BITalino: DiY biosignals

Where: Portugal

Year: 2013

Who:BITalino - Hugo Silvia is one of the leaders

BITalino is a low-cost modular body signal sensor kit that makes people able to learn and rapidly create wearables, quantified self apps, or biomedical devices. It enables anyone to create quirky and serious projects alike for wearable health tracking devices. The base kit includes sensors to measure your muscles, heart, nervous system, motion, and ambient light—and it includes a microcontroller, Bluetooth, power management module, and all the accessories needed to start working.

How is it open?

  • BITalino is based on the Arduino open-source hardware platform but BITalino schematics are not available online and some parts of the documentation are copyrighted. The software is released under GNU
  • Anyone can clone and fork the software
  • The software is free while the hardware is sold on their website and other distributors: there are available different kind of toolkits, such as: Board Kit (149€), Freestyle Kit (159€), Plugged Kit (169€) and OpenSignals (free).
  • The kit, which costs €149 (£125), includes a set of physiological sensors that can easily detect bio-signals, and software that enables the user to visualise and record data. Usually, bio-signal-acquisition technologies cost about €10,000-15,000
  • The data is local
  • It is not clear whether a specific community was involved in the design process or not

How is it “care”?

  • It doesn’t solve a specific medical or social issue, but it allows users to build a do-it-yourself system to capture human physiology. It is designed for everyone, it's for students, teachers, makers, artists, researchers, corporate R&D because no electrical skills are required.


Cool! What’s the source?

Hello Moushira, this looks really interesting. Where did you find it? Did you actually talk to Hugo or others in his team?

I ak because, in order to process this information into an ethnography, it is important to assess who is the source (the “informant”, as ethnographers say), and how far removed he or she is from written text. More information is in our Data strategy. Especially p. 10-11 contain data quality-enhancing advice for cases in which the informant can’t or won’t themselves write their own story.