Insights from control theory into deep brain stimulation for relief from Parkinson's disease

Davidson, Clare M.; Paor, Annraoi M. de; Lowery, Madeleine M.

doi:10.1109/elektro.2012.6225591

Cited by 6 publications

(1 citation statement)

References 17 publications

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“…2,3 A computational prototype model simulator of PD (Parkinsonian) pathological 'oscillatory-activity' as well as its control through the application-of high-frequencystimuli is given. [2][3][4] Its a type of "macroscopic neural-mass model" whose objective was to acquire the "prime-features" of a synchronized "group-of-neurons" by mathematicalframeworks. It's proved to generate hypothetical findings which offer a fit in near accord through clinical/and or diagnostic information/data issued within, 5,6 In this study, the prototype-model produced within the 2 is employed "as the basis" through which to detect "oscillatory-activity" within oscillating (self) as well as non "self-oscillating" connected-loops.…”

Section: Introductionmentioning

confidence: 99%

Microelectrode recordings (MER) signals with subthalami nucleus (STN) deep brain stimulation (DBS) local field potentials (LFP) in basal ganglion circuitry in Parkinsonians

Raju

2023

IJN

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Since last 10 years, the authors have established what seems designate a extremely effective phenomenological model-prototype for evaluating the D B S in alleviating symptoms of Parkinson disease (PD). In this study, we broaden the scope of the model applying it to predict the computation and then generating more frequencies as of net-works (NW) tuned to a particular frequency, in fact not an self - oscillatory in any way. Two main issues discussed, 1. basic and fundamental systems are connected (or coupled) in an excitatory vogue, that is designated by ‘+ / +’, 2. Where the basic/constituent systems are connected in excitatory-inhibitory way, designated by ‘+ / -’. It expects that as of a ‘basic-system’ tuned-to tremor-frequency such that we can compute/ generate infinite (limitless) range-of-frequencies. Our example specifically, start as of systems that are primarily non oscillatory, which while the connecting coefficient surpasses a certain/threshold-value, the system starts to oscillate by the signal-amplitude that enhances through he connecting/‘coupling-strength’. One more feature-manifestation, that shown to rise by connecting complex net-works based on physiology of basal-ganglia(BG) be exemplified through “root-locus” strategy method that displays enhancing plus reducing oscillatory frequencies, present concurrently, has the theory which their symmetrical average-mean leftovers/remnants significantly continuous as the connecting-strength(amplitude) is speckled. Through this method, we are offering a new utility-tool to comprehend reality also interface of “pathological-oscillations” that trigger, PD plus more ailments ex. Memory, cognition, cognitive-impairment (CI), cognitive dementia (CD), depression, epileptic-seizures, Tourette’s syndrome, Huntington’s disease, and axial symptoms like speech, hallucinations, and gait.

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Section: Introductionmentioning

confidence: 99%

Microelectrode recordings (MER) signals with subthalami nucleus (STN) deep brain stimulation (DBS) local field potentials (LFP) in basal ganglion circuitry in Parkinsonians

Raju

2023

IJN

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Detection of signs of Parkinson’s disease using dynamical features via an indirect pointing device

Ushirobira¹,

Efimov²,

Casiez

et al. 2020

IFAC-PapersOnLine

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Designing a robust backstepping controller for rehabilitation in Parkinson's disease: a simulation study

et al. 2016

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In this study, a model of basal ganglia (BG) is applied to develop a deep brain stimulation controller to reduce Parkinson's tremor. Conventionally, one area in BG is stimulated, with no feedback, to control Parkinson's tremor. In this study, a new architecture is proposed to develop feedback controller as well as to stimulate two areas of BG simultaneously. To this end, two controllers are designed and implemented in globus pallidus internal (GPi) and subthalamic nucleus (STN) in the brain. A proportional controller and a backstepping controller are designed and implemented in GPi and STN, respectively. The proposed controllers deliver suitable stimulatory control signals to GPi and STN based on hand tremor amplitude (as the feedback). When tremor reduces, these controllers decrease the stimulatory energy intensity proportionally. Therefore, additional stimulatory signal is not delivered to the brain. Subsequently, the side effects from the excessive stimulation intensity become much less. Comparing with one area stimulation, the results show that stimulating two areas of BG results in reduction of the level of the stimulation intensity. It is observed that these two controllers are both robust in terms of changing the system parameters.

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Insights from control theory into deep brain stimulation for relief from Parkinson's disease

Cited by 6 publications

References 17 publications

Microelectrode recordings (MER) signals with subthalami nucleus (STN) deep brain stimulation (DBS) local field potentials (LFP) in basal ganglion circuitry in Parkinsonians

Microelectrode recordings (MER) signals with subthalami nucleus (STN) deep brain stimulation (DBS) local field potentials (LFP) in basal ganglion circuitry in Parkinsonians

Detection of signs of Parkinson’s disease using dynamical features via an indirect pointing device

Designing a robust backstepping controller for rehabilitation in Parkinson's disease: a simulation study

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