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Subspace-based predictive control of Parkinson's disease: A model-based study.

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Title: Subspace-based predictive control of Parkinson's disease: A model-based study.
Authors: Ahmadipour, Mahboubeh1 (AUTHOR) ahmadipour@eng.uk.ac.ir, Barkhordari-Yazdi, Mojtaba1 (AUTHOR) barkhordari@uk.ac.ir, Seydnejad, Saeid R.1 (AUTHOR) sseydnejad@uk.ac.ir
Source: Neural Networks. Oct2021, Vol. 142, p680-689. 10p.
Subjects: Parkinson's disease, Deep brain stimulation, Neural circuitry, Basal ganglia, Predictive control systems, Symptoms
Abstract: Deep brain stimulation (DBS) of the Basal Ganglia (BG) is an effective treatment to suppress the symptoms of Parkinson's disease (PD). Using a closed-loop scheme in DBS can not only improve its therapeutic effects but it can also reduce its energy consumption and possible side effects. In this paper, a predictive closed loop control strategy is employed to suppress the PD in real-time. A linear multi-input multi-output (MIMO) state-delayed system is considered as a simplified model of the BG neuronal network relating the stimulation signals as inputs to the beta power of local field potentials as PD biomarkers. The effect of time delay in different areas of the BG is incorporated into this model and a real-time subspace-based identification is implemented to continuously model the state of the BG neuronal network and drive the predictive control strategy. Simulation results show that the proposed MIMO subspace based predictive controller can suppress PD symptoms more effectively and with less power consumption compared to the conventional open-loop DBS and a recently proposed single-input single-output closed loop controller. [ABSTRACT FROM AUTHOR]
Copyright of Neural Networks is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 152163115
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PubTypeId: academicJournal
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  Data: Subspace-based predictive control of Parkinson's disease: A model-based study.
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  Data: <searchLink fieldCode="AR" term="%22Ahmadipour%2C+Mahboubeh%22">Ahmadipour, Mahboubeh</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ahmadipour@eng.uk.ac.ir</i><br /><searchLink fieldCode="AR" term="%22Barkhordari-Yazdi%2C+Mojtaba%22">Barkhordari-Yazdi, Mojtaba</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> barkhordari@uk.ac.ir</i><br /><searchLink fieldCode="AR" term="%22Seydnejad%2C+Saeid+R%2E%22">Seydnejad, Saeid R.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> sseydnejad@uk.ac.ir</i>
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  Data: <searchLink fieldCode="JN" term="%22Neural+Networks%22">Neural Networks</searchLink>. Oct2021, Vol. 142, p680-689. 10p.
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Parkinson's+disease%22">Parkinson's disease</searchLink><br /><searchLink fieldCode="DE" term="%22Deep+brain+stimulation%22">Deep brain stimulation</searchLink><br /><searchLink fieldCode="DE" term="%22Neural+circuitry%22">Neural circuitry</searchLink><br /><searchLink fieldCode="DE" term="%22Basal+ganglia%22">Basal ganglia</searchLink><br /><searchLink fieldCode="DE" term="%22Predictive+control+systems%22">Predictive control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Symptoms%22">Symptoms</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Deep brain stimulation (DBS) of the Basal Ganglia (BG) is an effective treatment to suppress the symptoms of Parkinson's disease (PD). Using a closed-loop scheme in DBS can not only improve its therapeutic effects but it can also reduce its energy consumption and possible side effects. In this paper, a predictive closed loop control strategy is employed to suppress the PD in real-time. A linear multi-input multi-output (MIMO) state-delayed system is considered as a simplified model of the BG neuronal network relating the stimulation signals as inputs to the beta power of local field potentials as PD biomarkers. The effect of time delay in different areas of the BG is incorporated into this model and a real-time subspace-based identification is implemented to continuously model the state of the BG neuronal network and drive the predictive control strategy. Simulation results show that the proposed MIMO subspace based predictive controller can suppress PD symptoms more effectively and with less power consumption compared to the conventional open-loop DBS and a recently proposed single-input single-output closed loop controller. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Neural Networks is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.neunet.2021.07.025
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      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 10
        StartPage: 680
    Subjects:
      – SubjectFull: Parkinson's disease
        Type: general
      – SubjectFull: Deep brain stimulation
        Type: general
      – SubjectFull: Neural circuitry
        Type: general
      – SubjectFull: Basal ganglia
        Type: general
      – SubjectFull: Predictive control systems
        Type: general
      – SubjectFull: Symptoms
        Type: general
    Titles:
      – TitleFull: Subspace-based predictive control of Parkinson's disease: A model-based study.
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            NameFull: Ahmadipour, Mahboubeh
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            NameFull: Barkhordari-Yazdi, Mojtaba
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            NameFull: Seydnejad, Saeid R.
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          Dates:
            – D: 01
              M: 10
              Text: Oct2021
              Type: published
              Y: 2021
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              Value: 142
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            – TitleFull: Neural Networks
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