HealthyPi v4 - Unplugged

A wireless, wearable, open source vital signs monitor powered by ESP32

Oct 12, 2023

Project update 13 of 13

Field Report: Using HealthyPi v4 in a Clinical Research Setting

by Philippe Valmaggia


As a medical researcher in Basel, I had the opportunity to test the performance of the HealthyPi v4, a portable vital signs monitoring device. In our lab, we work with multimodal data. This can include data such as structural imaging data, functional tests, or information about patient demographics. With the help of Healthy Pi, including vital signs in our analyses was straightforward. This field report aims to provide my personal observations and insights into the device’s usability and effectiveness during its deployment in our clinic.

Our HealthyPi v4 with an ESP32 development board

Deployment and Setup

The HealthyPi v4 was seamlessly integrated into our research infrastructure, and the setup process was straightforward. I followed the documentation online, and on the same day, the device was ready for use. Its compact size and lightweight nature allowed me to easily move it between different rooms without causing any inconvenience.

Performance Evaluation

Live ECG monitoring with the HealthyPi v4 visualised on the smartphone


Throughout my testing, the HealthyPi v4 consistently delivered accurate measurements of ECG signals. I compared its readings with those obtained from our existing medical devices, and the results were consistently reliable. This accuracy instilled confidence in the device’s ability to capture precise ECG data. We did not evaluate the other sensors (pulse oximetry, respiration rate, body temperature) quantitatively so far but they tended to be more prone to larger variability.

Data Visualization and User Experience

The HealthyPi v4’s software interface impressed me with its comprehensive and visually appealing data visualizations. The open-source code allowed to generate new graphs and charts provided an intuitive representation of the collected data. The ability to zoom in on specific data points for closer analysis was particularly helpful. I found the HealthyPi v4 to be very user-friendly.


The USB connectivity option of the HealthyPi v4 proved to be reliable and efficient. The device seamlessly integrated with our computer systems, enabling fast and secure data transfer. This ensured that the information was easily accessible and could be stored for future reference.

Recommendations for Improvement

While the HealthyPi v4 exceeded my expectations during its deployment, there are a few areas where I believe improvements could be made:

  1. Enhanced Sensor Capabilities
    Expanding the range of physiological parameters that the HealthyPi v4 can measure would make it an even more comprehensive tool in a clinical research setting. The addition of sensors or modules to measure parameters like blood pressure or glucose levels would greatly enhance its versatility and utility.
  2. Installation Documentation
    A challenge was that the HealthyPi appeared first as FTDI device and virtual COM port drivers had to be installed. A complete step-by-step documentation for the installation would be helpful.

Excellent Customer Service

To my great pleasure, Protocentral has consistently demonstrated excellent customer service - this was surprising to me for such a small company. Their dedication to providing support and assistance to their customers is commendable. Whenever I have reached out to their customer service team with inquiries or concerns regarding their products, they have responded promptly and professionally. Their knowledgeable and friendly staff go above and beyond to ensure that all my questions are answered and that I receive the necessary guidance to make the most of their offerings.


From my personal experience, the HealthyPi v4 proved to be a very valuable asset in our clinic. Its open-source code, accuracy, user-friendly interface made it a great addition to our existing research devices. I am confident that the HealthyPi has the potential to further enhance the way we monitor and assess vital signs by enabling raw data analysis.

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