A multimodal framework for extraction and fusion of satellite images and public health data.

In low- and middle-income countries, the substantial costs associated with traditional data collection pose an obstacle to facilitating decision-making in the field of public health. Satellite imagery offers a potential solution, but the image extraction and analysis can be costly and requires specialized expertise. We introduce SatelliteBench, a scalable framework for satellite image extraction and vector embeddings generation. We also propose a novel multimodal fusion pipeline that utilizes a series of satellite imagery and metadata. The framework was evaluated generating a dataset with a collection of 12,636 images and embeddings accompanied by comprehensive metadata, from 81 municipalities in Colombia between 2016 and 2018. The dataset was then evaluated in 3 tasks: including dengue case prediction, poverty assessment, and access to education. The performance showcases the versatility and practicality of SatelliteBench, offering a reproducible, accessible and open tool to enhance decision-making in public health.

Multi-Dimensional Dataset of Open Data and Satellite Images for Characterization of Food Security and Nutrition.

BACKGROUND: Nutrition is one of the main factors affecting the development and quality of life of a person. From a public health perspective, food security is an essential social determinant for promoting healthy nutrition. Food security embraces four dimensions: physical availability of food, economic and physical access to food, food utilization, and the sustainability of the dimensions above. Integrally addressing the four dimensions is vital. Surprisingly most of the works focused on a single dimension of food security: the physical availability of food. OBJECTIVE: The paper proposes a multi-dimensional dataset of open data and satellite images to characterize food security in the department of Cauca, Colombia. METHODS: The food security dataset integrates multiple open data sources; therefore, the Cross-Industry Standard Process for Data Mining methodology was used to guide the construction of the dataset. It includes sources such as population and agricultural census, nutrition surveys, and satellite images. RESULTS: An open multidimensional dataset for the Department of Cauca with 926 attributes and 9 rows (each row representing a Municipality) from multiple sources in Colombia, is configured. Then, machine learning models were used to characterize food security and nutrition in the Cauca Department. As a result, The Food security index calculated for Cauca using a linear regression model (Mean Absolute Error of 0.391) is 57.444 in a range between 0 and 100, with 100 the best score. Also, an approach for extracting four features (Agriculture, Habitation, Road, Water) of satellite images were tested with the ResNet50 model trained from scratch, having the best performance with a macro-accuracy, macro-precision, macro-recall, and macro-F1-score of 91.7, 86.2, 66.91, and 74.92%, respectively. CONCLUSION: It shows how the CRISP-DM methodology can be used to create an open public health data repository. Furthermore, this methodology could be generalized to other types of problems requiring the creation of a dataset. In addition, the use of satellite images presents an alternative for places where data collection is challenging. The model and methodology proposed based on open data become a low-cost and effective solution that could be used by decision-makers, especially in developing countries, to support food security planning.

A method for mapping regional oxygen and CO2 transfer in the lung.

This paper presents a novel approach to visualizing regional lung function, through quantitative three-dimensional maps of O2 and CO2 transfer rates. These maps describe the contribution of anatomical regions to overall gas exchange and demonstrate how transfer rates of the two gas species' differ regionally. An algorithm for generating such maps is presented, and for illustration, regional gas transfer maps were generated using values of ventilation and perfusion imaged by PET/CT for a healthy subject and an asthmatic patient after bronchoprovocation. In a sensitivity analysis, compartment values of gas transfer showed minor sensitivity to imaging noise in the ventilation and perfusion data, and moderate sensitivity to estimation errors in global lung input values, chiefly global alveolar ventilation, followed by cardiac output and arterial-venous O2 content difference. Gas transfer maps offer an intuitive display of physiologically relevant lung function at a regional level, the potential for an improved understanding of pulmonary gas exchange in health and disease, and potentially a presurgical evaluation tool.

The hackathon model to spur innovation around global mHealth.

The challenge of providing quality healthcare to underserved populations in low- and middle-income countries (LMICs) has attracted increasing attention from information and communication technology (ICT) professionals interested in providing societal impact through their work. Sana is an organisation hosted at the Institute for Medical Engineering and Science at the Massachusetts Institute of Technology that was established out of this interest. Over the past several years, Sana has developed a model of organising mobile health bootcamp and hackathon events in LMICs with the goal of encouraging increased collaboration between ICT and medical professionals and leveraging the growing prevalence of cellphones to provide health solutions in resource limited settings. Most recently, these events have been based in Colombia, Uganda, Greece and Mexico. The lessons learned from these events can provide a framework for others working to create sustainable health solutions in the developing world.

DISEÑO Y CONSTRUCCIÓN DE UN PEDAL DE BICICLETA BASADO EN SENSORES PIEZORRESISTIVOS PARA DETERMINAR LA FUERZA RESULTANTE

En el ciclismo colombiano, las pautas de entrenamiento se ajustan a partir de datos cualitativos basados en la observación directa al deportista. Esta investigación busca mejorar ese proceso por medio de la implementación de pedales instrumentados para obtener datos cuantitativos del rendimiento del ciclista. En este artículo se presenta el diseño y construcción de un prototipo de dispositivo dinamométrico que permite la captura de datos de fuerza en el pedal durante el gesto del pedaleo. El dispositivo funciona con base en un sensor de fuerza piezorresistivo (FlexiForce®) acoplado a un arreglo mecánico específico y a un sistema de acondicionamiento de señal que entrega un voltaje proporcional a la fuerza ejercida, cuyo registro y análisis se realiza por medio de LabVIEW TM. El dispositivo permite visualizar la fuerza del pedaleo en tiempo real.

In the Colombian cycling, the training guidelines are adjusted from qualitative data based on the direct observation of the sportsman. The aim of this research was to improve this process by the implementation of instrumented pedals to collect quantitative data of the performance of the cyclist. In this article we present the design and construction of a prototype of a dynamometric device that allows the acquisition of force data in the pedal. The device works based in a piezoresistive force sensor (FlexiForce®) connected to a specific mechanical adjustment and a signal conditioning system that gives a proportional voltage to the exerted force, whose registry and analysis are made in LabVIEW TM. The device allows the visualization of the pedaling force in real time.