Free-hand sketching is one of those skills that occurs to us almost naturally.
Using a simple pencil and paper we can sketch easily irrespective of how the sketch might look.
Now, there are also tasks, for example, diagnosis of mental health disorders
such as Post-Traumatic Stress Disorder that are difficult to administer due to various social constraints.
PTSD usually manifests itself as an aftermath of traumatic exposure.
The WHO world mental health survey reveals that traumatic experiences are pervasive among the societies worldwide.
However, the exposure is higher within low-resource communities,
where getting access to initial diagnosis of PTSD is almost difficult.
To this end, we utilize people’s natural ability of sketching to design a novel, low-cost, and creative method for screening PTSD.
In particular we ask this research question:
Can we utilize quantitative methods to identify patterns from free-hand sketches
and use them to screen for PTSD?
We explore the answer to this question through our recent IMWUT paper titled
“Leveraging Free-Hand Sketches for Potential Screening of PTSD”,
where we have collaborated with a diverse group of researchers across different disciplines.
And I am Farhana Shahid from Bangladesh University of Engineering & Technology who is presenting this work to you.
To address our research question on how to utilize free-hand sketches for screening PTSD,
we interviewed & collected data from three diverse communities in Bangladesh.
They are the Rohingya refugees, slum-dwellers, and engineering students.
We interviewed the participants using a PTSD screening tool that sets the ground truth of our study.
For the drawing task, we provided our participants with simple pencil & paper
and requested them to sketch their homes.
We chose pencil & paper considering their simplicity, low-cost, ease of use, and availability.
We selected home as our drawing subject considering its appeal and familiarity
among our study population irrespective of their diverse backgrounds.
On the researchers’ end, we used a regular mobile phone camera to digitize the sketches
which we analyzed later both quantitatively and qualitatively.
Besides, to gain a deeper understanding of the drawing task
we collected EEG signals while sketching from the participant Rohingya refugees
using a low-cost and portable EEG headset.
Next, we analyzed the sketches qualitatively and identified four different themes
where the participants presented home either as shelter, within Nature, as a place for activities, and strengthening relationships.
Following this, we utilized image processing algorithms to extract different features from the digital images of free-hand sketches.
These are: the number of corners, the number and average length of strokes.
Next, we combined data from all the participants to develop multiple logistic regression models for screening PTSD.
We used different combinations of participants' gender, group,
quantitative sketch features, and qualitative sketch themes to develop four different models.
Among them the logistic regression model that considers
interaction effect among the features could screen for PTSD with greater accuracy.
This might be because there are significant effects of both gender and participant's group on the sketch features.
Additionally, we built a Random Forest model using multimodal EEG data & sketch features from the Rohingya refugees.
Here, combining temporal EEG data with sketch features resulted in greater accuracy.
Now, if we think about the implications, our proposed low-cost assessment method
using pencil, paper, and regular mobile phone camera can be useful in resource-scarce populations.
This is particularly important for forcibly displaced populations,
the vast majority of whom are hosted by developing countries around the world.
Besides, due to the nonverbal nature of sketching our proposed method has the potential
to address communication barriers and stigma associated with sharing traumatic experiences.
Moreover, due to the automated nature of feature extraction and machine learning models,
our developed methods and metrics are standardized, repeatable, and objective.
And to sum up, through our work we have presented the initial proof for a low-cost, nonverbal assessment method to potentially screen PTSD within low-resource communities.
As part of our future work, we plan to conduct a broader study involving large diverse populations to assess the ubiquity of our proposed method for PTSD patients having diverse backgrounds.
Finally, thank you everyone for enjoying this talk.