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Abstract
Current diagnosis of concussion relies on self-reported symptoms and medical records rather than objective biomarkers. This work uses a novel measurement setup called BioVRSea to quantify concussion status. The paradigm is based on brain and muscle signals (EEG, EMG), heart rate and center of pressure (CoP) measurements during a postural control task triggered by a moving platform and a virtual reality environment. Measurements were performed on 54 professional athletes who self-reported their history of concussion or non-concussion. Both groups completed a concussion symptom scale (SCAT5) before the measurement. We analyzed biosignals and CoP parameters before and after the platform movements, to compare the net response of individual postural control. The results showed that BioVRSea discriminated between the concussion and non-concussion groups. Particularly, EEG power spectral density in delta and theta bands showed significant changes in the concussion group and right soleus median frequency from the EMG signal differentiated concussed individuals with balance problems from the other groups. Anterior–posterior CoP frequency-based parameters discriminated concussed individuals with balance problems. Finally, we used machine learning to classify concussion and non-concussion, demonstrating that combining SCAT5 and BioVRSea parameters gives an accuracy up to 95.5%. This study is a step towards quantitative assessment of concussion.
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1 Reykjavik University, Institute of Biomedical and Neural Engineering, Reykjavik, Iceland (GRID:grid.9580.4) (ISNI:0000 0004 0643 5232)
2 Reykjavik University, Department of Psychology, School of Social Sciences, Reykjavik, Iceland (GRID:grid.9580.4) (ISNI:0000 0004 0643 5232)
3 Reykjavik University, Institute of Biomedical and Neural Engineering, Reykjavik, Iceland (GRID:grid.9580.4) (ISNI:0000 0004 0643 5232); University of Naples Federico II, Department of Chemical, Materials and Production Engineering, Naples, Italy (GRID:grid.4691.a) (ISNI:0000 0001 0790 385X)
4 University of Naples Federico II, Department of Electrical Engineering and Information Technology, Naples, Italy (GRID:grid.4691.a) (ISNI:0000 0001 0790 385X)
5 Reykjavik University, Institute of Biomedical and Neural Engineering, Reykjavik, Iceland (GRID:grid.9580.4) (ISNI:0000 0004 0643 5232); University of Salerno, Department of Computer Engineering, Electrical and Applied Mathematics, Salerno, Italy (GRID:grid.11780.3f) (ISNI:0000 0004 1937 0335)
6 Reykjavik University, Department of Psychology, School of Social Sciences, Reykjavik, Iceland (GRID:grid.9580.4) (ISNI:0000 0004 0643 5232); Landspitali National University Hospital of Iceland, Reykjavik, Iceland (GRID:grid.410540.4) (ISNI:0000 0000 9894 0842)
7 Reykjavik University, Department of Psychology, School of Social Sciences, Reykjavik, Iceland (GRID:grid.9580.4) (ISNI:0000 0004 0643 5232); Reykjavik University, Physical Activity, Physical Education, Sport and Health (PAPESH) Research Centre, Sports Science Department, School of Social Sciences, Reykjavik, Iceland (GRID:grid.9580.4) (ISNI:0000 0004 0643 5232)
8 Landspitali National University Hospital of Iceland, Reykjavik, Iceland (GRID:grid.410540.4) (ISNI:0000 0000 9894 0842); University of Iceland, Faculty of Medicine, School of Health Sciences, Reykjavik, Iceland (GRID:grid.14013.37) (ISNI:0000 0004 0640 0021)
9 University of Naples Federico II, Department of Electrical Engineering and Information Technology, Naples, Italy (GRID:grid.4691.a) (ISNI:0000 0001 0790 385X); University of Naples, Department of Information Technology and Electrical Engineering, Naples, Italy (GRID:grid.4691.a) (ISNI:0000 0001 0790 385X)
10 Reykjavik University, Institute of Biomedical and Neural Engineering, Reykjavik, Iceland (GRID:grid.9580.4) (ISNI:0000 0004 0643 5232); MINDig, Rennes, France (GRID:grid.9580.4)
11 University of Iceland, Department of Anatomy, Faculty of Medicine, School of Health Sciences, Reykjavik, Iceland (GRID:grid.14013.37) (ISNI:0000 0004 0640 0021); Akureyri Hospital, Akureyri, Iceland (GRID:grid.440311.3) (ISNI:0000 0004 0571 1872)
12 Reykjavik University, Institute of Biomedical and Neural Engineering, Reykjavik, Iceland (GRID:grid.9580.4) (ISNI:0000 0004 0643 5232); Landspitali, National University Hospital of Iceland, Department of Science, Reykjavik, Iceland (GRID:grid.410540.4) (ISNI:0000 0000 9894 0842)