Cooking Hacks announces medical biometric sensor for Arduino and Raspberry Pi communities

Cooking Hacks, the open hardware division of Libelium, a wireless sensor networks platform provider for Smart Cities solutions, has released a new e-Health biometric sensor platform to give the maker community tools that use Arduino and Raspberry Pi open source hardware platforms to monitor patients’ conditions

This new sensor, called the e-Health Sensor Shield platform adds sensing capability for nine unique biometric parameters, such as pulse, blood pressure, oxygen in blood, electrocardiogram, airflow, glucometer, galvanic skin response, patient position and body temperature, to give the Arduino and Raspberry Pi community a way to develop new e-Health applications and products.

An Arduino is a single-board microcontroller and a software suite for programming it. It is an open-source physical computing platform and can be used to develop interactive objects, taking inputs from a variety of switches or sensors. In the case of this new e-Health sensor, the information the Arduino receives comes from a human wearing biometric sensors.

Raspberry Pi is a similar product, but it’s primary focus is teaching the basic skills of computer science. It is a credit card-sized computer that plugs into your TV and a keyboard, allowing for complete malleable customization and functionality.

“We aim to give the Arduino and Raspberry Pi community a platform to develop quick proof-of-concept projects as the basis of a new era of open source medical products,” David Gascon, CTO of Libelium said. “Cooking Hacks provides a cheap, open alternative compared to the proprietary and price prohibitive medical market solutions available, to inspire makers to develop new applications that help people thrive.”

According to the company, this information can be used to monitor a patient’s state of to collect sensitive data to be analyzed for medical diagnosis. Using different wireless protocols – such as Wi-Fi, 3G and Bluetooth – information can be sent to a laptop computer, a smartphone or directly to the Cloud for subsequent analysis.

Read more