A Review of Parkinson Disease Detection Techniques
Abstract
Parkinson’s disease (PD) is a progressive disorder that is caused by degeneration of nerve cells in the part of the brain called the substantia nigra, which controls movement. These nerve cells die or become impaired, losing the ability to produce an important chemical called dopamine. Studies have shown that symptoms of Parkinson’s develop in patients with an 80 percent or greater loss of dopamine-producing cells in the substantia nigra. Normally, dopamine operates in a delicate balance with other neurotransmitters to help coordinate the millions of nerve and muscle cells involved in movement. Without enough dopamine, this balance is disrupted, resulting in tremor (trembling in the hands, arms, legs and jaw); rigidity (stiffness of the limbs); slowness of movement; and impaired balance and coordination – the hallmark symptoms of Parkinson’s. The cause of Parkinson’s essentially remains unknown. However, theories involving oxidative damage, environmental toxins, genetic factors and accelerated aging have been discussed as potential causes for the disease. In 2005, researchers discovered a single mutation in a Parkinson’s disease gene (first identified in 1997), which is believed responsible for five percent of inherited cases.
Keywords:
Parkinson’s disease, Deep learning, Multi-modal data analysisPublished
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