Enhancing mobile brain and body imaging: Open-source solutions for real-world research applications

Area of Science:

• Neuroscience
• Computer Science
• Biomedical Engineering

Background:

• Mobile brain and body imaging (MoBI) necessitates unobtrusive, portable hardware for real-world human behavior monitoring.
• Existing solutions often lack robust multi-sensor signal streaming and time-synchronized recording capabilities on smartphones.
• The Lab Streaming Layer (LSL) standard is crucial for synchronizing data from various sources in neuroscience research.

Purpose of the Study:

• To enhance the Senda and Recorda Android applications for improved mobile brain and body imaging.
• To integrate additional sensors and functionalities for comprehensive real-world data acquisition.
• To validate the performance and reliability of the updated mobile data acquisition framework.

Main Methods:

• Development and integration of new features into the open-source Android apps Senda and Recorda.
• Incorporation of body-worn inertial measurement units (IMUs) and GPS for location tracking.
• Integration of Google MediaPipe for pose landmark motion capture and introduction of the Viewa app for real-time stream visualization.

Main Results:

• Successful integration of IMUs, GPS, and MediaPipe pose estimation into the mobile data acquisition framework.
• Improved usability through real-time stream integrity feedback and the Viewa visualization app.
• Validation studies confirmed high correlations between app-derived sensor data and reference sensors, demonstrating reliable performance.

Conclusions:

• The enhanced framework significantly expands research capabilities for mobile brain and body imaging.
• The updates enable seamless extension of the LSL standard into real-world scenarios beyond traditional laboratory settings.
• The improved system offers a powerful, portable, and synchronized solution for mobile neuroscience and behavioral research.