Towards closed-loop deep brain stimulation: Decision tree-based Essential Tremor patient's state classifier and tremor reappearance predictor

Deep brain stimulation (DBS) is an approved therapy for the treatment of medically refractory and severe movement disorders. However, most existing neurostimulators can only apply continuous stimulation [open-loop DBS (OL-DBS)], ignoring patient behavior and environmental factors, which consequently leads to an inefficient therapy, thus limiting the therapeutic window. Here, we established the feasibility of a self-adjusting therapeutic DBS [closed-loop DBS (CL-DBS)], fully embedded in a chronic investigational neurostimulator (Activa PC + S), for three patients affected by essential tremor (ET) enrolled in a longitudinal (6 months) within-subject crossover protocol (DBS OFF, OL-DBS, and CL-DBS). Most patients with ET experience involuntary limb tremor during goal-directed movements, but not during rest. Hence, the proposed CL-DBS paradigm explored the efficacy of modulating the stimulation amplitude based on patient-specific motor behavior, suppressing the pathological tremor on-demand based on a cortical electrode detecting upper limb motor activity. Here, we demonstrated how the proposed stimulation paradigm was able to achieve clinical efficacy and tremor suppression comparable with OL-DBS in a range of movements (cup reaching, proximal and distal posture, water pouring, and writing) while having a consistent reduction in energy delivery. The proposed paradigm is an important step toward a behaviorally modulated fully embedded DBS system, capable of delivering stimulation only when needed, and potentially mitigating pitfalls of OL-DBS, such as DBS-induced side effects and premature device replacement.

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Chronic electrocorticography for sensing movement intention and closed-loop deep brain stimulation with wearable sensors in an essential tremor patient

Journal of Neurosurgery ◽

10.3171/2016.8.jns16536 ◽

2017 ◽

Vol 127 (3) ◽

pp. 580-587 ◽

Cited By ~ 45

Author(s):

Jeffrey A. Herron ◽

Margaret C. Thompson ◽

Timothy Brown ◽

Howard J. Chizeck ◽

Jeffrey G. Ojemann ◽

...

Keyword(s):

Deep Brain Stimulation ◽

Essential Tremor ◽

Brain Stimulation ◽

Power Efficiency ◽

Closed Loop ◽

Wearable Sensors ◽

Open Loop ◽

Valuable Treatment ◽

Closing The Loop ◽

Deep Brain

Deep brain stimulation (DBS) has become a widespread and valuable treatment for patients with movement disorders such as essential tremor (ET). However, current DBS treatment constantly delivers stimulation in an open loop, which can be inefficient. Closing the loop with sensors to provide feedback may increase power efficiency and reduce side effects for patients. New implantable neuromodulation platforms, such as the Medtronic Activa PC+S DBS system, offer important data sources by providing chronic neural sensing capabilities and a means of investigating dynamic stimulation based on symptom measurements. The authors implanted in a single patient with ET an Activa PC+S system, a cortical strip of electrodes on the hand sensorimotor cortex, and therapeutic electrodes in the ventral intermediate nucleus of the thalamus. In this paper they describe the effectiveness of the platform when sensing cortical movement intentions while the patient actually performed and imagined performing movements. Additionally, they demonstrate dynamic closed-loop DBS based on several wearable sensor measurements of tremor intensity.

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Predicting the effects of deep brain stimulation using a reduced coupled oscillator model

10.1101/448290 ◽

2018 ◽

Cited By ~ 2

Author(s):

Gihan Weerasinghe ◽

Benoit Duchet ◽

Hayriye Cagnan ◽

Peter Brown ◽

Christian Bick ◽

...

Keyword(s):

Deep Brain Stimulation ◽

Essential Tremor ◽

Brain Stimulation ◽

Neurological Disorders ◽

Closed Loop ◽

Kuramoto Model ◽

Brain Oscillations ◽

Hybrid Strategy ◽

The Brain ◽

Deep Brain

AbstractDeep brain stimulation (DBS) is known to be an effective treatment for a variety of neurological disorders, including Parkinson’s disease and essential tremor (ET). At present, it involves administering a train of pulses with constant frequency via electrodes implanted into the brain. New ‘closed-loop’ approaches involve delivering stimulation according to the ongoing symptoms or brain activity and have the potential to provide improvements in terms of efficiency, efficacy and reduction of side effects. The success of closed-loop DBS depends on being able to devise a stimulation strategy that minimizes oscillations in neural activity associated with symptoms of motor disorders. A useful stepping stone towards this is to construct a mathematical model, which can describe how the brain oscillations should change when stimulation is applied at a particular state of the system. Our work focuses on the use of coupled oscillators to represent neurons in areas generating pathological oscillations. Using a reduced form of the Kuramoto model, we analyse how a patient should respond to stimulation when neural oscillations have a given phase and amplitude. We predict that, provided certain conditions are satisfied, the best stimulation strategy should be phase specific but also that stimulation should have a greater effect if applied when the amplitude of brain oscillations is lower. We compare this surprising prediction with data obtained from ET patients. In light of our predictions, we also propose a new hybrid strategy which effectively combines two of the strategies found in the literature, namely phase-locked and adaptive DBS.Author summaryDeep brain stimulation (DBS) involves delivering electrical impulses to target sites within the brain and is a proven therapy for a variety of neurological disorders. Closed loop DBS is a promising new approach where stimulation is applied according to the state of a patient. Crucial to the success of this approach is being able to predict how a patient should respond to stimulation. Our work focusses on DBS as applied to patients with essential tremor (ET). On the basis of a theoretical model, which describes neurons as oscillators that respond to stimulation and have a certain tendency to synchronize, we provide predictions for how a patient should respond when stimulation is applied at a particular phase and amplitude of the ongoing tremor oscillations. Previous experimental studies of closed loop DBS provided stimulation either on the basis of ongoing phase or amplitude of pathological oscillations. Our study suggests how both of these measurements can be used to control stimulation. As part of this work, we also look for evidence for our theories in experimental data and find our predictions to be satisfied in one patient. The insights obtained from this work should lead to a better understanding of how to optimise closed loop DBS strategies.

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Classifier-based closed-loop deep brain stimulation for essential tremor

2017 8th International IEEE/EMBS Conference on Neural Engineering (NER) ◽

10.1109/ner.2017.8008354 ◽

2017 ◽

Cited By ~ 4

Author(s):

Brady C. Houston ◽

Margaret C. Thompson ◽

Jeffrey G. Ojemann ◽

Andrew L. Ko ◽

Howard J. Chizeck

Keyword(s):

Deep Brain Stimulation ◽

Essential Tremor ◽

Brain Stimulation ◽

Closed Loop ◽

Deep Brain

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Approaches to closed-loop deep brain stimulation for movement disorders

Neurosurgical FOCUS ◽

10.3171/2018.5.focus18173 ◽

2018 ◽

Vol 45 (2) ◽

pp. E2 ◽

Cited By ~ 17

Author(s):

Chao-Hung Kuo ◽

Gabrielle A. White-Dzuro ◽

Andrew L. Ko

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Deep Brain Stimulation ◽

Essential Tremor ◽

Brain Stimulation ◽

Movement Disorders ◽

Closed Loop ◽

Closed Loop Systems ◽

Signal Sources ◽

Deep Brain

OBJECTIVEDeep brain stimulation (DBS) is a safe and effective therapy for movement disorders, such as Parkinson’s disease (PD), essential tremor (ET), and dystonia. There is considerable interest in developing “closed-loop” DBS devices capable of modulating stimulation in response to sensor feedback. In this paper, the authors review related literature and present selected approaches to signal sources and approaches to feedback being considered for deployment in closed-loop systems.METHODSA literature search using the keywords “closed-loop DBS” and “adaptive DBS” was performed in the PubMed database. The search was conducted for all articles published up until March 2018. An in-depth review was not performed for publications not written in the English language, nonhuman studies, or topics other than Parkinson’s disease or essential tremor, specifically epilepsy and psychiatric conditions.RESULTSThe search returned 256 articles. A total of 71 articles were primary studies in humans, of which 50 focused on treatment of movement disorders. These articles were reviewed with the aim of providing an overview of the features of closed-loop systems, with particular attention paid to signal sources and biomarkers, general approaches to feedback control, and clinical data when available.CONCLUSIONSClosed-loop DBS seeks to employ biomarkers, derived from sensors such as electromyography, electrocorticography, and local field potentials, to provide real-time, patient-responsive therapy for movement disorders. Most studies appear to focus on the treatment of Parkinson’s disease. Several approaches hold promise, but additional studies are required to determine which approaches are feasible, efficacious, and efficient.

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