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

Herron, Jeffrey A.; Thompson, Margaret C.; Brown, Timothy; Chizeck, H.J.; Ojemann, Jeffrey G.; Ko, Andrew L.

doi:10.3171/2016.8.jns16536

Cited by 116 publications

(130 citation statements)

References 12 publications

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“…Therefore, sEMG is considered to be a potential input signal for aDBS for ET and tremor‐dominant PD. sEMG‐based aDBS was feasible, effective, and efficient in ET patients . Given that evidence of sEMG‐based bradykinesia and rigidity detection methods is limited, sEMG should be combined with other input signals for akinetic‐rigid PD patients.…”

Section: Adbs Based On Electrophysiological Recordingsmentioning

confidence: 99%

“…Numerous studies based on tremor detection have supported the feasibility, effectiveness, and efficiency of wearables‐based aDBS . However, no other PD symptoms are yet detectable or implemented with wearable aDBS systems, and therefore the applicability for akinetic‐rigid PD patients is unclear …”

Section: Adbs Based On Wearable Sensorsmentioning

confidence: 99%

“…sEMG-based aDBS was feasible, effective, and efficient in ET patients. [49][50][51] Given that evidence of sEMG-based bradykinesia and rigidity detection methods is limited, 52,53 sEMG should be combined with other input signals for akinetic-rigid PD patients. Another major concern of sEMG-based aDBS is potential loss of data quality attributed to the required self-management of sEMG sensors by patients.…”

Section: Surface Electromyographymentioning

confidence: 99%

“…[59][60][61] Numerous studies based on tremor detection have supported the feasibility, effectiveness, and efficiency of wearables-based aDBS. 5,51,62 However, no other PD symptoms are yet detectable or implemented with wearable aDBS systems, and therefore the applicability for akinetic-rigid PD patients is unclear. 62 Application of wearables for aDBS will rely heavily on machine-learning approaches for distinguishing symptoms from voluntary movements.…”

Section: Adbs Based On Wearable Sensorsmentioning

confidence: 99%

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An update on adaptive deep brain stimulation in Parkinson's disease

et al. 2018

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Advancing conventional open‐loop DBS as a therapy for PD is crucial for overcoming important issues such as the delicate balance between beneficial and adverse effects and limited battery longevity that are currently associated with treatment. Closed‐loop or adaptive DBS aims to overcome these limitations by real‐time adjustment of stimulation parameters based on continuous feedback input signals that are representative of the patient's clinical state. The focus of this update is to discuss the most recent developments regarding potential input signals and possible stimulation parameter modulation for adaptive DBS in PD. Potential input signals for adaptive DBS include basal ganglia local field potentials, cortical recordings (electrocorticography), wearable sensors, and eHealth and mHealth devices. Furthermore, adaptive DBS can be applied with different approaches of stimulation parameter modulation, the feasibility of which can be adapted depending on specific PD phenotypes. Implementation of technological developments like machine learning show potential in the design of such approaches; however, energy consumption deserves further attention. Furthermore, we discuss future considerations regarding the clinical implementation of adaptive DBS in PD. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

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Section: Adbs Based On Electrophysiological Recordingsmentioning

confidence: 99%

Section: Adbs Based On Wearable Sensorsmentioning

confidence: 99%

Section: Surface Electromyographymentioning

confidence: 99%

Section: Adbs Based On Wearable Sensorsmentioning

confidence: 99%

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An update on adaptive deep brain stimulation in Parkinson's disease

et al. 2018

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“…Case studies in Parkinson’s disease [37] and essential tremor [38] suggest the feasibility of using wearable sensors. One downside of this approach is that the system will only be able to suppress symptoms after they manifest, and neural signals would be likely to neuromodulate prior to a clinical manifestation.…”

Section: Development Of Closed-loop Dbs Systemsmentioning

confidence: 99%

Reengineering deep brain stimulation for movement disorders: Emerging technologies

Gündüz

Foote

Okun

2017

Current Opinion in Biomedical Engineering

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Deep brain stimulation (DBS) is a neurosurgical technique, which consists of continuous delivery of an electrical pulse through chronically implanted electrodes connected to a neurostimulator, programmable in amplitude, pulse width, frequency, and stimulation channel. DBS is a promising treatment option for addressing severe and drug-resistant movement disorders. The success of DBS therapy is a combination of surgical implantation techniques, device technology, and clinical programming strategies. Changes in device settings require highly trained and experienced clinicians to achieve maximal therapeutic benefit for each targeted symptom, and optimization of stimulation parameters can take many visits. Thus, the development of innovative DBS technologies that can optimize the clinical implementation of DBS will lead to wider scale utilization. This review aims to present engineering approaches that have the potential to improve clinical outcomes of DBS, focusing on the development novel temporal patterns, innovative electrode designs, computational models to guide stimulation, closed-loop DBS, and remote programming.

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Milestones in Tremor Research: 10 Years Later

Erro

Fasano

Barone

et al. 2022

Movement Disord Clin Pract

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Major progress has occurred during the last decade in the field of tremor. From the clinical standpoint, a new classification has completely revised the nosology of tremor syndromes and has re‐conceptualized essential tremor as a syndrome rather than a single disease entity, fueling an ongoing enlightened debate. Significant advances have been obtained in terms of instrumental measurement of tremor, remarking on the possibility of developing novel treatment strategies based on tremor characteristics, namely tremor‐phase. Moreover, a better understanding of the pathophysiological mechanisms has further led to the suggestion of refining the classification of tremor syndromes according to their driving underpinnings. Finally, surgical options such as deep brain stimulation and focused ultrasound thalamotomy are now part of the therapeutic portfolio for tremor, but several oral drugs, including long‐chain alcohols, T‐channel blockers, allosteric modulators of potassium channels, and of GABA‐A receptors, are currently being tested and hold promise. This review will discuss the key milestones in tremor research of the last 10 years, with a focus on the most common tremor syndromes, namely essential tremor, dystonic tremor, and Parkinsonian tremor.

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

Cited by 116 publications

References 12 publications

An update on adaptive deep brain stimulation in Parkinson's disease

An update on adaptive deep brain stimulation in Parkinson's disease

Reengineering deep brain stimulation for movement disorders: Emerging technologies

Milestones in Tremor Research: 10 Years Later

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