Validation of two novel human activity recognition models for typically developing children and children with Cerebral Palsy.

ABSTRACT: Human Activity Recognition models have potential to contribute to valuable and detailed knowledge of habitual physical activity for typically developing children and children with Cerebral Palsy. The main objective of the present study was to develop and validate two Human Activity Recognition models. One trained on data from typically developing children (n = 63), the second also including data from children with Cerebral Palsy (n = 16), engaging in standardised activities and free play. Our data was collected using accelerometers and ground truth was established with video annotations. Additionally, we aimed to investigate the influence of window settings on model performance. Utilizing the Extreme gradient boost (XGBoost) classifier, twelve sub-models were created, with 1-,3- and 5-seco

SUBMITTER: Torring MF 

PROVIDER: S-EPMC11419372 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature