Annotation and synchronization of smartphone inertial measurement unit and motion capture data collected in a laboratory setting to study gait and balance

TL;DR

This paper presents methods for accurate annotation and synchronization of smartphone inertial data with motion capture data in laboratory tests to validate digital health tools for gait and balance analysis.

Contribution

It introduces innovative solutions for data annotation and synchronization to improve data quality and integrity in validation studies of gait and balance measurement systems.

Findings

Successful synchronization of smartphone and motion capture data

Enhanced data annotation techniques for gait analysis

Validation of Floodlight technology against reference systems

Abstract

Validating smartphone sensor-based tests to study gait and balance against reference measurement systems in a laboratory setting poses several technical challenges related to data quality and data processing. One challenge is to guarantee the correct annotation of the data, which is required to ensure that only data collected during the same test execution are compared across measurement systems in subsequent analyses. A second challenge is to accurately synchronize the data across the different systems. Here, we propose innovative solutions for both challenges and illustrate their use in the example of comparing smartphone sensor data collected with the Floodlight technology with data collected with a motion capture system. These solutions form important tools for guaranteeing the data quality and data integrity required for the validation of gait and balance characteristics measured by digital health technology tools such as the Floodlight technology.