Hello Everyone! Welcome back to this week's blog. My name is Sritej Padmanabhan, a top 10 finalist for the 2022 3M Young Scientist challenge. In this week's blog, I will be talking about the process of narrowing down the problem to focus on. I will touch on the factors that impact this decision, and the evolution of my solution. 

With multiple problems, focusing on one can be difficult, but finding the right connection towards it can simplify the decision.  My primary areas of interest were finding ways to reduce greenhouse emissions as well as improving healthcare access to remote populations. This allowed me to narrow down my focus to my top 3 problems: The inefficiencies in the current garbage collection system (non-productive stops), improper classification of recyclable waste by households, and the struggle to accurately monitor hand tremors for remote/rural populations.

With these 3 problems the biggest factor in my decision was about “Which one I truly have a connection to?” To me this was an obvious answer. I knew I wanted to find an accurate, reliable, and accessible method to measure hand tremors for remote/rural populations so that my grandpa and others suffering from Parkinsons did not have to worry about access to qualified neurologists.

Once I picked my problem, I did more research.  I found that while access to qualified neurologists is a challenge for rural populations, accuracy of the diagnosis is also a challenge even in clinical settings.  Tremors are often diagnosed based on visual observations  and hence are observer dependent causing misclassifications. One study found 37% of essential tremor diagnosis were inaccurate.  I interviewed a professor of neurosurgery and he confirmed the challenges in accurately measuring the tremors. The pictures below show the access to neurologists in rural areas as well as the red flags in these visual observations. 

I researched further on potential solution approaches that would address both access and accuracy issues.  I wondered if measurements of hand tremors can be done from videos and started focusing my research on that approach.  My research included online resources as well as discussions with a family friend with video analysis experience.  The images below show the different existing methods used to measure hand tremors. 


Combining my background in Computer Vision programming and interest in the brain,  I finally decided to use Video Analysis to Quantitatively measure Hand Tremor Frequency.

As I work on improving my solution, my mentor Rohit Gupta has been especially helpful in assisting me. Mr. Gupta has given me input on my ideas and has reached out to different contacts in order for me to have all my questions answered. As well as this, we are working on finding a 3M product for me to use in this innovation. Thank you to Mr. Gupta for helping me along this journey and making this summer mentorship a blast. 

Overall, I feel confident about where I currently am in this journey and in my project and I hope to continue to improve it and make strong progress.  Thank you all for reading this week's blog about my experience and process for picking the right problem as well as the evolution of my solution. Stay Tuned for More and Until Next Time!


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