The Problem:

Pneumonia has been the cause of death for over two million children below the age of five.
Most of these deaths occur in developing nations in South East Asia and Africa.
Delay in diagnosis and lack of continuous monitoring increase the risk and cost of treatment. Early detection and providing timely treatments can reduce the mortality rate of pneumonia .
Community healthcare workers face a huge challenge in assessing and treating children in low to medium income countries.

Existing Systems:

Primary method for diagnosing pneumonia is by assessing whether the child has an elevated respiration rate greater than or equal to 40 breaths/min. The NPB-290 Nellor pulse oximetry device is a low cost stationary pulse oximeter that is currently being used.
For respiration sensing chest based Impedance Pneumography method is used in conjuction with ECG monitoring systems. Nasal thermistor based systems along with Hot wire anemometers have been commercially been used to find respiration rate.

Background:

I, Vignesh am a final year engineering student from Chennai, India. I've always been into biomedical sensing and combining electronics and biomedical engineering.

Inspired after playing Deus Ex: Human Revolution as a 16 year old, My adolescent my mind was blown away by the possibilities in front of me. Reading about the work done by Dr.Hugh Herr at the Biomechatronics lab and Dr.Rosalind Packard at the Affective Computing lab MIT media lab. I realized I wanted to work on wearable sensors, After seeing the unbelievable progress in Machine Learning for the past few years empowering doctors with Machine Learning for diagnostics is my current goal.
Along the way I've read statistics on pneumonia and wanted to do my path, I've also been forming a team to aid us in this.

Solution:

There was a need for an inexpensive yet accurate wearable diagnostic device which can continuously monitor vital parameters like Respiration Rate, Heart Rate, Blood Oxygenation and Body temperature to accurately identify pneumonia and thus enabling timely treatment.
Providing timely aid can make the difference between life or death for the child. Human and monetary resource which is limited in LMIC can be conserved by facilitating remote monitoring, thus enabling healthcare workers to provide better care to the community.

We propose a novel, inexpensive ear-worn device which would noninvasively and nonobtrusively monitor vital parameters like Respiration Rate, SpO2 levels, Heart Rate, Body temperature of a child to enable rapid diagnosis wirelessly.

System Design:

Respiration Rate Sensing:

One of the most frequently used methods to sense breathing pattern is to detect airflow using a nasal thermistor or a thermocouple sensor. We have chosen to use an IR noncontact thermopile array to measure the variation of the nasal temperature accurately using the MLX90614 noncontact infrared temperature sensor(TMP007 would be used in final design) which is pointed to the nasal passage. The sensor is smaller in size and comfortable when compared to nasal thermistors. As the child exhales, the nasal temperature increases which are picked up by the Infrared (IR) temperature sensor. The data is read at high speeds by the Microcontroller over the I2C bus. The sensor also detects ambient temperature which is used for calibration to identify threshold. The samples are compared with each other and the peaks are found. The internal timer is triggered to find the peak to peak time duration from which the respiration rate can be accurately found.

Heart Rate and Blood Oxygenation sensor:

Photoplethysmography (PPG) and Pulse Oximetry (SpO2) are carried out by a single sensor which is used to measure reflectance of three LEDs of different wavelengths. SpO2 is found by measuring the reflectance of 650 nm light in comparison with 940 nm light. Heart rate is measured by PPG wherein the change in blood volume is found by measuring reflectance of 850 nm light. The measurement of vital signs by placing sensors and LEDs behind the earlobe has been validated by previous studies. The Si1141 I2C light sensor( JEElabs Pulse ox sensor) was initially chosen for its availability and good documentation.


I am moving to the smaller Maxim Semiconductors MAX30100 for our next revision to reduce the size, cost. The sensor has an integrated amplifier, Analog to Digital Converter (ADC) and inbuilt LED's and LED drives (940nm,650nm).

Body Temperature sensor:

The body temperature was also measured nonobtrusively by checking the ear canal temperature using the LMT70 temperature sensor. The analog signal is fed to the MCU’s Analog to Digital converter at 1Hz sampling frequency.

We would be going towards a noncontact approach with this too, Similar to the ear measuring temperature sensors that are commercially available now.

Activity and sleep sensing:

An ADXL345 accelerometer is also used to provide activity and sleep data of the child. The technique of actigraphy is used to continuously record the motion data. Activity or inactivity can be quantified and shared with the doctor. Instances of abnormal sleepiness or severe restlessness can be found.

Hardware & Communication:

A powerful STM32F205 microcontroller is used for interfacing various sensors. Sleep modes are used frequently to increase the battery life of the wearable. A Broadcom BCM43438 module is used to provide wireless connectivity to the system and supports both Bluetooth Low Energy and WiFi. Even though WiFi is power consuming, we have used it to directly post the data to the cloud over WiFi in the prototype. The WiFi transmission is done in bursts to conserve battery. A chip antenna was used to give a low profile design to the system. Commercially available components were chosen to design Raksh. The future iterations would use a Nordic Semiconductors nRF52832 BLE Micro controller for its extremely low power consumption and low cost. Further due to the presence of NFC in the MCU, Pairing would be extremely simple even for parents without prior education.

The data can either be transferred through the parent’s smartphone if available or through a dedicated gateway device bundled along with the sensor which would send the data to the cloud over Mobile Networks. Even though the availability of mobile network is limited in very remote areas, Initiatives like the Google Project Loon is likely to expand connectivity to even remote locations around the world.

Power Management & Battery:

A 3.7 V, 240 mAh Lithium Polymer battery is used to power the prototype. A Buck-Boost topology based converter is used to give a clean 3.3 V supply to the MCU and power various sensors. A MCP73831 IC is used for charging the Lithium Polymer battery. It can be powered from a 5 V standard USB wall plug. The future iterations would use a smaller and safer rechargeable coin cell battery such as the LIR2032 with external recharging.

Packaging:

The comfort of the child was a priority while designing Raksh. If the design is obtrusive, the usage will be limited. So Raksh is designed with MCU, wireless unit and battery behind the outer ear helix to provide high degree of comfort. The SpO2 and PPG sensor are gently clamped to the earlobe and the body temperature sensor is integrated with an ear bud like an earphone. The IR non contact temperature sensor is held below the nostril using a semi-rigid cable. This would resemble the microphone used with headphones. The approximate dimension of the device is 40mm x 20mm x 10mm which can be easily placed behind the ear. Length of the cable is 50mm which is adjustable according to the user preference.The system would be extremely inexpensive due to the low Bill of Materials cost and would be light to wear at 38 grams.
Work has been done to get a custom 3d printed enclosure behind the ear and that will be shared here too.

BOM & Weight cost split-up:

Software:

I'm EE student lacking a lot on software and it's been the main pain point of the project.
While I can write some good code for firmware, Cloud and Android dev flies over my head.
That being said, I've posted firmware code on Github for the Particle Photon (Code Compatible with Redbear Duo). While porting some libraries was a pain due to my inexperience, The development was done using Particle Dev.
I will be posting a build instruction for setting up Particle Dev and getting custom libraries up there.
I'm using thingspeak for now due to it's ease of use and it's Matlab compatibility which was essential for performing studies. I'll be moving to mobile based app soon and use MQTT to post to a custom secure server in the future.



Open-Source details:

I've used some open libraries made by others and do not believe that I should own it.
My intention from the start was that Raksh should be open and accessible project. So;

All the software for the Raksh project is copyright 2016 Vignesh Ravichandran , and is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License version 3.For more info see http://www.gnu.org/licenses/

All the hardware for the Raksh project, and the PCB design files and the stl files necessary to produce the hardware are copyright 2016 Vignesh Ravichandran, and are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. For more info see http://creativecommons.org/licenses/by-sa/4.0/