A Cross-Validation Approach for Classifying Physical Activity Intensity : A Case Study in Children with Attention Deficit/Hyperactivity Disorder

To assess physical activity intensity using raw acceleration data, various thresholds have been proposed based on different metrics, making it challenging to select the appropriate threshold, particularly when trying to find a threshold adapted to a similar study in terms of device type, population, and device placement. In this study, a cross-validation method is proposed that does not take into account the specific details of the data recording device, the placement of the device, and the characteristics of the population being recorded. We collected acceleration data from 18 healthy children and 18 children with attention deficit/hyperactivity disorder (ADHD) in normal living conditions using the Actigraph GT9X. After collection, the raw data underwent processing steps such as preprocessing, segmentation, and metric extraction. Subsequently, five intensity thresholds were applied to this data, and a voting method using an aggregation approach was used to combine the classifications from each threshold to obtain a final classification. The findings indicated that 97.2% of the voting classifications are reliable (total and approximate decisions) for children with ADHD (97.4% for healthy children), while 2.8% (2.6% for healthy children) should be considered with caution. In conclusion, our approach is flexible and adaptable to different devices and population groups, making it a valuable tool for assessing physical activity in various research contexts.