Yaw Anokwa

Evaluation of an Android-based mhealth system for population surveillance in developing countries

OBJECTIVE In parts of the developing world traditionally modeled healthcare systems do not adequately meet the needs of the populace. This can be due to imbalances in both supply and demand--there may be a lack of sufficient healthcare and the population most at need may be unable or unwilling to take advantage of it. Home-based care has emerged as a possible mechanism to bring healthcare to the populace in a cost-effective, useful manner. This study describes the development, implementation, and evaluation of a mobile device-based system to support such services. MATERIALS AND METHODS Mobile phones were utilized and a structured survey was implemented to be administered by community health workers using Open Data Kit. This system was used to support screening efforts for a population of two million persons in western Kenya. RESULTS Users of the system felt it was easy to use and facilitated their work. The system was also more cost effective than pen and paper alternatives. DISCUSSION This implementation is one of the largest applications of a system utilizing handheld devices for performing clinical care during home visits in a resource-constrained environment. Because the data were immediately available electronically, initial reports could be performed and important trends in data could thus be detected. This allowed adjustments to the programme to be made sooner than might have otherwise been possible. CONCLUSION A viable, cost-effective solution at scale has been developed and implemented for collecting electronic data during household visits in a resource-constrained setting.

The PSI Board: Realizing a Phone-Centric Body Sensor Network

When designing a body sensor network, the mobile phone is a natural design point for data aggregation services. However, there is a missing bridge that allows sensors to communicate with existing commercial phones, even if they already possess sufficient storage and processing capabilities. The PSI board is a small expansion module that interfaces body sensor networks with commercially available cell-phones through a standard MMC/SD slot. Adding this expansion capability allows researchers to extend phone devices with additional capabilities, allowing the devices to easily serve as the hub of a wearable body sensor network. The PSI board has an integrated switching mechanism allowing transparent access to an MMC/SD card, an embedded microcontroller, accelerometer, expansion connector, and an IEEE 802.15.4 radio that can connect to a variety of commonly available wireless sensors. The capabilities afforded by the PSI board enable several new applications that would be difficult to implement given the sensors and capabilities currently found in existing cell-phone platforms.

Gesture connect: facilitating tangible interaction with a flick of the wrist

The Gesture Connect system streamlines the process of connecting to and/or controlling objects from a users personal mobile device. Typically, in order to connect two devices together they users must follow a two-step process that consists of first selecting which devices should be connected, and then specifying what the devices should do once they are connected. By combining contact-based connections with gesture-based selection, the Gesture Connect system combines these two steps into a single physical action for simple actions, greatly simplifying the common case. In order to demonstrate and test the underlying concept, a hardware extension comprising Near Field Communication (NFC) and accelerometer capability has been developed for standard commercial mobile phone devices, along with the associated tagging and gesture recognition software. This system greatly reduces overall interaction time for common-case interaction, enhancing the overall user experience.

A User Interaction Model for NFC Enabled Applications

Near field communication (NFC) is a short-range wireless protocol that allows users to connect devices and access content and services by simply holding enabled devices near each other. This paper introduces a user interaction model for NFC enabled applications. Our model specifies that enabled devices take on the properties and context of the objects required in the interaction. This transformation leverages the existing knowledge users have about certain objects and thus can support a number of different applications tied together with simple, intuitive and repeatable interactions. In this paper, we present an overview of the model and the system we have implemented to enable evaluation. We also detail some research challenges we are pursuing

Design of a phone-based clinical decision support system for resource-limited settings

While previous work has shown that clinical decision support systems (CDSS) improve patient care in resource-limited settings, there is little access to such systems at the point of care. Moreover, even when CDSS are available, compliance with care suggestions remain low. In this paper, we use a multi-method approach to document four failure modes that can affect CDSS implementations. Building from six iteratively derived design principles, we describe a phone-based system designed to address these failure modes. Through a formal usability evaluation, we discover six core findings that are important for implementers of mobile systems for health care providers in resource-limited settings.

Reliable data collection in highly disconnected environments using mobile phones

Over four and a half billion people live in the developing world and require access to services in the financial, agricultural, business, government and healthcare sectors. Due to constraints of the existing infrastructure (power, communications, etc), it is often difficult to deliver these services to remote areas in a timely and efficient manner. The CAM framework has found success as a flexible platform for quickly developing and deploying high-impact applications for these environments. Many of the applications built with CAM have relied on a model where a field worker with a mobile phone regularly returns from a disconnected environment to one with connectivity. In this connected state, the phone and a centralized server can exchange information and get the collected data backed up on reliable media. We propose extending CAMs networking model to enable continual operation in disconnected environments. Using a set of heterogeneous paths made available through social and geographic relationships naturally present among workers, we describe a system for asynchronously routing data in a best-effort manner.

Context to Make You More Aware

The goal of our work is to help users make more informed choices about what physical activities they undertake. One example is to provide relevant information to help someone choose whether to wait at the closest bus stop, or walk a few minutes to the next stop, without missing the bus. In this paper, we report on our development of a platform which collects relevant context information for five different scenarios, processes this data, and presents relevant information to the user at the right time, in an unobtrusive way. The personal area network we use consists of a sensor platform with wireless capabilities, a Bluetooth-enabled wristwatch, and a mobile phone. We are also able to communicate with the users PCs and various web services through multiple wireless channels. In future work, we will integrate the scenarios into a customizable set of applications, and evaluate the complete system.

A new generation of open source data collection tools

Organizations in low income regions need tools for collecting and reporting on data. Existing paper-based approaches are often slow and incomplete when compared to data collection tools on mobile devices. In this demonstration, we present the authors Android-based system in addition to broader work by the OpenRosa Consortium - a community dedicated to building open source, standards-based tools for mobile data collection, aggregation, analysis, and reporting.