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In this prospective, unicentric, case-control study, the main aim is to analyze joint movement and walking patterns in patients with acute stroke with a marker-free motion capture system. Case group: Stroke patients who fulfill the inclusion criteria are invited to participate in the study during admission. The evaluation consists of a workout designed by expert rehabilitation physicians and neurologists that is performed by the patient in front of the Microsoft Kinect camera. The custom-built software Akira record the joint angles of body trunk and upper limbs during the workout. The kinematic data will be analyzed with a machine learning algorithm that classifies the participant according to the kinematic data in normal movement or impaired movement (with the degree of impairment) by age decade. Control group: healthy participants (without neurological or osteomuscular diseases) matched by age and sex with cases 1:1. The correlation between kinematic and clinical scales (NIHSS) and functional scales (modified Rankin Scale) will be analyzed. A secondary objective will be to analyze the predictive value of the kinematic measurements with the functional outcome at three months
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140 participants in 2 patient groups
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Raquel Gutiérrez Zúñiga, MD; María Alonso de Leciñana, MD PhD
Data sourced from clinicaltrials.gov
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