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Bio-Inspired Algorithms: Devices for Diagnosis and Treatment of Parkinson's Disease
Abstract
Parkinson's disease (PD) is a common neurodegenerative disorder with a high prevalence rate in the geriatric population, and more than 10 million people are afflicted with this disease worldwide. Striatal dopamine deficiency and intracellular inclusions containing aggregates of alpha-synuclein are the neuropathological signs caused by neuronal loss in the substantia nigra. PD causes motor and nonmotor symptoms. A diagnostic test or medical tool that is reliable for Parkinson's disease is not yet available. Thus, the diagnosis of PD is primarily based on clinical symptoms. Optimized bio-inspired algorithms are the novel and heuristic approach for diagnosis and treatment of Parkinson's disease. In this chapter, various bio-inspired algorithms are discussed such as optimized cuttlefish algorithm, optimized grasshopper algorithm, wolf search algorithm, crow search algorithm, and ant-lion algorithm. Other useful approaches include bionics institute rigidity device, sawtooth waveform-inspired pitch estimator (SWIPE), brain stimulation therapies, and bioinspired nanomedicine.
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