Study highlight - Sensor-based gait and balance assessment

In a study published in Sensors, researchers from the ABCD-J consortium present a mobile system for remote gait and balance monitoring, leveraging force plates, standard smartphone sensors, and the JTrack Social app. Developed as part of the ABCD-J software stack, JTrack Social enables sensor data collection related to movement in real time.

The study addressed three questions:

1. Does repeated testing itself influence changes in gait and balance (i.e., does it cause habituation effects)?
2. Does short-term gain and balance training improve performance?
3. Does wearable sensor positioning affect measurement accuracy?

To answer the first, 26 healthy adults completed weekly gait and balance assessments over three weeks. For the analysis of training effects on performance, these participants were compared to 25 participants from a previous study that followed a structured at-home training protocol. Force and pressure data were measured by a motion capturing system, and accelerometer and gyroscope data were recorded by smartphones with JTrack Social installed. Both participant groups improved similarly in gait and balance scores, indicating that habituation and training contributed equally to performance gains, underscoring the importance of accounting for learning effects in digital longitudinal studies.

To evaluate sensor positioning effects, a separate group of 32 participants wore a smartphone in a waist pouch—either at the lower back or lower abdomen—while performing a normal walk. As there were no detectable differences in values measured from the lower abdomen compared to the lower back (which is more typical for gait and balance analyses), the authors recommend that smartphone sensors could be worn in the lower abdomen position to increase comfort for participants, potentially increasing study adherence and lowering drop-out rates.

The use of JTrack Social in this study highlights the ability to quantitatively analyze gait and posture with low monetary and technical costs, demonstrating the potential for scalable digital health tools to contribute to one of the ABCD-J’s core efforts: Translating research into clinical practice.

Source: Rentz et al., 2024; www.mdpi.com/1424-8220/24/17/5598