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Gündoğdu S, Çolak ÖH, Doğan EA, Gülbetekin E, Polat Ö. Assessment of mental fatigue and stress on electronic sport players with data fusion. Med Biol Eng Comput 2021; 59:1691-707. [PMID: 34216320 DOI: 10.1007/s11517-021-02389-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 06/03/2021] [Indexed: 10/20/2022]
Abstract
Stress and mental fatigue are in existence constantly in daily life, and decrease our productivity while performing our daily routines. The purpose of this study was to analyze the states of stress and mental fatigue using data fusion while e-sport activity. In the study, ten volunteers performed e-sport duty which required both physical and mental effort and skills for 2 min. Volunteers' electroencephalogram (EEG), galvanic skin response (GSR), heart rate variability (HRV), and eye tracking data were obtained before and during game and then were analyzed. In addition, the effects of e-sports were evaluated with visual analogue scale and d2 attention tests. The d2 tests are performed after the game, and the game has a positive effect on attention and concentration. EEG from the frontal region indicates that the game is partly caused by stress and mental fatigue. HRV analysis showed that the sympathetic and vagal activities created by e-sports on people are different. By evaluating HRV and GSR together, it was seen that the emotional processes of the participants were stressed in some and excited in others. Data fusion can serve a variety of purposes such as determining the effect of e-sports activity on the person and the appropriate game type.
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Elisei G, Pella A, Ricotti R, Via R, Fiore MR, Calvi G, Mastella E, Paganelli C, Tagaste B, Bello F, Fontana G, Meschini G, Buizza G, Valvo F, Orlandi E, Ciocca M, Baroni G. Development and validation of a new set-up simulator dedicated to ocular proton therapy at CNAO. Phys Med 2021; 82:228-239. [PMID: 33657472 DOI: 10.1016/j.ejmp.2021.01.070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Revised: 11/27/2020] [Accepted: 01/14/2021] [Indexed: 10/22/2022] Open
Abstract
An Eye Tracking System (ETS) is used at CNAO for providing a stable and reproducible ocular proton therapy (OPT) set-up, featuring a fixation light (FL) and monitoring stereo-cameras embedded in a rigid case. The aim of this work is to propose an ETS set-up simulation algorithm, that automatically provides the FL positioning in space, according to patient-specific gaze direction and avoiding interferences with patient, beam and collimator. Two configurations are provided: one in the CT room for acquiring images required for treatment planning with the patient lying on a couch, and one related to the treatment room with the patient sitting in front of the beam. Algorithm validation was performed reproducing ETS simulation (CT) and treatment (room) set-up for 30 patients previously treated at CNAO. The positioning accuracy of the device was quantified through a set of 14 control points applied to the ETS case and localizable both in the CT volume and in room X-ray images. Differences between the position of ETS reference points estimated by the algorithm and those measured by imaging systems are reported. The corresponding gaze direction deviation is on average 0.2° polar and 0.3° azimuth for positioning in CT room and 0.1° polar and 0.4° azimuth in the treatment room. The simulation algorithm was embedded in a clinically usable software application, which we assessed as capable of ensuring ETS positioning with an average accuracy of 2 mm in CT room and 1.5 mm in treatment room, corresponding to gaze direction deviations consistently lower than 1°.
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Affiliation(s)
- G Elisei
- Centro Nazionale di Adroterapia Oncologica CNAO, Clinical Department-Bioengineering Unit, Pavia, Italy
| | - A Pella
- Centro Nazionale di Adroterapia Oncologica CNAO, Clinical Department-Bioengineering Unit, Pavia, Italy.
| | - R Ricotti
- Centro Nazionale di Adroterapia Oncologica CNAO, Clinical Department-Bioengineering Unit, Pavia, Italy
| | - R Via
- Center of Proton Therapy, Paul Scherrer Institut, 5232 Villigen, PSI, Switzerland
| | - M R Fiore
- Centro Nazionale di Adroterapia Oncologica CNAO, Clinical Department, Pavia, Italy
| | - G Calvi
- Centro Nazionale di Adroterapia Oncologica CNAO, Particle Accelerator Department, Pavia, Italy
| | - E Mastella
- Centro Nazionale di Adroterapia Oncologica CNAO, Clinical Department - Medical Physics Unit, Pavia, Italy
| | - C Paganelli
- Politecnico di Milano, Department of Electronics Information and Bioengineering, Milano, Italy
| | - B Tagaste
- Centro Nazionale di Adroterapia Oncologica CNAO, Clinical Department-Bioengineering Unit, Pavia, Italy
| | - F Bello
- Centro Nazionale di Adroterapia Oncologica CNAO, Clinical Department-Bioengineering Unit, Pavia, Italy
| | - G Fontana
- Centro Nazionale di Adroterapia Oncologica CNAO, Clinical Department-Bioengineering Unit, Pavia, Italy
| | - G Meschini
- Politecnico di Milano, Department of Electronics Information and Bioengineering, Milano, Italy
| | - G Buizza
- Politecnico di Milano, Department of Electronics Information and Bioengineering, Milano, Italy
| | - F Valvo
- Centro Nazionale di Adroterapia Oncologica CNAO, Clinical Department, Pavia, Italy
| | - E Orlandi
- Centro Nazionale di Adroterapia Oncologica CNAO, Clinical Department, Pavia, Italy
| | - M Ciocca
- Centro Nazionale di Adroterapia Oncologica CNAO, Clinical Department - Medical Physics Unit, Pavia, Italy
| | - G Baroni
- Centro Nazionale di Adroterapia Oncologica CNAO, Clinical Department-Bioengineering Unit, Pavia, Italy; Politecnico di Milano, Department of Electronics Information and Bioengineering, Milano, Italy
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