A Cross-Lingual Mobile Medical Communication System Prototype for Foreigners and Subjects with Speech, Hearing, and Mental Disabilities Based on Pictograms

People with speech, hearing, or mental impairment require special communication assistance, especially for medical purposes. Automatic solutions for speech recognition and voice synthesis from text are poor fits for communication in the medical domain because they are dependent on error-prone statistical models. Systems dependent on manual text input are insufficient. Recently introduced systems for automatic sign language recognition are dependent on statistical models as well as on image and gesture quality. Such systems remain in early development and are based mostly on minimal hand gestures unsuitable for medical purposes. Furthermore, solutions that rely on the Internet cannot be used after disasters that require humanitarian aid. We propose a high-speed, intuitive, Internet-free, voice-free, and text-free tool suited for emergency medical communication. Our solution is a pictogram-based application that provides easy communication for individuals who have speech or hearing impairment or mental health issues that impair communication, as well as foreigners who do not speak the local language. It provides support and clarification in communication by using intuitive icons and interactive symbols that are easy to use on a mobile device. Such pictogram-based communication can be quite effective and ultimately make people’s lives happier, easier, and safer

Towards Multi-Lingual Pneumonia Research Data Collection Using the Community-Acquired Pneumonia International Cohort Study Database

Background: Although multilingual interfaces are preferred by most users when they have a choice, organizations are often unable to support and troubleshoot problems involving multiple user languages. Software that has been structured with multiple languages and data interlinking considerations early in its development is more likely to be easily maintained. We describe the process of adding multilingual support to the CAPO international Cohort study database using REDCap. Methods: Using Google Translate API we extend the supported Spanish language version of REDCap to the most recent version used by CAPO, 8.1.4. We then translate the English data dictionary for CAPO to Spanish and link the two projects together using REDCap’s hook feature. Results: The Community Acquired Pneumonia Organization database now supports data collection in Spanish for its international collaborators. REDCap’s program hook functionality facilitates both databases staying up to date. When a new case is added to the Spanish project, the case is also added to the English project and vice versa. Conclusions: We describe the implementation of multilingual functionality in a data repository for community-acquired pneumonia and describe how similar projects could be structured using REDCap as an example software environment