What is NeuronUP Score?
NeuronUP Score is the system used to measure the progress of the patients using NeuronUP and also, in the future, it will allow you to compare your scores with the rest of the patients on a global scale over periods of time.
Types of scores shown on the NeuronUP Score screen
The overall score is the average of the scores obtained by the patient in the selected time interval.
You can see the evolution of the overall scores in the line graph of the NeuronUP Score screen.
Each point on the graph reflects the weighted average of the scores of the different cognitive functions worked on that specific date and can include both activities worked in the facility and at home. In other words, it brings together the scores of the activities worked on individually, grouped in sessions or in programs during that day.
The data is updated on the graph every day at 00:00 UTC.
The current score is the average of the scores obtained in the last three months. It is the frame of reference to know the patient’s current situation and will not be modified if the time interval for which scores will be displayed is changed.
Cognitive function score
The score of a cognitive function is the average of the scores obtained in that cognitive function in the selected time interval.
You can see the evolution of the cognitive function scores in the line graph of the NeuronUP Score screen.
Each point of the graph reflects the average of the scores of that cognitive function on that day.
You will be able to make a comparison between the scores of the different cognitive functions.
A maximum of 3 cognitive function scores and a general score will be shown on the graph at the same time.
Overall score of the activity:
The overall score of the activity is the average of the scores obtained in that activity in the selected time interval.
You can see the evolution of the score of the activity by clicking on the activity, its linear graph will appear in a pop-up window.
Each point on the graph reflects the average score for that activity on that day.
Additional information provided by the NeuronUP Score screen.
By default, the patient evolution graph will show the trend filter enabled. The trend in the patient’s evolution graph will eliminate some of the points that may cause a sharp fluctuation in the score, thus smoothing the graph line and allowing a better reading of the patient’s score evolution.
In order to calculate the trend, the patient must have obtained at least four scores in the selected time interval.
The trend filter is a mathematical tool that uses an algorithm to calculate a trend line based on the points on the graph, so it is not a random elimination of points.
The trend line is especially useful in long-term interventions with a high dispersion of results, since as mentioned above it allows to visualize the progression of the score with less interference.
The colors associated with the overall score and cognitive functions indicate:
- Gray: No change in the score or the data is not relevant enough to determine whether the patient has improved or worsened in their NeuronUP Score.
- Green: The changes in the score are sufficiently relevant to determine that the patient has improved their NeuronUP Score..
- Red: The changes in the score are relevant enough to determine that the patient has worsened in their NeuronUP Score.
Impact of Cognitive Functions on the Score
The graph of cognitive function weights in the intervention is a useful tool to assess the importance of each cognitive area in the patient’s work with NeuronUP. This information can be used by the practitioner to make adjustments to intervention activities if necessary.
The graph shows the percentage of each cognitive function involved in the calculation of the score, which is determined by the activities the patient has worked on in NeuronUP. In this way, the professional can identify areas that require more attention and focus the intervention on them. The visualization of this information allows a better understanding of the patient’s progress and greater efficiency in the intervention.
Please note that depending on your time zone, the date of the score may vary from what is shown in the graph, which will always correspond to UTC±00:00.
NeuronUP has three types of activities: worksheets, generators and games. Each of these activities has the following variables associated with it: number of correct answers, number of errors, number of attempts and number of omissions. A careful study has been made of each of these activities and the weight that each of these variables has on them.
Let n 0 , n 1 , n 2 , n 3 be the number of hits, number of errors, number of attempts and number of omissions respectively and p 0 , p 1 , p 2 , p 3 their respective weights on an activity, with p i ∈ [0, 1] e i = 0, . . . , 3. Then let s j be the score for one worked screen, in the case of games, or a single exercise, in the case of worksheets and generators, in a given activity j. We have that:
In addition, this score is multiplied according to the difficulty of the activity being performed. In the case of the worksheets, we have five levels: basic, easy, intermediate, difficult and advanced. The difficulty of a worksheet is given by the level played divided by the maximum level of that worksheet. In the case of the generators, there is no multiplication by the level. We are working on the correlation of the variables in order to establish a customized configuration to better determine the difficulty of a generator.
Finally, in games, the level played is multiplied by the maximum level of that game. Similarly to the generators, the customized games do not have the difficulty determined, but work is being done on the correlation between the configuration variables in order to calculate it.
The s j is multiplied by the difficulty d, with d ∈ R. We thus obtain the score for that respective worksheet, generator or played level in a game.
The calculation of the score for an activity j is an average of the score obtained in each of the screens played.
In addition, we offer a score by cognitive functions. Each of the activities works on different cognitive functions. Within an activity, we have determined the weight of each of these cognitive functions. Let S i be the score per activity of a given user, with i = 0, . . . . n where n is the number of activities played. Let w i be the weight of each of the cognitive functions in an activity, we have:
We also determine the percentage impact of each cognitive function score on the overall score. This is done by making a weighted average of the weights in a given function with their respective scores per activity.
We finish by calculating the overall score, which is the sum of the product of all the scores per area by their percentage of impact.