Kalman Filter, Object tracking and translation of 2D data to 1D signals

Observation and Identification of Erythrocyte Cell Membrane Vibrations for Differential Diagnosis

Developed a diagnostic technology that can identify visual and non-visual abnormality in an erythrocyte sample.

Skills and Expertise:

Image and Signal Processing using Matlab, SIMULINK:- Kalman Filter, template matching ; Fluorescent Microscopy, Bradford Protein Assay

1. Observing non visual abnormality of RBCs for Disease diagnosis:

Description:
-Controlled heat excitation causes vibration of the RBC membrane. This was precisely recorded, detected and tracked using KALMAN filter implemented in MATLAB and SIMULINK
-The observed frequency of vibration varies for different normal blood samples and significantly for blood infected by S.typhi & blood with abnormal cholesterol.
-A mathematical explanation for the vibration frequency was derived & a model was proposed. Overall Blood protein was estimated & correlated
-The lipid bilayer rupture time and the observed vibration waveform shows direct correlation to RBC surface and intra+extracellular parameters; #Cell vibration- frequency

Innovation: This technique might surpass the conventional biochemical techniques; Discovered parameters like RBC rupture time, Vibration frequency

2. Observing Visual abnormality of RBCs for Disease diagnosis:

Observing visual abnormality in Erythrocyte sample by template matching of test-image with a database of various diseased erythrocyte images.