Dbs Essential Tremor Adaptive Dbs

Parkinson's Disease (PD) is the second most common neurodegenerative disease, characterized by progressive motor (such as resting tremor, hypokinesia, postural instability) and non-motor symptoms (such as neuropsychiatric decline and autonomic dysfunction). Since its introduction in the late 1980s, deep brain stimulation (DBS) has revolutionized the treatment of PD. Initially used in patients' with advanced PD with either medically refractory motor symptoms or medication intolerance, DBS typically provides excellent improvement in motor symptoms...

INTRODUCTION: Deep brain stimulation (DBS) has been an established surgical procedure in the field of functional neurosurgery for many years. The experimental electrophysiological method of local field potential (LFP) recordings in postsurgically externalized patients has made substantial contributions to the better understanding of pathophysiologies underlying movement disorders. As interest in LFP recordings for the development of improved stimulation strategies increases, this study's aim was to provide evidence concerning safety of this research method, in a major DBS center...

Deep brain stimulation (DBS) for Parkinson's disease, essential tremor and epilepsy is an established palliative treatment. DBS uses electrical neuromodulation to suppress symptoms. Most current systems provide a continuous pattern of fixed stimulation, with clinical follow-ups to refine settings constrained to normal office hours. An issue with this management strategy is that the impact of stimulation on circadian, i.e. sleep-wake, rhythms is not fully considered; either in the device design or in the clinical follow-up...

Deep brain stimulation (DBS) is an established therapy for Parkinson's disease (PD) and essential-tremor (ET). In adaptive DBS (aDBS) systems, online tuning of stimulation parameters as a function of neural signals may improve treatment efficacy and reduce side-effects. State-of-the-art aDBS systems use symptom surrogates derived from neural signals-so-called neural markers (NMs)-defined on the patient-group level, and control strategies assuming stationarity of symptoms and NMs. We aim at improving these aDBS systems with (1) a data-driven approach for identifying patient- and session-specific NMs and (2) a control strategy coping with short-term non-stationary dynamics...

Background: Deep brain stimulation (DBS) has become a standard treatment for advanced stages of Parkinson's disease, essential tremor, and dystonia. In addition to the correct surgical device implantation, effective programming is regarded to be the most important factor for clinical outcome. Despite established strategies for adjusting neurostimulation, DBS programming remains time- and resource-consuming. Although kinematic and neuronal biosignals have recently been examined as potential feedback for closed-loop DBS (CL-DBS), there is an ongoing need for programming strategies to adapt the stimulation parameters and electrode configurations accurately and effectively...

Introduction: Parkinson's disease (PD) is a progressive movement disorder characterized by heterogenous motor dysfunction with fluctuations in severity. Objective, short-timescale characterization of this dysfunction is necessary as therapies become increasingly adaptive. Objectives: This study aims to characterize a novel, naturalistic, and goal-directed tablet-based task and complementary analysis protocol designed to characterize the motor features of PD. Methods: A total of 26 patients with PD and without deep brain stimulation (DBS), 20 control subjects, and eight patients with PD and with DBS completed the task...

OBJECTIVE: Deep brain stimulation (DBS) is a safe and established treatment for essential tremor (ET) and several other movement disorders. One approach to improving DBS therapy is adaptive DBS (aDBS), in which stimulation parameters are modulated in real time based on biofeedback from either external or implanted sensors. Previously tested systems have fallen short of translational applicability due to the requirement for patients to continuously wear the necessary sensors or processing devices, as well as privacy and security concerns...

Deep brain stimulation (DBS) is a safe and established treatment for essential tremor (ET). However, there remains considerable room for improvement due to concerns associated with the initial implant surgery, semi-regular revision surgeries for battery replacements, and side effects including paresthesia, gait ataxia, and emotional disinhibition that have been associated with continuous, or conventional, DBS (cDBS) treatment. Adaptive DBS (aDBS) seeks to ameliorate some of these concerns by using feedback from either an external wearable or implanted sensor to modulate stimulation parameters as needed...

Early studies of deep brain stimulation (DBS) for various neurological disorders involved a temporary trial period where implanted electrodes were externalized, in which the electrical contacts exiting the patient's brain are connected to external stimulation equipment, so that stimulation efficacy could be determined before permanent implant. As the optimal brain target sites for various diseases (i.e., Parkinson's disease, essential tremor) became better established, such trial periods have fallen out of favor...

Essential tremor is one of the most common tremor syndromes. According to the recent tremor classification, tremor as a symptom is defined as an involuntary, rhythmic, oscillatory movement of a body part and is classified along two axes: axis 1-defining syndromes based on the clinical features such as historical features, tremor characteristics, associated signs, and laboratory tests; and axis 2-classifying the etiology (Bhatia et al., Mov Disord 33:75-87, 2018). The management of this condition has two major approaches...

The development of closed-loop deep brain stimulation (DBS) systems represents a significant opportunity for innovation in the clinical application of neurostimulation therapies. Despite the highly dynamic nature of neurological diseases, open-loop DBS applications are incapable of modifying parameters in real time to react to fluctuations in disease states. Thus, current practice for the designation of stimulation parameters, such as duration, amplitude, and pulse frequency, is an algorithmic process. Ideal stimulation parameters are highly individualized and must reflect both the specific disease presentation and the unique pathophysiology presented by the individual...

INTRODUCTION: Deep brain stimulation (DBS) for movement disorders has been mainly performed with constant voltage (CV) technology. More recently also constant current (CC) systems have been developed which theoretically might have additional advantages. Furthermore, rechargeable (RC) system implantable pulse generators (IPG) are increasingly being used rather than the former solely available non-rechargeable (NRC) IPGs. OBJECTIVE: To provide a systematic investigation how to proceed and adapt settings when switching from CV NRC to CC RC technology...

Background: The purpose of the present study was to evaluate deep learning-based image-guided surgical planning for deep brain stimulation (DBS). We developed deep learning semantic segmentation-based DBS targeting and prospectively applied the method clinically. Methods: T2∗ fast gradient-echo images from 102 patients were used for training and validation. Manually drawn ground truth information was prepared for the subthalamic and red nuclei with an axial cut ∼4 mm below the anterior-posterior commissure line...

The annual deep brain stimulation (DBS) Think Tank aims to create an opportunity for a multidisciplinary discussion in the field of neuromodulation to examine developments, opportunities and challenges in the field. The proceedings of the Sixth Annual Think Tank recapitulate progress in applications of neurotechnology, neurophysiology, and emerging techniques for the treatment of a range of psychiatric and neurological conditions including Parkinson's disease, essential tremor, Tourette syndrome, epilepsy, cognitive disorders, and addiction...

Deep 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...

BACKGROUND: Deep brain stimulation (DBS) is an approved therapy option for movement disorders such as Parkinson's disease (PD), essential Tremor (ET), and dystonia. While current research focuses on rechargeable implantable pulse generators (IPGs), little is known about changes of the motor functions after IPG replacement and the consequences of additionally implanted hardware. OBJECTIVE: To assess changes of the motor functions, the therapy impedances, and the total electric energy delivered (TEED) after elective IPG replacement...

OBJECTIVE: Gait disturbances are frequent side effects occurring during chronic thalamic deep brain stimulation (DBS) in patients with essential tremor (ET). Adapting stimulation settings to shorter pulse widths has been shown to reduce side effects of subthalamic DBS. Here, we assess how a reduction of pulse width changes gait performance of affected patients. METHODS: Sensor-based gait assessment was performed to record spatiotemporal gait parameters in 10 healthy subjects (HS) and 7 patients with ET with gait disturbances following thalamic DBS...

INTRODUCTION: Drawing on the seminal work of DeLong, Albin, and Young, we have now entered an era of basal ganglia neuromodulation. Understanding, re-evaluating, and leveraging the lessons learned from neuromodulation will be crucial to facilitate an increased and improved application of neuromodulation in human disease. METHODS: We will focus on deep brain stimulation (DBS) - the most common form of basal ganglia neuromodulation - however, similar principles can apply to other neuromodulation modalities...

Deep brain stimulation (DBS) represents one of the major clinical breakthroughs in the age of translational neuroscience. In 1987, Benabid and colleagues demonstrated that high-frequency stimulation can mimic the effects of ablative neurosurgery in Parkinson's disease (PD), while offering two key advantages to previous procedures: adjustability and reversibility. Deep brain stimulation is now an established therapeutic approach that robustly alleviates symptoms in patients with movement disorders, such as Parkinson's disease, essential tremor, and dystonia, who present with inadequate or adverse responses to medication...

The results presented in this paper indicate that future on-demand Deep Brain Stimulation (DBS) systems for chronic use in patients with movement disorders should continuously and adaptively "learn" in order to maintain high symptom control efficacy. In this work, two machine learning algorithms-Decision Tree and LArge Memory STorage And Retrieval (LAMSTAR) neural network, both with surface Electromyography and accelerometry as control signals-are used to predict onset of tremor after DBS has been switched off in two patients, one suffering from Parkinson's disease and the other from essential tremor...