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
Issue
Section
License
Copyright (c) 2024 International Journal on Emerging Research Areas

This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- Adhil Salim, Advaith Manoj, Alan Thomas Shaji, The Future of Encryption in the Face of Advancing Quantum Computing Technology , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Akhil Shaji, Albin Joshy, M J Athulkrishna, Joel Biju, Bino Thomas, COLLEGE BUS SECURITY AND MANAGEMENT SYSTEM , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- S Adithyakrishnan, U Anjukrishna, Rohith Manuel Philip, P Careena, A Comprehensive Review on Diagnosis and Classification of Various Respiratory Diseases , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Adona Shibu, Aarunya Retheep, Albin Joseph, Ali Jasim, Adona Shibu , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Adithya Satheesh, Ashwin S Nair, Darren Padamittam Jacob, Athul Rajeev, Er. Maheshwary Sreenath, Intrusion Countermeasure System , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Dileepkumar S R, Dr Juby Mathew, An Insight into DevOps: Techniques and Optimal Practices , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Adithya Satheesh, Ashwin S Nair, Darren Padamittam Jacob, Athul Rajeev, Er. Maheshwary Sreenath, Intrusion Countermeasure System , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Ansamol Varghese, Anoushkha Tresa, Athira John, Ignatious Ealias Roy, M S Gautham Sankar, A Machine Learning Approach to Fake News Detection , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Manju Susan Thomas, Juby Mathew, The Integration of Trustworthy AI Values: A Comprehensive Model for Governance, Risk, and Compliance in Audit Architecture Framework context , International Journal on Emerging Research Areas: Vol. 3 No. 2 (2023): IJERA
- Dr nitha C Vellayudan, Akshay K.P, Muhamed Adhil P.M, C.A Sivasankar , Crop Yield and Price Prediction , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
You may also start an advanced similarity search for this article.