Visualising accelerometer-based 24/7 human movement behaviour data: an umbrella review and framework development from...

Area of Science:

• Movement Behaviour Science
• Health Informatics
• Data Visualization

Background:

• Physical activity, sedentary behaviour, and sleep are key components of 24/7 human movement.
• Accurate measurement of these behaviours is crucial for health promotion and disease prevention.
• Current methods for visualising 24/7 movement behaviour metrics are not well-established, potentially hindering effective communication.

Purpose of the Study:

• To systematically review metrics used to quantify 24/7 human movement behaviours.
• To provide an overview of current data visualisation techniques for these metrics.
• To develop a framework for selecting appropriate visualisations based on communication goals.

Main Methods:

• An umbrella review of scientific literature was conducted.
• Data extraction and thematic analysis were used to identify metrics and visualisations.
• A framework was developed using the sender-receiver communication model.

Main Results:

• 93 reviews identified 134 unique metrics from accelerometer data.
• Step counts and Moderate-to-Vigorous Physical Activity (MVPA) were the most common metrics.
• Bar charts, line graphs, and pie charts are commonly used visualisations, with potential for more advanced options.

Conclusions:

• This study provides a structured summary of visualisations for accelerometer-derived movement behaviour metrics.
• A novel framework is presented to guide the choice of visualisations for different audiences and contexts.
• Further research should focus on applying and evaluating this framework in practice.