US2010056276A1PendingUtilityA1

Assessment of computer games

Assignee: NEUROINSIGHT PTY LTDPriority: Dec 22, 2006Filed: Dec 22, 2006Published: Mar 4, 2010
Est. expiryDec 22, 2026(~0.4 yrs left)· nominal 20-yr term from priority
A63F 13/10A63F 2300/6009A61B 5/165A63F 2300/1012A61B 5/245A63F 13/60A61B 5/377A61B 5/16A63F 13/45
52
PatentIndex Score
0
Cited by
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References
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Claims

Abstract

A method of improving a computer game, the method including the steps of: (a) causing a player to play the computer game in which various game situations are presented to the player during the course of the game; (b) recording game situation parameters corresponding to the various game situations of step (a); (c) determining brain activity of the player during each of the game situations which are presented to the player; (d) evaluating effectiveness of the game situation parameters by reference to brain activities determined in step (c) for each of the game situation parameters recorded in step (b); and (e) improving the game by eliminating or modifying those game situations which have low levels of brain activity as determined in step (d).

Claims

exact text as granted — not AI-modified
1 . A method of improving a computer game, the method including the steps of:
 (a) causing a player to play the computer game in which various game situations are presented to the player during the course of the game;   (b) recording game situation parameters corresponding to the various game situations of step (a);   (c) determining brain activity of the player during each of the game situations which are presented to the player;   (d) evaluating effectiveness of the game situation parameters by reference to brain activities determined in step (c) for each of the game situation parameters recorded in step (b); and   (e) improving the game by eliminating or modifying those game situations which have low levels of brain activity as determined in step (d).   
     
     
         2 . A method as claimed in  claim 1  wherein the brain activities determined in step (c) are averaged for each game situation parameter. 
     
     
         3 . A method as claimed in  claim 1  or  2  wherein step (a) is performed by a plurality of players and step (c) includes the steps of averaging the brain activities of the players. 
     
     
         4 . A method as claimed in  claim 3  wherein step (c) is carried out by determining gamma or high frequency EEG or MEG activity. 
     
     
         5 . A method as claimed in  claim 3  wherein step (c) is carried out by detecting EEG or MEG activity in the frequency range 8 to 13 Hz. 
     
     
         6 . A method as claimed in  claim 3  wherein step (c) is carried out by assessment of the phase of steady state visually evoked potentials (SSVEP) in EEG signals obtained from the players or by assessment of steady state visually evoked responses (SSVER) in MEG signals obtained from the players. 
     
     
         7 . A method as claimed in any one of  claims 1  to  6  wherein step (c) includes the steps of placing electrodes at scalp sites to obtain output EEG signals which enable assessment of:
 engagement with the game situations;   attraction associated with the game situations;   emotional intensity associated with the game situations; and/or   long term memory encoding associated with the game situations.   
     
     
         8 . A method as claimed in  claim 7  including the step of applying a sinusoidally varying visual flicker stimulus to each player during step (c) to thereby enable calculation of Fourier coefficients from said output signals to thereby enable calculation of said SSVEP amplitudes and/or phase differences. 
     
     
         9 . A method as claimed in  claim 8  wherein said SSVEP amplitude and phase are calculated by the equations: 
       
         
           
             
               
                 
                   SSVEP 
                   amplitude 
                 
                 = 
                 
                   
                     ( 
                     
                       
                         A 
                         n 
                         2 
                       
                       + 
                       
                         B 
                         n 
                         2 
                       
                     
                     ) 
                   
                 
               
                
               
                   
               
             
           
         
         
           
             
               
                 
                   SSVEP 
                   phase 
                 
                 = 
                 
                   a 
                    
                   
                       
                   
                    
                   
                     tan 
                      
                     
                       ( 
                       
                         
                           B 
                           n 
                         
                         
                           A 
                           n 
                         
                       
                       ) 
                     
                   
                 
               
                
               
                   
               
             
           
         
       
       where: a n  and b n  are cosine and sine Fourier coefficients calculated by the equations: 
       
         
           
             
               
                 a 
                 n 
               
               = 
               
                 
                   1 
                   
                     S 
                      
                     
                         
                     
                      
                     Δ 
                      
                     
                         
                     
                      
                     τ 
                   
                 
                  
                 
                   
                     ∑ 
                     
                       i 
                       = 
                       0 
                     
                     
                       S 
                       - 
                       1 
                     
                   
                    
                   
                       
                   
                    
                   
                     
                       f 
                        
                       
                         ( 
                         
                           nT 
                           + 
                           
                             i 
                              
                             
                                 
                             
                              
                             Δ 
                              
                             
                                 
                             
                              
                             τ 
                           
                         
                         ) 
                       
                     
                      
                     
                       cos 
                        
                       
                         ( 
                         
                           
                             
                               2 
                                
                               
                                   
                               
                                
                               π 
                             
                             T 
                           
                            
                           
                             ( 
                             
                               nT 
                               + 
                               
                                 i 
                                  
                                 
                                     
                                 
                                  
                                 Δ 
                                  
                                 
                                     
                                 
                                  
                                 τ 
                               
                             
                             ) 
                           
                         
                         ) 
                       
                     
                   
                 
               
             
           
         
         
           
             
               
                 b 
                 n 
               
               = 
               
                 
                   1 
                   
                     S 
                      
                     
                         
                     
                      
                     Δ 
                      
                     
                         
                     
                      
                     τ 
                   
                 
                  
                 
                   
                     ∑ 
                     
                       i 
                       = 
                       0 
                     
                     
                       S 
                       - 
                       1 
                     
                   
                    
                   
                       
                   
                    
                   
                     
                       f 
                        
                       
                         ( 
                         
                           nT 
                           + 
                           
                             i 
                              
                             
                                 
                             
                              
                             Δ 
                              
                             
                                 
                             
                              
                             τ 
                           
                         
                         ) 
                       
                     
                      
                     
                       sin 
                        
                       
                         ( 
                         
                           
                             
                               2 
                                
                               
                                   
                               
                                
                               π 
                             
                             T 
                           
                            
                           
                             ( 
                             
                               nT 
                               + 
                               
                                 i 
                                  
                                 
                                     
                                 
                                  
                                 Δ 
                                  
                                 
                                     
                                 
                                  
                                 τ 
                               
                             
                             ) 
                           
                         
                         ) 
                       
                     
                   
                 
               
             
           
         
       
       where:
 a n  and b n  are the cosine and sine Fourier coefficients respectively where; 
 n represents the nth flicker stimulus cycle; 
 S is the number of samples per flicker stimulus cycle; 
 Δτ is the time interval between samples; 
 T is the period of one cycle; 
 f(nT+iΔr) is the EEG signal (raw or pre-processed using ICA) obtained from said predetermined scalp sites; 
 and wherein A n  and B n  are overlapping smoothed Fourier coefficients calculated by using the equation: 
 
       
         
           
             
               
                 A 
                 n 
               
               = 
               
                 
                   ∑ 
                   
                     i 
                     = 
                     1 
                   
                   
                     i 
                     = 
                     N 
                   
                 
                  
                 
                     
                 
                  
                 
                   
                     a 
                     
                       n 
                       + 
                       i 
                     
                   
                   / 
                   N 
                 
               
             
           
         
         
           
             
               
                 B 
                 n 
               
               = 
               
                 
                   ∑ 
                   
                     i 
                     = 
                     1 
                   
                   
                     i 
                     = 
                     N 
                   
                 
                  
                 
                     
                 
                  
                 
                   
                     b 
                     
                       n 
                       + 
                       i 
                     
                   
                   / 
                   N 
                 
               
             
           
         
       
     
     
         10 . A method as claimed in  claim 9  including the steps of:
 obtaining EEG signals from a plurality of scalp sites of each player; and   utilising inverse mapping techniques such as BESA, EMSA or LORETA to produce modified EEG signals which represent activity in deeper regions of the brain of each subject such as the orbito-frontal cortex or the ventro-medial cortex.   
     
     
         11 . A method as claimed in  claim 9  or  10  including the step of averaging the Fourier coefficients A n  and B n  for a selected group of players and then calculating the SSVEP amplitudes and SSVEP phase differences for said group of players. 
     
     
         12 . A method as claimed in any one of  claims 8  to  11  wherein the flicker signal is applied only to the peripheral vision of each player. 
     
     
         13 . A method as claimed in  claim 12  including the steps of directing the flicker signal towards the eyes of each player via first and second screens and wherein each screen includes an opaque area, and wherein the method further includes the step of positioning the screens to the relative position of each player such that said opaque areas prevent said flicker signal impinging on the fovea of each eye of each player. 
     
     
         14 . A method as claimed in  claim 13  wherein the opacity of each screen decreases as a function of distance from its opaque area so that the intensity of the flicker signal impinging on each retina of each player decreases in value from the central vision to the peripheral vision. 
     
     
         15 . A method as claimed in  claim 14  including the step of applying a masking pattern to each screen to define the opacity thereof, the method including the step of applying the pattern in accordance with a masking pattern function which provides zero or low gradients for changes in opacity adjacent to its opaque area and peripheral areas thereof which define parts of the flicker signal impinging on the peripheral vision of each player. 
     
     
         16 . A method as claimed in  claim 15  wherein the opaque area of each screen is circular and wherein the masking pattern function is selected to be a Gaussian function, so that the opacity P of the screen is defined by the equation:
   P=e −(r−R)     2     /G     2        
       where:
 r is the radial distance from the centre of the opaque area; and 
 G is a parameter that determines the rate of fall-off of opacity with radial distance, and wherein when r<R, P=1. 
 
     
     
         17 . A method as claimed in  claim 16  wherein G has a value in the range R/4 and 2R. 
     
     
         18 . A method as claimed in  claim 9  including the step of applying an electrode to the scalp of each player at a site which is approximately equidistant from sites O 2 , P 4  and T 6 , calculating SSVEP amplitudes and phase differences from EEG signals from said electrode whereby the output signals indicate each player's emotional intensity associated with the game situations or game situation parameters. 
     
     
         19 . A method as claimed in  claim 10  wherein the step of utilising inverse mapping determines brain activity in the right cerebral cortex in the vicinity of the right parieto-temporal junction whereby the output signals indicate each player's emotional intensity associated with the game situations or game situation parameters. 
     
     
         20 . A method as claimed in  claim 9  including the steps of applying an electrode to the scalp of each player at the F 3 , F 4 , F p1  and F p2  sites, calculating SSVEP amplitudes and phase differences from EEG signals from said electrodes, calculating values for attraction-repulsion using the equation:
   attraction=( a   1 *SSVEP phase advance at electrode  F   3   +a   2 *SSVEP phase advance at electrode  F   p1   −a   3 *SSVEP phase advance at electrode  F   4   −a   4 *SSVEP phase advance at electrode  F   p2 )   where a 1 =a 2 =a 3 =a 4 =1.0   whereby said values indicate each player's attraction or repulsion towards the game situations or game situation parameters.   
     
     
         21 . A method as claimed in  claim 10  wherein the step of utilising inverse mapping determines brain activity in:
 the right orbito-frontal cortex in the vicinity of Brodman area 11;   the right dorso-lateral prefrontal cortex in the vicinity of Brodman area 9;   the left orbito frontal cortex in the vicinity of Brodman area 11; and   the left dorso-lateral prefrontal cortex in the vicinity of Brodman area 9; and   calculating a value for attraction-repulsion using the equation:
   attraction=( c   1 *right orbito-frontal cortex (in vicinity of Brodman area 11)+ c   2 *right dorso-lateral prefrontal cortex (in vicinity of Brodman area 9)+ c   3 *left orbito frontal cortex (in vicinity of Brodman area 11)+ c   4 *left dorso-lateral prefrontal cortex (vicinity of Brodman area 9)) 
 where c 1 =1, c 2 =1, c 3 =1, c 4 =1, 
   whereby said values indicate each player's attraction or repulsion towards the game situations or game situation parameters.   
     
     
         22 . A method as claimed in  claim 9  including the steps of applying electrodes to the scalp of each player at F 3 , F 4 , P p1  and F p2  sites, calculating SSVEP amplitudes and phase differences from said electrodes, calculating values for engagement in features of the advertisement by a weighted mean SSVEP phase advance at said sites using the equation:
   engagement=( b   1 *SSVEP phase advance at electrode  F   3   +b   2 *SSVEP phase advance at electrode  P   p1   +b   3 *SSVEP phase advance at electrode  F   4   +b   4 *SSVEP phase advance at Electrode  F   p2 )   where b 1 =0.1, b 2 =0.4, b 3 =0.1, b 4 =0.4,   whereby said values indicate each player's engagement in the game situations or game situation parameters.   
     
     
         23 . A method as claimed in  claim 10  wherein the step of utilising inverse mapping determines brain activity in:
 the right orbito frontal cortex in the vicinity of Brodman area 11;   the right dorso-lateral prefrontal cortex in the vicinity of Brodman area 9;   the left frontal cortex in the vicinity of Brodman area 11; and   the left dorso-lateral prefrontal cortex in the vicinity of Brodman area 9, calculating SSVEP amplitudes and phase differences from said modified EEG signals from said electrodes; and   calculating a value for engagement using the equation:
   engagement=( d   1 *right orbito frontal cortex (in vicinity of Brodman area 11)+ d   2 *right dorso-lateral prefrontal cortex (in vicinity of Brodman area 9)+ d   3 *left orbito frontal cortex (in vicinity of Brodman area 11)+ d   4 *left dorso-lateral prefrontal cortex (in vicinity of Brodman area 9)) 
 where d 1 =0.1, d 2 =0.4, d 3 =0.1, d 4 =0.4, 
   whereby said values indicate each player's engagement in the game situations or game situation parameters.   
     
     
         24 . A system for assessing entertainment value of a computer game including:
 (a) a computer upon which the computer game to be assessed can be played, the computer being arranged to record game situation parameters corresponding to various game situations which occur during playing of the computer game;   (b) means for determining brain activity of the player during each of the game situations which occur during playing of the computer game; and   (c) means for evaluating the effectiveness of the game situation parameters by reference to brain activities determined by said means for determining brain activity for each of the recorded game situation parameters.

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