Automatic Assessing of Tremor Severity Using Nonlinear Dynamics, Artificial Neural Networks and Neuro-Fuzzy Classifier
Neurological diseases like Alzheimer, epilepsy, Parkinson's disease, multiple sclerosis and other dementias influence the lives of patients, their families and society. Parkinson's disease (PD) is a neurodegenerative disease that occurs due to loss of dopamine, a neurotransmitter and sl...
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| Format: | Article |
| Language: | English |
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Stefan cel Mare University of Suceava
2014-02-01
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| Series: | Advances in Electrical and Computer Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.4316/AECE.2014.01020 |
| _version_ | 1811276585263693824 |
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| author | GEMAN, O. COSTIN, H. |
| author_facet | GEMAN, O. COSTIN, H. |
| author_sort | GEMAN, O. |
| collection | DOAJ |
| description | Neurological diseases like Alzheimer, epilepsy, Parkinson's disease, multiple sclerosis and other
dementias influence the lives of patients, their families and society. Parkinson's disease (PD)
is a neurodegenerative disease that occurs due to loss of dopamine, a neurotransmitter and slow
destruction of neurons. Brain area affected by progressive destruction of neurons is responsible
for controlling movements, and patients with PD reveal rigid and uncontrollable gestures, postural
instability, small handwriting and tremor. Commercial activity-promoting gaming systems such as the
Nintendo Wii and Xbox Kinect can be used as tools for tremor, gait or other biomedical signals acquisitions.
They also can aid for rehabilitation in clinical settings. This paper emphasizes the use of intelligent
optical sensors or accelerometers in biomedical signal acquisition, and of the specific nonlinear dynamics
parameters or fuzzy logic in Parkinson's disease tremor analysis. Nowadays, there is no screening test
for early detection of PD. So, we investigated a method to predict PD, based on the image processing of
the handwriting belonging to a candidate of PD. For classification and discrimination between healthy
people and PD people we used Artificial Neural Networks (Radial Basis Function - RBF and Multilayer
Perceptron - MLP) and an Adaptive Neuro-Fuzzy Classifier (ANFC). In general, the results may be expressed
as a prognostic (risk degree to contact PD). |
| first_indexed | 2024-04-13T00:00:25Z |
| format | Article |
| id | doaj.art-91d85de1a6554ab59226bffa08b76cc6 |
| institution | Directory Open Access Journal |
| issn | 1582-7445 1844-7600 |
| language | English |
| last_indexed | 2024-04-13T00:00:25Z |
| publishDate | 2014-02-01 |
| publisher | Stefan cel Mare University of Suceava |
| record_format | Article |
| series | Advances in Electrical and Computer Engineering |
| spelling | doaj.art-91d85de1a6554ab59226bffa08b76cc62022-12-22T03:11:23ZengStefan cel Mare University of SuceavaAdvances in Electrical and Computer Engineering1582-74451844-76002014-02-0114113313810.4316/AECE.2014.01020Automatic Assessing of Tremor Severity Using Nonlinear Dynamics, Artificial Neural Networks and Neuro-Fuzzy ClassifierGEMAN, O.COSTIN, H.Neurological diseases like Alzheimer, epilepsy, Parkinson's disease, multiple sclerosis and other dementias influence the lives of patients, their families and society. Parkinson's disease (PD) is a neurodegenerative disease that occurs due to loss of dopamine, a neurotransmitter and slow destruction of neurons. Brain area affected by progressive destruction of neurons is responsible for controlling movements, and patients with PD reveal rigid and uncontrollable gestures, postural instability, small handwriting and tremor. Commercial activity-promoting gaming systems such as the Nintendo Wii and Xbox Kinect can be used as tools for tremor, gait or other biomedical signals acquisitions. They also can aid for rehabilitation in clinical settings. This paper emphasizes the use of intelligent optical sensors or accelerometers in biomedical signal acquisition, and of the specific nonlinear dynamics parameters or fuzzy logic in Parkinson's disease tremor analysis. Nowadays, there is no screening test for early detection of PD. So, we investigated a method to predict PD, based on the image processing of the handwriting belonging to a candidate of PD. For classification and discrimination between healthy people and PD people we used Artificial Neural Networks (Radial Basis Function - RBF and Multilayer Perceptron - MLP) and an Adaptive Neuro-Fuzzy Classifier (ANFC). In general, the results may be expressed as a prognostic (risk degree to contact PD).http://dx.doi.org/10.4316/AECE.2014.01020adaptive neuro-fuzzy classifierartificial neural networkshandwriting analysisnonlinear dynamicstremor |
| spellingShingle | GEMAN, O. COSTIN, H. Automatic Assessing of Tremor Severity Using Nonlinear Dynamics, Artificial Neural Networks and Neuro-Fuzzy Classifier Advances in Electrical and Computer Engineering adaptive neuro-fuzzy classifier artificial neural networks handwriting analysis nonlinear dynamics tremor |
| title | Automatic Assessing of Tremor Severity Using Nonlinear Dynamics, Artificial Neural Networks and Neuro-Fuzzy Classifier |
| title_full | Automatic Assessing of Tremor Severity Using Nonlinear Dynamics, Artificial Neural Networks and Neuro-Fuzzy Classifier |
| title_fullStr | Automatic Assessing of Tremor Severity Using Nonlinear Dynamics, Artificial Neural Networks and Neuro-Fuzzy Classifier |
| title_full_unstemmed | Automatic Assessing of Tremor Severity Using Nonlinear Dynamics, Artificial Neural Networks and Neuro-Fuzzy Classifier |
| title_short | Automatic Assessing of Tremor Severity Using Nonlinear Dynamics, Artificial Neural Networks and Neuro-Fuzzy Classifier |
| title_sort | automatic assessing of tremor severity using nonlinear dynamics artificial neural networks and neuro fuzzy classifier |
| topic | adaptive neuro-fuzzy classifier artificial neural networks handwriting analysis nonlinear dynamics tremor |
| url | http://dx.doi.org/10.4316/AECE.2014.01020 |
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