communicate the measured information to a mobile phone
      using a wireless interface. This will deliver a record of behavior and health data that is
      time-stamped, synchronized, and geographically localized using GPS to a secure server. Data
      will then be analyzed and displayed to participating health professionals to provide them
      with readily interpretable records of continuously monitored energy expenditure, recorded and
      synchronized with other essential biological, behavioral and geographical data. To accomplish
      this project, 50 African American and Hispanic youth (50% female, ages 12-17) will be
      recruited into the research in advisory capacities, to test the sensors during development,
      and to wear the sensors for three non-contiguous weeks. To test the sensors prior to use with
      minority youth, 30 college students age 18 and above will be recruited to try out the sensors
      in and outside of the laboratory in order to make sure that all sensors are in perfect
      working order before testing them in minority youth populations. An advisory group of medical
      professionals will be assembled to guide us through the process of developing a web interface
      that will ensure that the right information will be displayed in an easily interpretable
      fashion. The advisory group will participate in regular meetings to develop and test the web
      interface. Using the data acquired, health professionals will be able to visualize average
      amounts of physical activity, sleep, sedentary behaviors (daily or weekly) as well as daily
      patterns. Average blood glucose, heart rate, and stress levels (daily or weekly) as well as
      daily patterns will also be available. Practitioners will be able to see when and where
      activity and metabolic events are occurring, enabling preemptive and preventive strategies as
      well as targeted interventions to prevent and treat pediatric obesity in underserved and
      at-risk minority youth.
    

Detailed description: 
      Part 1: Developing a Mobile Software Suite for Biomonitoring The software suite proposed in
      this research will be implemented using a three-tier architecture. The front tier of this
      architecture is the data collection sensors coupled with mobile phones that acts as data
      transmission device. The middle tier is a web server that receives and processes information
      and sends it to a back-end database server that stores the information.

      The sensor layer is a collection of off-the-shelf devices that measure the metabolic
      activity. In particular, we propose to use heart rate, blood pressure, and blood glucose
      monitors currently available from Alive Technologies25. In addition to measuring the
      metabolic activity all these sensors are also capable of wirelessly transmitting this data
      over Bluetooth interface. We propose to use feature rich Nokia N95 as the mobile phone
      platform. N95 supports Bluetooth 2.0 +EDR for quick pairing with external Bluetooth sensors,
      and has 3G and WiFi radios for high bandwidth data transfer. All the external sensors listed
      above stream data to the Bluetooth enabled N95 mobile phone. In addition to the high
      bandwidth radio capabilities, the N95 mobile phone platform has a highly accurate built-in
      assisted GPS unit that uses a combination of GPS satellites, cellular tower and WiFi scanning
      to obtain a GPS position lock in less than 10 seconds. The stated location accuracy of GPS
      unit is 30 meters, while in practice the observed accuracy is around 3 meters.

      Part 1a: Testing and Initial Deployment of sensors in target populations: We will use unit
      testing to extensively test our mobile software suite. We will recreate several usage
      scenarios and environmental conditions that our deployment test bed is likely to encounter. A
      total of 50 Hispanic and African American youth will be recruited to assist in technology
      development: 1) an advisory group of 10 youth, 2) 20 youth to participate in laboratory
      testing of the biomonitors and 3) 20 youth to wear the biomonitors and provide data and
      feedback. The advisory group of 5 African American and 5 Hispanic youth will be retained
      throughout the developmental phase to periodically visit our laboratory and test-run the
      sensors (50% female, 12-17 years of age). We will recruit a separate group of 10 African
      American and 10 Hispanic youth (50% female, 12-17 years of age) to participate in idea
      building sessions to ensure that sensors will be attractive and wearable, and to test the
      ease of usability of our mobile software suite. The initial deployment phase includes
      training the children on how to wear and remove the sensors. For laboratory testing of
      sensors, 10 Hispanic and 10 African American youth will spend 3-6 hours wearing the sensors
      and following protocols for walking, sitting, standing and doing various daily activities
      either at Dr. Spruijt-Metz's Physical Activity Observation Laboratory at USC HSA, or to the
      Motion Capture Laboratory at the Viterbi School of Engineering on USC Main Campus. Once the
      software and hardware is determined to be robust enough for deployment we will conduct our
      initial monitoring study with 10 African American and 10 Hispanic youth (50% female, 12-17
      years of age). Children will wear the devices for three periods of one week (7 days), after
      which they will participate in brief individual interviews and surveys to ascertain ease of
      wear and to find ways to motivate and incentivize teens for wearing the sensors. Data
      collected from these weeks of wear will be used for the remaining data analysis and web
      presentation phases of the study.

      Part 2: Data Capture and Transmission to a Back-End Server: We propose t a comprehensive
      mobile software suite that will allow the mobile phone to use Bluetooth to pair with wireless
      monitoring devices to collect vital health and behavioral data along with reading the
      built-in GPS data. The BodyMedia and MemSensse units will provide accelerometry data on
      physical activity and sleep. These measures will be validated in our physical activity lab
      against the Actigraph accelerometer (which has been extensively validated in youth) and
      Continuous Observation using the SOFIT system, a gold standard for physical activity
      measurement in youth 32, 33. By using time stamps the sensor data from Accelerometer can be
      correlated to the vital signs data collected from wearable sensors. We will use the data
      collected from all these sensors to automatically classify the user's activity. In
      particular, the software creates user specific movement signatures to account for differences
      in user's gait, walking/running/bicycling speed, usual route taken between work and home etc.
      The software will be able to use a combination of GPS and accelerometers to recognize the
      differences between driving on road and walking. This sensor information will be recorded
      continuously on the local storage on the mobile phone. For reference, our mobile device
      platform has an 8GB in-built flash memory that can be used for storing sensor information.
      Table 1 shows the approximate data rate of sensors. Using these data rates, we estimate that
      our 8GB local storage can store approximately 1000 days worth of data.

      While data may be stored locally on the mobile phone the real value of our approach is the
      fact that these mobile devices can transmit the sensor information to any remote server using
      cellular data network or even WiFi. The information collected from the sensors in the mobile
      phone is sent to the web server for processing. The web server acts as data integrity manager
      that prevents illegal data read/writes by using simple authentication mechanisms, such as
      personal authentication. The web server utilizes HTTP/SMTP protocol to receive information
      from the mobile phones. The web server also provides web enabled access to the data for
      physician's around the globe.

      Part 3: Simultaneous Data Analysis and Interpretation: The web server sends the data to the
      back-end database server for storing and further analysis of the data. Sensor data is likely
      to be noisy. Therefore, the experts in engineering and pediatric obesity in minority
      populations gathered on this team will work together to create adaptive algorithms to distill
      important health and behavioral information from noisy sensors. The development of such
      algorithms will allow for accurate measurements even when one sensor is not working properly.
      In addition, we shall investigate the possibility of monitoring whether a child is properly
      wearing all sensors.

      3a) Web interface capabilities: What, when and where:

      Using the data acquired, health professionals will be able to visualize:

        -  Average amount of moderate to vigorous physical activity a child is getting (daily or
           weekly), plus daily patterns of exercise

        -  Average number of steps a child is taking (daily or weekly), plus daily patterns of
           steps

        -  Average amount of sedentary behavior a child is experiencing per day or per week, plus
           daily patterns of sedentary behaviors

        -  Average levels of stress or arousal (daily or weekly), plus daily patterns of stress

        -  All patterns of behavioral and metabolic data will be time stamped. Therefore,
           practitioners will be able to see when a child is active, sedentary, stressed, or
           experiencing high blood glucose levels.

      Providing notifications: The final product will be influenced by the advisory group of
      medical professionals that we will assemble. We therefore provide a brief list of examples
      below (thus not an exhaustive list) of notifications that we envision the web interface
      supply to participating health professionals:

        -  Recommendations for physical activity range from 30-90 minutes of moderate to vigorous
           physical activity per day and are somewhat age-specific34. Automated system
           notifications could be generated when average daily physical activity moderate to
           vigorous falls below 60 minutes, and again below 30 minutes.

        -  Recommendations for steps per day are currently 11,000 to 12,000 steps per day for girls
           and 13.000 to 15,000 steps per day for boys. Automated system notifications will be
           generated when children fall below these recommendations. New recommendations for both
           physical activity and steps are expected to be made public soon35. Advances in the field
           will be scrupulously monitored and incorporated.

        -  There are currently no gold standards or threshold measures for stress or arousal in
           youth or in adults. However, Firstbeat technologies
           (http://www.firstbeattechnologies.com/) has been working to develop stress and recovery
           analysis in collaboration with several research projects in the area of stress
           measurement and autonomic nervous system (ANS) function, applying also research in the
           fields of exercise physiology, behavioral sciences, and applied mathematics. We will
           work with Firstbeat to explore development of guidelines for measurement and definition
           of cut-points for stress in youth. We will begin the design of multi-modal signal
           processing algorithms for determining personalized cut-points for individual youths.

      Bio-monitoring for developing interventions and intervention strategies: Because
      practitioners will be able to attach time of day to metabolic and behavioral indices and
      patterns, health practitioners will be able to pinpoint causes and effects as well as develop
      targeted intervention strategies. Furthermore, for researchers, the wealth of time and
      location stamped data will allow for much broader understanding of the effects of the
      environment and time of day of metabolic and behavioral events.

      Part 4: Developing a User-Friendly, Web Enabled and Secure Interface for Health
      Professionals: This part of the research will be ongoing and begin at the onset of the
      project. An advisory team including pediatricians, family doctors, pediatric
      endocrinologists, specialists in pediatric diabetes, African American health outreach
      professionals and promotoras (outreach workers in the Hispanic community) will be assembled
      to guide us through the process of developing a web interface that will ensure that the right
      information will be displayed in an easily interpretable fashion. The advisory group will
      participate in regular meetings to develop and test the web interface. At the onset of the
      project, they will be invited to participate in an idea-building session in order to develop
      specific guidelines for web interface development. Idea-building sessions are one of the
      nominal group techniques that are used to structure small group meetings in such a way that
      individual judgments can be effectively pooled. Typically, four steps are involved: 1) silent
      generation of ideas; 2) group recording of ideas; 3) serial discussion of ideas; and, 4)
      voting to order the ideas as to their salience. Idea writing is particularly helpful in
      developing general ideas into more specific ideas using group interaction. This is also a
      four-step process: 1) organization into small groups; 2) initial written response; 3) written
      interaction; and, 4) analyses and report. Idea writing is an attractive technique because the
      group produces a written product. Analyses of the idea-building data includes recording,
      transcription, and examination of the data for emergent themes. The information from these
      sessions will be used for several purposes: 1) to define the form and content of final data
      that the web interface will provide, 2) to develop a system of notifications or alarms for
      specific metabolic and behavioral values, such as blood pressure that is too high or physical
      activity that is too low as discussed in the previous paragraph, 3) define important pathways
      within the data that health practitioners will need to navigate easily and 4) to ensure web
      interface user friendliness, accuracy and appeal. Ideas will also be generated on use of the
      web interface to develop interventions for the targeted groups immediately and in the future.
    

Intervention name(s): Knowme Device Wear
Intervention type(s): Device
Intervention model: Single Group Assignment
Masking: None (Open Label)
Primary purpose: Prevention
Keywords: Physical activity