Bitesome Team presents diet and nutrition tracking app at NIH mHealth Technology Showcase

Team Bitesome

The new Bitesome diet and nutrition tracking app was presented at the NIH mHealth Tech Showcase on June 4, 2018.

Part of the NIH MD2K initiative, the Tech Showcase highlighted recent advances in mHealth technologies and methods.

https://mhealth.md2k.org/2018-tech-showcase-home

Our poster illustrated the architecture of our app, and usage of cloud services, and real-time databases specifically, for managing large numbers of users.  We also document our use of food database API for nutritient content information.

Bitesome is currently available for use on the Android and iOS stores.  Visit the Bitesome.mobi website to learn more about the app.

PDF of our poster Research Symposium Poster FINAL_small

 

Bitesome – a new diet and nutrition-tracking app for public health research

Our group is finishing a new diet and nutrition-tracking app called Bitesome.  Similar to the many diet-tracking apps that already exist for smartphones, the new app allows people to track the foods they each. But, somewhat differently, Bitesome tracks numerous factors that help public health and nutrition scientists better understand the context the underlies diet.

Bitesome utilizes sensors on the smartphones to better understand dietary context.  This includes, GPS, motion, and camera data.  Not only can researchers see when and where meals occur, but the nutritional content of each food item, query the neighborhood food environment, observe the physical activity that occurred before and after meals, etc.

Moreover, to better support science, researchers can access real-time Bitesome data from participants enrolled in research studies using a secure web portal.  The website will support researchers by providing data reports for subjects in the study.

Bitesome is currently undergoing testing.  The app will be available for iOS iPhones and Android smartphones in early 2018, starting with deployment in the ENACTS hypertension intervention study in Seattle — a new study funded by the National Institutes of Health, which is focused on minority health disparities.

The new Bitesome app builds upon previous smartphone app development in our research group, including past and ongoing studies that have used our CalFit smartphone app.

 

New center to develop mobile apps to improve Native American cardiovascular health

National Vital Statistics System, CDC, and the U.S. Census Bureau

Hypertension is a leading risk factor for cardiovascular disease, affecting 1 in 3 US adults or about 78 million people. It is very common as well as understudied in American Indians, Alaska Natives, and Native Hawaiians and Pacific Islanders. A new center called Native-Controlling Hypertension and Risk Through Technology (Native-CHART) will bring together academic and community partners, who will conduct research and outreach to improve hypertension in these populations.

Native-CHART is one of two new centers funded by the NIH National Intitutes of Minority Health and Health Disparities (NIMHD) that together will share $20 million over the next 5 years. Native-CHART is co-led by Dedra Buchwald at Washington State University and Spero Manson at the University of Colorado. The center will have broad reach across Native populations, including Satellite Centers in Alaska and the Pacific Northwest, Rocky Mountain, Plains, Southwest, Northern, and Southeast regions.

New technologies will play a key role in Native-CHART, both as tools for research, as well as tools for engaging with groups in the center. For instance, mobile technologies will play a role in collecting objective data on a variety of risk factors including diet, food environments, and physical activity for hypertension.  Dr. Edmund Seto’s group will help develop mobile apps that track aspects of cardiovascular risk for the center.

New Study Predict How Much A Person Will Eat From Smartphone Data

Increasingly smartphones are being used be people to log various aspects of their life. Recently my group published a paper in which we analyzed data from individuals’ smartphones, to see whether we could model their dietary patterns. Rather than compare across people, we focused on the patterns that exist for specific individuals. We examined whether the portion size for each person’s meal tended to followed a routine based on time of day, whether the portion size was related to how much physical activity they engaged in before the meal, or whether the their “food environment” — the quantity, diversity, and types of food establishments around them — influenced the portion size. We also looked at the person’s mood to see it influenced their meals. All of these data were collected from a smartphone app we developed (voice-annotated video recording of meals, accelerometry for physical activity, GPS for food environments, and occasional prompts to ask about mood).

What we found was fascinating. In some cases, certain individuals exhibited fairly routine eating patterns, while for other individuals, exercise before the meal was an important factor in determining their portion sizes. However, we were surprised to find that across all of the subjects, the food environment tended to be an important factor for explaining portion sizes.

This study was based on data from a fairly small group of test subjects who were only monitored over a short period of time, but we now have hundreds of gigabytes of similar data for which we will be doing the same sort of analyses.

The work provides an early glimpse of our ability to integrate various different sorts of sensor, self-report data, contextual data to model specific individuals behavioral patterns.  Moving forward, we are interested in evaluating how well these models work for prediction, and eventual use for tailoring behavioral interventions to specific individuals to help them live healthier lives.

This study was recently published in the journal PLoS ONE: http://dx.doi.org/10.1371/journal.pone.0153085

 

My NIEHS Webinar: Environmental Sensors, Citizen Science, and Quantified Self


On April 5, I gave a webinar “Sensor Technologies for Improving Environmental Health: Juxtaposing the Citizen Science and Quantified Self Movements”.  Thanks to all who attended, and especially to those who provided questions/feedback on my group’s work.  Here’s the abstract:

In recent years, numerous sensor technologies have been developed that offer the ability to collect detailed data on environmental conditions and their impact on human health. These technologies will likely change how communities and individuals access environmental health information, and the amount of data that are available for improved decision-making.

An example of the potential impact of emerging sensor technology can be seen through the development of low-cost direct-reading air pollution monitors many of which are now commercially available.  While researchers continue to conduct studies to answer the fundamental question of “how well do these new devices perform?,” perhaps the more intriguing question is “if useful air pollution data could be obtained from a device that many people could afford, how would this change our understanding of air pollution-related health?”

This webinar will discuss multiple answers to this question, including how community groups, Citizen Science, epidemiologic researchers and individuals may benefit from these new sensors.

One answer to the above question is that community-based environmental groups may have better access to monitoring technologies to document environmental injustices. In some respects, this is not entirely new, as community groups have for many years documented their local knowledge of air pollution levels in much more detail than what was possible through government monitoring efforts. The difference now, is that monitors are more readily available for these groups to collect their own objective measurements. Because of the low cost of each monitor, it is not implausible to imagine entire communities blanketed with a high density of air pollution sensors. And, in fact, NIEHS-funded research is demonstrating that such community-engaged monitoring networks are possible.

Slightly different from the community-initiated and led research described above, new air pollution technologies are enabling a new form of environmental research within our communities, called Citizen Science. While there are different models for conducting Citizen Science, the more intriguing examples are those that are organized over the Internet, involve many individuals who work together to crowdsource data, and result in massive amounts of data that are shared openly. In some cases, technology-savvy Citizen Science leaders are developing and sharing their designs for new monitors, providing proof of concept for how measurements can be made with low-cost sensors.

Another possible answer to the above question is that an increasing number of environmental epidemiology studies may use sensors to conduct personal exposure assessments. Sensors are not only getting cheaper, but also battery-powered and are getting smaller in size, making them increasingly practical for use in a variety of cohort studies. An exciting example of NIH support for this is the new Pediatric Research Using Integrated Sensor Monitoring Systems (PRISMS) program, within which various research groups are developing new wearable sensors that can measure environmental exposures that can be related to health symptoms for future children’s asthma studies. An exciting aspect of the PRISMS program is the recognition that future sensors will likely need to be network-enabled, which would provide more immediate data from research subjects, as well as also enable more immediate feedback to research subjects.

While NIH programs like PRISMS are fostering future sensor technologies for epidemiologic research, the private sector is also commercializing air pollution monitors for the consumer health and wellness market. Smart technologies (e.g., smartphone apps, smart watches, fitness trackers, GPS loggers, etc.) used to be primarily marketed to the Quantified Self movement – individuals who use devices and data to track and optimize various aspects of their life – air pollution monitors being just one of latest devices that such an individual may want to use. But, there is a large group of individuals who have pre-existing health conditions and may be susceptible to air pollution exposures, which may be interested in understanding their air pollution exposures by either having a household or wearable monitor. While these individuals may be the greatest market for these new air pollution monitors, it remains unclear how people will respond to personalized air pollution exposure data (e.g., what are the best ways to communicate individual-based air pollution exposures and risks?), or whether people have practical ways to manage their exposures.

In summary, the recent developments in low-cost air pollution monitoring devices illustrate various opportunities for improving environmental health through sensor technologies. The benefits to traditional community-based and epidemiologic research studies are somewhat clear, with new monitoring devices potentially providing data for more persons, places, and times than previously possible. Less clear, but no less exciting because of the reach and numbers of people potentially involved, are the novel ways in which new air pollution monitors are being adopted into Citizen Science and consumer health and wellness applications.

More, and an eventual link to Youtube can be found here:
https://tools.niehs.nih.gov/conference/exposome_webinar/

New Study to Develop Environmental Exposure Monitoring for Pediatric Asthma

My group at UW was awarded a $2M grant to work with the National Institutes of Health on a new program called Pediatric Research using Integrated Sensor Monitoring Systems (PRISMS).  The goal of this program is the “development of wearable and non-wearable sensors that can monitor pediatric environmental exposures, physiological signals, activity, and/or behavior in a natural environment to gain new insights into environmental determinants of asthma.”

This new grant will bring together researchers at UW in the Environmental Health Sciences, Pediatrics, and Engineering to develop a new environmental exposure monitoring system for PRISMS.  Research partners include Professors Novosselov, Posner, Korshin, Mamishev, Yost and Karr. The study will test the system for use in the HAPI asthma intervention study in Yakima, WA.

Close to 1 in 10 children in the U.S. suffer from asthma.  Children who have asthma are prone to acute exacerbations of airway inflammation (asthma “attacks”) that may be triggered by numerous environmental exposures, including infectious agents, pollens, smoke, mold, chemicals, etc.  The morbidity associated with children’s asthma is large. Asthma is the third most common cause for child hospitalization for those less than 15 years old. It is a leading cause of school absenteeism.  And, there are large public health disparities associated with asthma: those that are poor, and of certain races and ethnicities are more likely to suffer from asthma.  Through the technologies developed in the PRISMS program, improved understanding of the relationship between exposures and asthma symptoms may help researchers and asthmatic families manage the disease better.

 

 

NCI’s RADAR Initiative Will Release Final Report

For the last couple years, the National Cancer Institute at the National Institutes of Health has been working on an important emerging area of health research — how to improve the collection, storing, management, and sharing of data from wearable sensor devices.  Over these last two years, a team of sensor researchers, technologists, and behavioral scientists have been gathering and sharing notes, and coming up with ideas for the future.  Not only does this initiative have relevance for the FitBits, Shines, Jawbones, iWatches, etc. — all those personal fitness devices you and your friends and family are using today.  But, it has the potential to affect how the next generation of devices interact with one another, via their data and metadata, over the Cloud. This initiative is called the “Repository for Algorithm Development in Ambulatory Research — or simply RADAR. Kudos to NCI for kick-starting this effort.

I wasn’t able to make all the various conferences where the RADAR team met, but it was great to be a member of the group, and to interact with the many bright minds on the team.  NCI should be releasing the final report “any day now”.

CalFit EMA — Smartphone-based Ecological Momentary Assessment

CalFit EMA allows researchers to conduct Ecological Momentary Assessments (EMAs) using smartphones.

EMAs are short surveys — a few questions — that occur during random times during the day.  They measure in-the-moment actions, emotions, and location.  The use of smartphones for EMA takes advantage of the fact that many people are already used to and comfortable with carrying their phone, and responding during the day to phone calls, text messages, emails, calendar events, etc.  Mobile EMAs capture what traditional paper questionnaires and direct observation studies cannot because researchers cannot following subjects for long periods of time (and even if they did so they would likely alter the subjects’ behaviors).

CalFit EMA is part of the CalFit system of apps.  CalFit EMA together with CalFit D (a time-location and physical activity tracker) provides rich contextual sensing of an individuals health.

CalFit EMA is extremely flexible.  It has these features:

  • Runs on inexpensive Android 2.3.3+ phones (e.g., ~$130 Samsung Galaxy Y phone).
  • Completely customizable questionnaires.
  • Can be used with or without a SIM-activated Android phone.
  • Using a SIM-activited phone with a mobile data plan allows for real-time data uploading to an Internet server.  If used without a SIM, data are simply stored on the phone’s memory card, and researchers can download the data later.
  • The phone logs times and locations when EMAs are completed allowing for studies of both temporal and spatial contextual factors.

 

 

 

 

 

 

 

 

CalFit EMA was developed by Dr. Seto through a grant from the NIH NIEHS R01ES020409.

If interested in using CalFit EMA, contact Dr. Seto.

mHealth Type 1 Diabetes Study

According to the National Institutes of Health, nearly 26 million people in the U.S. have diabetes (8.3% of the population).  Over 200,000 persons less than 20 years old have either type 1 or 2 diabetes.

Working with the Center of Excellence in Diabetes & Endocrinology (CEDE) in Sacramento (Dr. Prakasam), researchers from UC Berkeley (Dr. Seto) and Aalborg University in Denmark (Dr. Hejlesen and Visiting PhD Student Jensen) are studying the efficacy of continuous glucose monitors (CGMs) among insulin pump users.  In this randomized clinical trial, one group of diabetics will receive regular notifications when their CGMs detect low levels of interstitial fluid glucose versus a comparison group that will not.  Study subjects will be closely monitored using the CalFit smartphone system, which will record their physical activity levels and their dietary intake of carbohydrates.

This study is supported by the Danish Agency for Science, Technology and Innovation (DASTI).

PANDAs in China: Prototype fine particulate matter monitors to study air pollution and obesity

Recently, PhD student, David Holstius and I organized a sensor build, inviting friends from within the EHS program and collaborators from EECS program to make prototypes of a particulate matter air pollution sensor.

The result of this was the creation of 15 monitors that have been shipped to China, where they are being used by Hilary Ong, a UCSF Pediatrics student who I am mentoring to conduct a study of pediatric obesity and its relationship to air pollution exposure.  The study is being conducting in Kunming, where my other PhD student Jenna is doing her dissertation work on food environments.

We’re calling these prototypes PANDAs, befitting their first use in China.  PANDA is an acronym for something I don’t remember.  David has also created a companion software package called BAMBOO that processes data from the PANDAs.  BAMBOO is probably also an acronym for something that I can’t remember.

Stay tuned for the results from our PANDA study.