Aly: A scalable remote monitoring system

We propose Aly, an ally for chronic patients, families, health care systems, government, and researchers in three in house implemented prototypes to be a wearable device, a mobile application, and a platform that act coordinately to acquire, monitor, and analyze vital signs and symptoms to predict and prevent infectious diseases. Aly is a service based on well-being, where all the agents involved can substantially improve their performance executing their role. For example, users can keep a rigorous follow-up of their health states and know when they go out of range. Also, doctors can better understand health states being allowed to predict evolution. The organizations can make critical decisions based on predictions thanks to the algorithms developed by Analytics. 

Aly wants to foster centralized data acquisition, families and health care systems monitoring, analytics for decision making, and government public policies implementation. This lack of centralized systems causes delay in patients' diagnosis, earlier spread of infectious diseases, and once patients are diagnosed health care systems spend more resources, hospital capacity in giving treatments to advanced patients. Therefore, the government has a need to better monitor patients at earlier stages of contagion and have an input to anticipate populations contagion and then generate on time policies to prevent outbreaks. 

Aly has a pilot using SARS-CoV-19 in low income countries, where the pilot test is about to be performed. COVID-19 in Colombia has reported up to 67.000 Deaths in 2020-2021 and up to 3 million deaths over the world, occupying even 95% of the bed capacity in the largest cities such as Bogotá and Medellin with patients in an advanced state of the disease. Actions taken by governments about quarantines present a lack of updated information and predictive strategies to control population´s behavior to reduce outbreak contagion rates. Thus, remotely monitoring with Aly can foster on time disease diagnosis, augment hospitals capacity and monitoring systems,  and government inputs can be improved.

That is Aly, the response to a complete integrated approach to cover, monitor and analyse people's health. Aly is composed of three products designed to be scalable and developed in local collaborations at the host organization and in further with international and government institutions. At first, a low cost high precision wristband, in charge of measuring vital signs (temperature, heart rate, oxygen saturation, respiration rate) and sending data. The second product is  mobile application in charge of receiving data, store users profile, and periodically send both symptoms and signs to a database, to make sure users  can monitor their data and trigger actions they consider or actions we recommend in function of and algorithm trained with Covid&Non-covid patients, its results and the risk assessment we provide.

Finally, a third product is under development, which is a react web platform for doctors and policy makers in order to monitor specific patients or consult aggregated anonymized data for decision making respectively. . Patients can monitor their own values, doctors can monitor values remotely,  report visits, advice and suggest patients to visit the hospitals. Finally policy makers would have the possibility to see aggregated and anonymized information given a region about demographic data.

Our solution address solutions of the following users:

• 18+ Patients with COVID-19  comorbidities reported by the world health organization at https://www.who.int/docs/default-source/ncds/un-interagency-task-force-on-ncds/uniatf-policy-brief-ncds-and-covid-030920-poster.pdf?ua=1. Aly delivers  our wristband, instructions and access to Aly mobile application. They can monitor they vital signs and have a digital record of the different variables for autonomous decision making. Additionally, they can consult the automatic computation of COVID-19 risk and doctor´s advice. 

• Private and public health care providers: In Colombia, once we finish tests of our prototype, we will meet with Compensar, a private health care provider and Secretarias de salud, to present and evaluate the possibility to use Aly at their Institutional Health Service Providers, so doctors can monitor patients, have inputs for decision making and have a way to communicate with their patients. 

• Government and researchers would get benefited by having access to the aggregated data of all the users to monitor population health and evaluate if designed interventions have a positive result. 

Our decisions are supported by the research director of the School of medicine, who has led a communication with patients at Fundación Santafé in Bogota and Secretariat of Health doctors and executives.

Aly is in charge or Strengthen disease surveillance, early warning predictive systems, and other data systems to detect, slow, or halt future disease outbreaks. Disease surveillance is related to reducing diagnose time and then evolution of the disease by usign our alarm generation and real time monitoring. The early warning predictive is related to monitoring, assesing risk and suggesting behaviors to the different patients by using the three products described in our approach.

The three mentioned products are under development at Universidad de los Andes. We have two wristband prototypes using arduino based architecture and a microcontroller version is under development in a modular approach. There is a communication BLE module, whose performance is measured when UART communication is tested at 230400 baud rates. The power system guarantees 3.3V at 200mA and the PIC16F18345 manages Max 30102 and Max86150 temperature and pulse-oximetry measurements respectively.  firmware is under tests. 

The react native application is a full functional prototype that has BLE interaction. Performance of the app is measured when data coming from the wristband and data acquired in the app prototype are  stored in the Database. 

The web platform successfully retrieves information from the database and lets users and doctors retrieve data and trigger a logistic regression algorithm to assess the level of risk of covid 19. Government aggregated visualization is under development. 

Ally is a system solution where all users benefit from its implementation since it considers the information in various moments, past, present, and future. Thanks to the fact that first, we identify the needs of our target population, we understand and then develop the relevant knowledge to solve the problem we are remembering, identifying failures and desires of the health service, as its step by step to provide the service determining our value proposition to execute with a clear objective. Therefore, we aim to speed up the paperwork to save lives, generating predictions to make decisions involving many real people, governments, public and private companies, such as oil companies, health insurers, as a few examples.

Our plan to measure and monitor the success of our Aly implementation is to use KPIs that show us two main things. 

• One, how easy it has been to articulate the existing system with our proposed technology.

• Two, the level of resources saved thanks to our system. Letting us understand resources such as time, energy, infrastructure, and personnel.

The first can be executed by a series of questions to the different users when operating some visualization action. If they wish, have an open response area where they can make recommendations that we can fix for the next version of the platform. We understand that it is always the service in constant evolution, as Windows, IOs, or the Adobe suite, to name a few examples.

The second, we as developers need a monitor that constantly tells us if our algorithms provide relevant information about saving resources for the different actors. Thus, we show which ones do not meet the expectation level, allowing us to improve the algorithms continuously.

Aly is conformed by 12 undergraduate level students, 3 Msc students, 2 PhD students and 4 faculty professors. Aly is an interdisciplinary project. Its members belong to Engineering school, Design and architecture school and School medicine.

The Biomicrosystems group, leaded by the Associate Professor Johann Osma (jf.osma43@uniandes.edu.co) , will help to work with two PhD students who work in biosensors and flexible electronics (Miguel Aroca ma.aroca@uniandes.edu.co and Crhistian Segura cc.segura@uniandes.edu.co ).. They will provide their experience and material gotten from the Instrumentation and Biomicrosystems courses given by the IEEE department.  

The Social and health complexity center, leaded by the Associate Professor Felipe Montes (fel-mont@uniandes.edu.co ), will help to develop the data analysis component using the material and knowledge gotten from previous collaborative work with the Massachusetts institute of technology (MIT) in visualization tools and regional data processing.  

In 2021, Professor Jorge Luis Hernandez, research director of Medicine School at Los Andes University, started supporting the team and included Martha Estrada, a public health Master´s student to develop a Thesis in a pilot patients study with the device when it´s finished. 

 The Professors Giovanna Danies (g-danies@uniandes.edu.co ) and Carolina Obregon  (c.obregon101@uniandes.edu.co ) led the design and consumer oriented design of the system, including this project in the biodesign challenge course given by the School of Design and Architecture.