We empower middle to high school students to perform malnutrition assessments in their own communities by equipping them with an easy to construct, accurate, and robust malnutrition assessment tool.
What is it?
We empower middle to high school students to perform malnutrition assessments in their own communities by equipping them with an easy to construct, accurate, and robust malnutrition assessment tool (RMAT). Our idea is to then utilize a synergistic incentive structure between educational and community healthcare systems in order to accelerate the reach of malnutrition assessments and the pace of patient referral for malnourished children and pregnant mothers.
How is it used?
The current version of the Veriband RMAT is carried by the assessor and is looped onto the left mid upper arm of the patient being assessed. The envisioned Veriband will be able to be worn on the wrist by the assessor when not in use. When not in assessment mode, the band can be used as a wristwatch by toggling a mode switch.
What technologies does it incorporate?
The Veriband RMAT incorporates a linear potentiometer to measure circumference via displacement of the band, a tactical button to assess proper tension, a robust wristband, LED indicators, a PCB and a microprocessor. It is charged via micro-USB, the same charging source as used in smartphone and feature phones. The data processing portion includes QR coded business cards, smartphones, and a more open source backend processing system that utilizes Amazon Web Services and Google Maps.
How does it work?
First, the assessor will toggle the band to either maternal or child setting to ensure the microprocessor is set to the correct MUAC threshold. Then, a given patient will place his/her arm through the pre-looped band. Subsequently, the assessor will grip the slider portion of the RMAT body and pull on the back of the band until the loop fits snug around the patient’s arm. When the band is pulled completely, the patient’s mid-upper-arm will touch an easy to depress tension button, triggering the device to digitally record and dislay the circumference and also display an indicator on a red / yellow / green continuum bar depending on the patient’s risk for malnutrition. This design addresses several shortfalls of the current paper MUAC. When using the RMAT, the assessor will not be reading measurements as the band is being pulled, thus effectively removing any form of digit bias. Also, the rate at which the band is pulled does not affect the recorded measurement because the part of the device that triggers the measurement is not the band itself, but rather the trigger button at the patient facing side of the sliding portion, thus removing any tension bias. The continuum bar will provide feedback on how to close to malnourished a patient is. This feature will be useful in the case that a child or pregnant mother is not malnourised but needs to be aware that they may need to make changes to their diet or rest more. We are designing the casing, PCB, and band to be modular and easy enough for a student to assemble.
Video of Prototype A1 showing measurement mode proof of concept
Who uses it?
The Veriband Rapid Malnutrition Assessment Tool (RMAT) will be delivered to secondary schools in the form of educational build kits. These kits will contain all the necessary components needed to construct the tool so that all students would need to do is solder several key components and then apply screws to the casing. A quality test for the tools will be included before use in the community. Teachers will be given an educational module to teach the basics of electronic theory and soldering as well as the effects of moderate and severe malnutrition (yellow and red RMAT MUAC reading) on children as well as the impact of malnutrition on a woman’s pregnancy (i.e. her baby’s subsequent birth weight, nutrition status, and mortality risk). Since female students at these age levels in developing countries are approaching the age when pregnancy is common, this educational intervention is a preventative measure when it comes to maternal malnutrition.
Next, a reward system will be set up through a one semester collaboration with local primary healthcare centers. Each student will be given a set of printed business cards with QR stickers which have encoded their name, class, and school. When students go out in the community and diagnose a child ages 6-24 months with moderate or severe acute malnutrition (SAM) using the Veriband or a pregnant mother with a higher risk of a low birth weight delivery ( MUAC<28.5 cm), they will give one of their personal business cards to the guardian of the child (or directly to the pregnant mother) and suggest bringing the child into (or having the pregnant mother visit) the nearest participating primary health center . Participating health centers will be aware of the referral system for malnourished children and expecting mothers. The use case for a child is as follows, with the same process for pregnant mothers implied: when the guardian brings the referred child to the doctor, the doctor will verify the malnutrition diagnosis using a Veriband reading, look for the presence of bipedal oedema, as well as observe weight for height. Following the seminal suggested method of Myatt, Khara and Collins in their 2005 technical background report “A review of methods to detect cases of severely malnourished children in the community for their admission into community based therapeutic care programs,” if the diagnosis is confirmed through either MUAC, MUAC+bipedal oedema, or weight for height, then the doctor will take the QR code sticker off the business card and place it on a sheet containing correct diagnoses, indicating the severity of the malnutrition. If the diagnosis is not confirmed, then the sticker will be taken and placed on another sheet containing incorrect diagnoses. On a weekly basis, program administrators will ensure that the healthcare centers have batch scanned their correct and incorrect diagnosis sheets using smartphones, and the data is uploaded to a central score database utilizing Amazon Web services and Google Maps. Each correct diagnosis will count as one ‘point’ for the student. Statistics will be announced monthly with updates on which individual, class, and school has performed the most correct diagnoses. This type of intra contest feedback will be vital to show students what kind of results their efforts are producing and can inform subsequent classroom and school strategies in order to outperform other classrooms and schools in the district. At the end of the fourth month (end of an effective semester of schooling), rewards will be given to individual students, classes, and schools which have reached certain point thresholds as well as the student, class, and school which accumulated the most points. The scale of this incentive system is hypothesized to work best on a district level in order to optimize coverage area, and our ideal target sites are the Pokhara valley of Nepal, the Bihar region of India, or certain pending regions of Nigeria to leverage the existing on the ground networks with our collaborators at Valid International and Doctors Without Borders. It is noted that the programmatic portion of this initiative specifically targeting antenatal care visits for pregnant mothers is separable and scalable in communities practicing Basic Emergency Obstetric and Newborn Care (BeMONC). Our project lead has worked closely on obstetric needs mapping in the area of vacuum assisted deliveries and prolonged labor with Jhpiego, which is a USAID leader in adminstering BeMONC globally.
Why does it help?
The Veriband RMAT device will remove the aforementioned tension and digit bias issues, while fostering community awareness and buy in to assess malnutrition and promote good nutrition for the pregnant mothers and children under the age of five (and especially the age of two) who are most susceptible to deleterious effects. The assessment data can be stored onto the cloud in order to aggregate data each week (or more frequently) in order to provide a centralized location for healthcare centers and NGOS to visualize the areas of greatest need. Furthermore, by involving local schools and students in the building of the Veriband kits, we are organically integrating our technology into our target communities, as opposed to relying on non-profits solely to drive adoption.
Aaron Chang, John Bacon, Seal-bin Han, Ravi Gaddipati
Diagnosis/Treatment/Referral, Behavior Change
Health, Education, Nutrition
These pages have been pulled directly from applications submitted to the Wearables for Good Challenge in 2015. They represent the work of the individual teams and have subsequently not been edited.