Quantitative assessment of trunk movements in functional reaching in children and adolescents with dyskinetic cerebral palsy.

BACKGROUND: Trunk control and upper limb function are often disturbed in people with dyskinetic cerebral palsy. While trunk control is fundamental in upper limb activities, insights in trunk control in dyskinetic cerebral palsy are missing. This study aimed to determine trunk movement characteristics in individuals with dyskinetic cerebral palsy during reaching. METHODS: Twenty individuals with dyskinetic cerebral palsy (MACS level I-III (16y6m)) and 20 typical developing peers (17y2m) were included. Participants performed three tasks: reach forward, reach sideways, and reach and grasp vertically, using a cross-sectional study design. Movements were analyzed using 3D motion capture and a sensor on the trunk. Trunk range of motion, joint angle at point of task achievement, peak and range of angular velocity and linear acceleration were compared between groups using Mann-Whitney U and independent t-tests. FINDINGS: Participants with dyskinetic cerebral palsy showed higher trunk range of motion in all planes during reach forward and reach and grasp vertically, and in rotation and lateral flexion during reach sideways. During reach and grasp vertically, the joint angle at point of task achievement differed in the transversal plane. Ranges of angular velocity and linear acceleration were higher for all tasks and planes for participants with dyskinetic cerebral palsy, and for peak values in nearly all planes. INTERPRETATION: Current results provide insights in trunk control at population level. This is a first step towards a better and individualized evaluation and treatment for trunk control, being an important factor in improving functional activities for individuals with dyskinetic cerebral palsy.

Assessment of movement disorders using wearable sensors during upper limb tasks: A scoping review.

Background: Studies aiming to objectively quantify movement disorders during upper limb tasks using wearable sensors have recently increased, but there is a wide variety in described measurement and analyzing methods, hampering standardization of methods in research and clinics. Therefore, the primary objective of this review was to provide an overview of sensor set-up and type, included tasks, sensor features and methods used to quantify movement disorders during upper limb tasks in multiple pathological populations. The secondary objective was to identify the most sensitive sensor features for the detection and quantification of movement disorders on the one hand and to describe the clinical application of the proposed methods on the other hand. Methods: A literature search using Scopus, Web of Science, and PubMed was performed. Articles needed to meet following criteria: 1) participants were adults/children with a neurological disease, 2) (at least) one sensor was placed on the upper limb for evaluation of movement disorders during upper limb tasks, 3) comparisons between: groups with/without movement disorders, sensor features before/after intervention, or sensor features with a clinical scale for assessment of the movement disorder. 4) Outcome measures included sensor features from acceleration/angular velocity signals. Results: A total of 101 articles were included, of which 56 researched Parkinson's Disease. Wrist(s), hand(s) and index finger(s) were the most popular sensor locations. Most frequent tasks were: finger tapping, wrist pro/supination, keeping the arms extended in front of the body and finger-to-nose. Most frequently calculated sensor features were mean, standard deviation, root-mean-square, ranges, skewness, kurtosis/entropy of acceleration and/or angular velocity, in combination with dominant frequencies/power of acceleration signals. Examples of clinical applications were automatization of a clinical scale or discrimination between a patient/control group or different patient groups. Conclusion: Current overview can support clinicians and researchers in selecting the most sensitive pathology-dependent sensor features and methodologies for detection and quantification of upper limb movement disorders and objective evaluations of treatment effects. Insights from Parkinson's Disease studies can accelerate the development of wearable sensors protocols in the remaining pathologies, provided that there is sufficient attention for the standardisation of protocols, tasks, feasibility and data analysis methods.