Background Dyskinetic cerebral palsy (DCP) is dominated by dystonia and choreoathetosis, two movement disorders that are often simultaneously present and challenging to evaluate. Wearable technology shows potential for monitoring motor dysfunctions at high temporal resolution while expanding our understanding of DCP movement disorders.

Objectives This study aimed (i) to develop a methodology for automatic classification of dystonia and choreoathetosis combining inertial measurement units (IMUs) and random forests (RFs) during powered wheelchair driving in participants with DCP, (ii) to determine signature features for dystonia and choreoathetosis, and (iii) to optimise placement of body-worn IMUs in function of dystonia and choreoathetosis classification performance.

Methods Unconstrained movements of the arms and head during powered mobility (n = 5 DCP participants) were analysed to extract 111 time- and frequency-domain features in 5-second windows. RFs were then used to rank, select optimal features and classify dystonia and choreoathetosis, based on expert-annotated videos.

Results Classification of dystonia and choreoathetosis for the neck, proximal and distal arm regions ranged within 67.8% - 80.7% accuracy. Reduced feature sets included between 19 - 73 features, as time-domain features were selected more prevalently in classifying both dystonia and choreoathetosis. IMUs on the distal arms predicted forehead dystonia and choreoathetosis with similar accuracy (74.5% - 81.2%) as using the forehead IMU.

Conclusions This study increases insights into DCP by relating distinct IMU features to dystonia and choreoathetosis and by leveraging distal arm-placed IMUs to assess movement disorders in multiple body parts: distal arm, proximal arm and neck region.

The authors have declared no competing interest.

This study was funded by the C3 grant from the Research Council of KU Leuven, C32/17/056

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The study was approved by the Medical Ethics Committee UZ KU Leuven and conducted in accordance with the Declaration of Helsinki.

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↵¥ Shared first authorship

The authors declare no conflict of interest concerning the current research.

This study was made possible by a C3 grant from the Research Council of the KU Leuven University, C32/17/056.

All data produced in the present study are available upon reasonable request to the authors.