Lead Mentor: Dhruv R. Seshadri, Bioengineering
Project Description:
What can we do to improve diagnoses of neurological diseases?
This innovative project aims to design and develop a simple, affordable Apple Pencil-like device capable of detecting microtremors as early indicators of Alzheimer’s and other neurodegenerative diseases. Leveraging advanced sensors and AI-driven algorithms, the device will offer non-invasive, continuous monitoring, enabling earlier diagnosis and intervention for high-risk populations in Kazakhstan.
Neurological diseases such as Alzheimer’s often go undetected until symptoms are advanced, reducing the efficacy of treatment options. In Kazakhstan, a country facing a growing elderly population, access to early diagnostic tools remains limited, particularly in rural and underserved areas.
International figures show that in rich countries, the prevalence of Alzheimer’s will rise by 116% between 2015 and 2050, whereas the increase in states with a medium-to-low-income level will be 264%. Kazakhstan falls into the latter category. Figures published by the Ministry of Health for 2017 state, however, that there are only 187 people with dementia in the country. So, given a population of 18 million, only 0.001% of them have Alzheimer’s. This would seem like an excellent situation, were it not for one big “but”. People in Kazakhstan are given no information about the condition, so they don’t seek diagnosis. In post-Soviet countries, signs of dementia are traditionally put down to simple senility. Thus, there is a critical need to aid in diagnosis to help manage quality of life in these patients. This project will address these gaps by offering a user-friendly, portable solution that can be deployed in clinics and health centers.
The device will monitor fine motor movements through natural daily activities, detecting subtle tremors undetectable by the naked eye. It will interface with a smartphone app, providing real-time feedback and flagging potential signs for further clinical assessment. The data collected will not only help identify early stages of disease but also assist healthcare professionals in tracking disease progression and optimizing treatment.
By focusing on a low-cost, widely accessible technology, this project has the potential to transform neurological healthcare in Kazakhstan, enabling early detection, reducing healthcare costs, and ultimately improving quality of life for patients. We will collaborate with students at the International IT University in Almaty on this project.