Automatic diagnosis of melanoma using linear and nonlinear features from digital image.

Melanoma is the most serious type of skin cancer and causes more deaths than other forms of skin cancer. It is a tiny small malignant mole that is usually black or brown but also appears in other color patterns. Early detection of melanoma is key as this is the time period when it is most likely to be cured.

Gait speed estimation using Kalman Filtering on inertial measurement unit data.

Gait speed measurement is vital for diagnosis of motor disorder and monitoring the progress of patient rehabilitation. This study presents an algorithm for moderate distance gait speed measurement from data acquired with inertial motion sensors comprised of a tri-axial accelerometer and a tri-axial gyroscope. Gait speed was measured in four different speed levels set by a treadmill: 0.

Vertical ground reaction force marker for Parkinson's disease.

Parkinson's disease (PD) patients regularly exhibit abnormal gait patterns. Automated differentiation of abnormal gait from normal gait can serve as a potential tool for early diagnosis as well as monitoring the effect of PD treatment. The aim of current study is to differentiate PD patients from healthy controls, on the basis of features derived from plantar vertical ground reaction force (VGRF) data during walking at normal pace.

Automatic detection and severity measurement of eczema using image processing.

Chronic skin diseases like eczema may lead to severe health and financial consequences for patients if not detected and controlled early. Early measurement of disease severity, combined with a recommendation for skin protection and use of appropriate medication can prevent the disease from worsening. Current diagnosis can be costly and time-consuming.