Full-body mobility data to validate inertial measurement unit algorithms in healthy and neurological cohorts

Gait and balance dysfunctions are common in neurological disorders and have a negative effect on the quality of life. Regularly quantifying these mobility limitations can be used to measure the disease progression and the effect of treatment. This information can be used to provide a more individualised treatment. Inertial measurement units (IMUs) can be utilized to quantify mobility in different contexts. However, algorithms are required to extract valuable parameters out of the raw IMU data. These algorithms need to be validated to make sure that they extract the features they should extract. This validation should be done per disease, since different mobility limitations or symptoms can influence the performance of an algorithm in different ways. Therefore, this dataset contains data from both healthy participants and patients with neurological diseases (Parkinson disease, stroke, multiple sclerosis, chronic low back pain). The full-body of 167 participants were measured with IMUs and an optical motion capture (reference) system. Participants performed multiple standardized mobility assessments and non-standardized activities of daily living.