Proposal

Depression and stress are the most common, yet looked over, health issues, faced by adolescents today. It is often left unidentified owing to the stigma the society attaches to it. Depression, when left unidentified can often have adverse effects on academics as well as social life. According to a report by The Telegraph, amongst the 130 random suicides investigated in 2016, school pressure was one of the main causes in addition to bullying and illness. Global Education Magazine states that, in India, about 20 students kill themselves every day due to stress related to exams.

A 2015 Huffington post article says “The suicide rate for girls ages 15 to 19 doubled from 2007 to 2015, when it reached its highest point in 40 years, according to the CDC. The suicide rate for boys ages 15 to 19 increased by 30 percent over the same time period.” Most of these deaths have been closely linked to the factors listed above. It is clearly a very big problem that has not been solved efficiently. However, if we are able to empower school authorities to identify and diagnose symptoms of depression, they can provide them with care and effective support hence reducing the suicide rate in the future generation of our country. Since such as system does not exist in today’s world, we decided to tackle this problem using handwriting analysis, aka Graphology.

According to the book, GRAPHOLOGY AND HEALTH-A Collection of Historical Articles on The Signs of Physical and Mental Health in Handwriting, it is possible to recognize, from handwriting the presence of various “local and constitutional troubles”. There are certain outstanding features in the way one writes, strokes one uses or the amount of pressure one applies, that can symbolize ill-health. This has previously been discussed in our problem statement and its implementation is further discussed in the Research Plan. A careful identification and analysis of such arrangements can lead to early and effective diagnosis of stress and depression allowing time for the reversal of its adverse effects.

So, as seen above, Depression, stress and anxiety are three very big problems that exist in adolescents today. Since no-one ever wants to come forward, we will, through our device, remove the need to do so. Social stigma itself will not be disturbed and the children will benefit as well. Considering, schooling involves a regular submission of written assignments, by carefully monitoring the subject’s handwriting we could gain strong insights into the mental pressure experienced by the subject and help institutions administer help to those who need it.

Our device would act as a scanner which would be used to analyze handwriting and then output whether the person who has written the document is suffering from high levels of stress, anxiety or even depression. Our device markets mostly to schools all over the world as the suicide rate amongst teens has increased due to high levels of pressure from both their institution as well as their families.

By using our device, the schools would be able to, to some extent, diagnose teens with these problems early. Then, it would be easier for them to send the teens to get the help they needed rom people such as the school counsellor. Our device would focus on at least one of the following areas in handwriting including grammar, depth into paper, stroke-style, gradient, spacing, etc. By analyzing this part of the handwriting, we would be able to come to a short conclusion regarding the level of depression, stress or anxiety. This would not only help schools better form curriculums suited to the children but also the students themselves as they would be better cared for.

To start off, we are contacting a couple of schools and coaching institutions around Delhi. We will be conducting meetings with the heads of these institutions and will hopefully get their students assignments as our testing grounds. After we get access to these assignments, we will personally look at the criteria that is used in Graphology to determine the conditions discussed in the problem statement and hence reduce our test case size. Once we find out what we are looking for by manually looking at the sheets, we can either begin interviews or begin creating the device.

Using existing questionnaires, we can interview the students who have been flagged in our first run through. This would allow us to reduce the sample size even further. Even if this is not permissible, through our analysis of the students writing, we can begin to work on the first prototype. We can also use existing research from sources such as those that we have listed in the reference list. A few possible solutions for the prototype are discussed below.

Method 1 - A possible way to create the device would be as such. The first aspect of the device will involve movement across the XZ plane. This will allow us to map out the writing of the individual. We can use the results to understand the work that was written. Then, using a grammar check software, it will be easy to understand what the mistake ratio is. After this, we can work on analyzing the strokes in the writing. This would probably be done using color changing sensors which could accurately view the change in color. Finally, we would attempt to look at the depth that the pencil or pen has been pushed into the paper. To do this we would use short range accurate sensors that would be able to perceive the depth that a pen is pushed into the paper.

Method 2- Another way would be to start off by using an Arduino camera sensor which would hover over the document in the XZ plane as described and slowly capture images which could be sent to the system and reconstructed to create a total image of the sheet. This Image could then be analyzed for the grammatical mistakes. Then, we could begin using a microcontroller setup similar to that which is given in our references and use this to scan the writing into the system while analyzing the criteria above. This would allow us to get a relatively good indication of the level of depression in a student.

Our project would not only have application in schools but at a higher level also have application in the medical industry as, if we were to increase and adapt our system even slightly, it could also be used to detect early indications of diseases such as Alzheimer’s and even ALS. This would be further work in our project and would allow us to continue our project even after our IED course and create a research project out of it. Our product could actually help the world and save lives.

UPDATE - 22nd March 2017 - We have begun working on the project by attempting to work on method 2