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Ongoing Research Projects
Decellularization of bovine small intestine submucosa for tissue engineered graft
Drug delivery from Chitosan polymeric nanoparticles
Undergraduate Thesis
Undergraduate Thesis
Synthesis and Characterization of Chitosan-Arabic Gum Nanoparticles for Potential Bioengineering Application
When dissolved in acetic acid, Chitosan becomes a positively charged polysaccharide. On the other hand, due to the presence of deprotonation of the carboxylic groups on its glucuronic acid residues, Arabic gum (Acacia) behaves as a negatively charged polysaccharide. When these two are brought to interact with each other, they undergo ionic gelation, and forms nanoparticle.
During my undergraduate thesis, I leveraged this characteristics, and formed nanoparticle, and then extended my work on to deliver drugs (Ciprofloxacin).
Abstract: Tissue engineering combines cells, suitable physiochemical factors, materials, and engineering knowledge to replace or revamp living tissues. As an emerging field, it scavenges for newer materials and optimizes those for the application area. Natural polysaccharides like gellan gum, xanthan, and their nanocomposites have emerged as such biomaterials because they can mimic the native condition as well as having excellent biocompatibility. They have tunable mechanical, rheological, or swelling behavior. The gelling property of these composites allows the formation of a suitable hydrogel scaffold. Gellan and xanthan-based hydrogel scaffolds or 3D microstructures allow cell attachment, proliferation, differentiation, motility for proper tissue regeneration, or organ reconstruction. The extraction, processing, structure, and properties of gellan and xanthan gum are reviewed extensively in this chapter. Application of gellan and xanthan based materials in tissue engineering including bone, cartilage, intervertebral disc, retinal, neural, soft, skin, or other tissues are also described in detail. Summary tables for all of the applications and future trends are also attached for the reader’s convenience.
Academic Projects
Hospital Based Medical Device: Finding Needs
Hospital Based Medical Device: Finding Needs
This project was done under the part of BME 6201: Advanced Biomaterials graduate course. Here, we had to visit multiple district level hospitals focusing on surgical procedures. We visited National ENT hospitals and Ibn Sina Dental Unit for collaborating with medical personnel and collecting data. We then Identifed current complex problems in the medical device industry of Bangladesh that need engineering solutions.
Specificity, ADME, and Overcoming Challenges while Delivering Doxorubicin & Empagliflozin
Specificity, ADME, and Overcoming Challenges while Delivering Doxorubicin & Empagliflozin
This project was done under the part of BME 6203: Advanced Drug Delivery graduate course. Here we had to select two drugs at first. We selected anti cancer drug- doxorubicin, and recently impactful drug- empagliflozin. At first half of the project, we identified their specificity, mechanism of actions, and challenges regarding their delivery in human body. The second half of the project was completely focused on how to overcome those identified challenges.
Smart EEG Helmet for Cognitive Load Analysis of Motorcyclists
Smart EEG Helmet for Cognitive Load Analysis of Motorcyclists
This project was done under the part of BME 350: Biomedical Engineering Design -II undergraduate course. We collected real-life EEG signals from motorcyclists and quantifed those signals in α, β, γ, δ, and θ spectrum. After that we used perception based binary classifer machine learning algorithm to detect drowsiness from the quantifed signals and sent alert to the user to increase concentration. We found 75% accuracy with our method.
Body Fat Measuring Device
Body Fat Measuring Device
This project was done under the part of BME 300: Biomedical Engineering Design -I undergraduate course. We made a non-invasive, user-friendly capacitance based body fat percentage measuring device. For this, we collected data from more than 40 adults to correlate with the available methods to measure body fat percentage. We then used linear regression to deduct a formula and showed calculated body fat percentage directly in a MATLAB GUI.
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