The data set include 63 typically developing (TD) children and 16 children with Cerebral Palsy(CP), Gross Motor Functions Classification System (GMFCS) I and II wearing two accelerometers, one on the lower back and one on the thigh, together with the corresponding video annotations of activities. The files includes accelerometer signal and annotation for each study subject. The files named 001-120 is individuals with CP, and the files named PM01-16 and TD01-48 are typically developing children. The study protocol was approved by the Regional Committee for Medical and Health research ethics (reference no. nr:2016/707/REK nord) and the Norwegian Center for Research Data (NSD-nr:50683). All participants and guardians signed a written informed consent before being enrolled in the study. The NTNU-HAR-children was used to validate a machine learning model for activity recognition in the paper "Validation of two novel human activity recognition models for typically developing children and children with Cerebral Palsy." (DOI:). For code used in original paper see: https://github.com/ntnu-ai-lab/harth-ml-experiments.