Adaptive Closed-Loop Deep Brain Stimulator Coding Techniques for Target Detections in Parkinson’s

Raju, Venkateshwarla Rama; Reddy, Dabbeta Anji; Narsimha, D.; Konda, Srinivas; Rani, Balmuri Kavitha

doi:10.1080/03772063.2021.1962742

Cited by 4 publications

(2 citation statements)

References 102 publications

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“…One possible way to optimize the delivery of pulsation would be to use real-time data on the patient's condition to select the right moment for stimulation. These data can include information obtained from chemical sensors (e.g., dopamine levels), accelerometers, and ECoG and EMG data [57]. For example, the occurrence of tremors can be detected in real time by applying a pre-trained classifier to the EMG signal [58].…”

Section: Application Of Machine Learningmentioning

confidence: 99%

Modern Methods of Diagnostics and Treatment of Neurodegenerative Diseases and Depression

et al. 2023

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This paper discusses the promising areas of research into machine learning applications for the prevention and correction of neurodegenerative and depressive disorders. These two groups of disorders are among the leading causes of decline in the quality of life in the world when estimated using disability-adjusted years. Despite decades of research, the development of new approaches for the assessment (especially pre-clinical) and correction of neurodegenerative diseases and depressive disorders remains among the priority areas of research in neurophysiology, psychology, genetics, and interdisciplinary medicine. Contemporary machine learning technologies and medical data infrastructure create new research opportunities. However, reaching a consensus on the application of new machine learning methods and their integration with the existing standards of care and assessment is still a challenge to overcome before the innovations could be widely introduced to clinics. The research on the development of clinical predictions and classification algorithms contributes towards creating a unified approach to the use of growing clinical data. This unified approach should integrate the requirements of medical professionals, researchers, and governmental regulators. In the current paper, the current state of research into neurodegenerative and depressive disorders is presented.

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Section: Application Of Machine Learningmentioning

confidence: 99%

Modern Methods of Diagnostics and Treatment of Neurodegenerative Diseases and Depression

et al. 2023

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“…25 In our NW we prove that probing the, investigating -studying the brain's 'problem-solving' capabilities flanking, combining with its aim of spending as limited resources equally feasible and capable of aid us recognize why, wherefore and wherefor brains act and looklike, look as if they accomplish and then fix. [26][27][28][29][30][31][32][33][34] In other studies [35][36][37][38][39][40][41][42][43][44] Co-lead author Dr. Danyal Akarca, as well as of from the MRC CBSU, supplemented, this originates as of an extensive source, that is the biologic-systems frequently acquire to generate the maximum and majority of what kind of active/energetic properties/resources that they have obtainable for them. The explanations and resolutions they arise to are frequently and repeatedly extremely neat and sophisticated also signal the business/trade-offs connecting numerous several forces impressed over on them.…”

Section: Introductionmentioning

confidence: 99%

A study of brains complex organs-organisms with artificial intelligence system to evolve cardinal feature-manifestations of brain`s (self-organizing)

Raju

2023

IJN

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: Embedding carnal (somatic or physical) restraints over the artificial intelligent system (i.e., artificially-intelligent system) in ample the similar way that the ‘human-brain’ must grow, progress plus function in the physically real, tangible and biological constrictions that lets system to advance feature-manifestations of the brains of multifaceted organs and organisms so as to solve brain issues. : Placing carnal restraints on AI-based model-system, i.e., artificially intelligent system. : spatially embedded recurrent neural nets (RNNs), 3D Euclidean space, where message of fundamental neural-cells are hampered by ‘sparse-connectome’ recurrent-neural-nets (RNN). : RNNs converge over anatomical, structural functional features universally originate within primates (cardinal, mandrill), and macaques’ cerebral/rational, brainy-cortices. Explicitly, they congregate/ (converge) over resolving implications via segmental (modular) tiny-world nets, in which functionally analogous-units spatially configure/construct themselves to use the dynamically effective varied-discerning code. Since features occur in union RNNs show how many mutual anatomical, functional-brain patterns (motifs) are deeply linked, can be ascribed to basic biologic optimization-processes. : RNNs merge biophysical limits in AI system plus aid as a bridge amid anatomical functional researchers to move ability neuroscience on.

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Subthalamic nucleus projection by SVM based MER Data via deep brain stimulation: A study of spike uncovering

Raju¹

2022

IJN

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This study was conducted at a medical university tertiary care hospital and research center of dedicated Parkinson and movement disorders unit in Hyderabad (South India) with a purpose to optimize projection of STN by applying M.E.R patterns analytically. 52 locally anesthetized Parkinson`s (diseased subjects/patients) underwent bilateral S.T.N-D.B.S. Concurrent M.E.R signal recording was done in a Ben’s-gun pattern setup with a 5core-pentode (5microelectrodes were set in an array scenario). Using spikes and circumstantial (or contextual) background-activity dissimilar parameters plus their phantom estimates in various-frequency-bands which include low-frequency(2Hz–7Hz), :Hz–12Hz, (sub-divided as low-) and superior :21Hz–30Hz and :31Hz-49Hz were computed. The ideal electrode implantation through better clinical-effect/dyskinesia ratio given to the peak spike-rate(S.R) in 86% of the implant. The amplitude mean-background activity in low-chucked frequency-range(FR) was analogous to right depth in 86% and right-hemisphere position in 95% of the implantation.

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Adaptive Closed-Loop Deep Brain Stimulator Coding Techniques for Target Detections in Parkinson’s

Cited by 4 publications

References 102 publications

Modern Methods of Diagnostics and Treatment of Neurodegenerative Diseases and Depression

Modern Methods of Diagnostics and Treatment of Neurodegenerative Diseases and Depression

A study of brains complex organs-organisms with artificial intelligence system to evolve cardinal feature-manifestations of brain`s (self-organizing)

Subthalamic nucleus projection by SVM based MER Data via deep brain stimulation: A study of spike uncovering

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