Motion classification using epidural electrodes for low-invasive brain-machine interface

Uejima, Takeshi; Kita, Kiyoshi; Fujii, Toshiyuki; Kato, Ryu; Takita, Masatoshi; Yokoi, Hiroshi

doi:10.1109/iembs.2009.5333547

Cited by 12 publications

(8 citation statements)

References 13 publications

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“…In animal studies, simple motor outputs have been decoded using eECoG. In rats, an eECoG-based decoder was used to classify four types of body movements, achieving an accuracy of 73.2% [28], and the two-dimensional reach direction was decoded with an accuracy of 69% [29].…”

Section: Introductionmentioning

confidence: 99%

Decoding continuous three-dimensional hand trajectories from epidural electrocorticographic signals in Japanese macaques

et al. 2012

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Brain–machine interface (BMI) technology captures brain signals to enable control of prosthetic or communication devices with the goal of assisting patients who have limited or no ability to perform voluntary movements. Decoding of inherent information in brain signals to interpret the user’s intention is one of main approaches for developing BMI technology. Subdural electrocorticography (sECoG)-based decoding provides good accuracy, but surgical complications are one of the major concerns for this approach to be applied in BMIs. In contrast, epidural electrocorticography (eECoG) is less invasive, thus it is theoretically more suitable for long-term implementation, although it is unclear whether eECoG signals carry sufficient information for decoding natural movements. We successfully decoded continuous three-dimensional hand trajectories from eECoG signals in Japanese macaques. A steady quantity of information of continuous hand movements could be acquired from the decoding system for at least several months, and a decoding model could be used for ∼10 days without significant degradation in accuracy or recalibration. The correlation coefficients between observed and predicted trajectories were lower than those for sECoG-based decoding experiments we previously reported, owing to a greater degree of chewing artifacts in eECoG-based decoding than is found in sECoG-based decoding. As one of the safest invasive recording methods available, eECoG provides an acceptable level of performance. With the ease of replacement and upgrades, eECoG systems could become the first-choice interface for real-life BMI applications.

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Section: Introductionmentioning

confidence: 99%

Decoding continuous three-dimensional hand trajectories from epidural electrocorticographic signals in Japanese macaques

et al. 2012

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“…Despite the advantages of an invasive approach to BMI (electrocorticography) over scalp EEG (e.g., higher signal bandwidth, closer location to the recording target, higher spatial resolution and signal amplitude, and the lack of interference from both electrooculography and electromyography [with the exception of the reference electrode]), 36 an invasive approach to BMI requires the implantation of a foreign body into the brain parenchyma, 33 which may result in inflammation. With an increase in the cross-sectional area of the device, there is increased inflammation in the week following implantation 29 (most likely due to increased parenchymal damage with insertion).…”

Section: Brain-machine Interfacesmentioning

confidence: 99%

The evolution of endovascular electroencephalography: historical perspective and future applications

Sefcik¹,

Opie

John

et al. 2016

FOC

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Current standard practice requires an invasive approach to the recording of electroencephalography (EEG) for epilepsy surgery, deep brain stimulation (DBS), and brain-machine interfaces (BMIs). The development of endovascular techniques offers a minimally invasive route to recording EEG from deep brain structures. This historical perspective aims to describe the technical progress in endovascular EEG by reviewing the first endovascular recordings made using a wire electrode, which was followed by the development of nanowire and catheter recordings and, finally, the most recent progress in stent-electrode recordings. The technical progress in device technology over time and the development of the ability to record chronic intravenous EEG from electrode arrays is described. Future applications for the use of endovascular EEG in the preoperative and operative management of epilepsy surgery are then discussed, followed by the possibility of the technique's future application in minimally invasive operative approaches to DBS and BMI.

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“…In the last few years, placing ECoG grids in the epidural space has been proposed to be a less invasive alternative to subdural grids, with most studies reporting on the decoding of task-related oscillatory activity in rodents (Uejima et al, 2009 ; Slutzky et al, 2010 , 2011 ) or non-human primates (Rouse and Moran, 2009 ; Shimoda et al, 2012 ; Lee et al, 2013 ; Marathe and Taylor, 2013 ; Rouse et al, 2013 ; Williams et al, 2013 ). A few human case studies have also shown the feasibility of epidural recordings for decoding task-related oscillations during short recording sessions (Leuthardt et al, 2006 ; Gomez-Rodriguez et al, 2010 ; Gharabaghi et al, 2014a , b ).…”

Section: Discussionmentioning

confidence: 99%

Epidural electrocorticography for monitoring of arousal in locked-in state

Martens¹,

Bensch²,

Halder³

et al. 2014

Front. Hum. Neurosci.

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Electroencephalography (EEG) often fails to assess both the level (i.e., arousal) and the content (i.e., awareness) of pathologically altered consciousness in patients without motor responsiveness. This might be related to a decline of awareness, to episodes of low arousal and disturbed sleep patterns, and/or to distorting and attenuating effects of the skull and intermediate tissue on the recorded brain signals. Novel approaches are required to overcome these limitations. We introduced epidural electrocorticography (ECoG) for monitoring of cortical physiology in a late-stage amytrophic lateral sclerosis patient in completely locked-in state (CLIS). Despite long-term application for a period of six months, no implant-related complications occurred. Recordings from the left frontal cortex were sufficient to identify three arousal states. Spectral analysis of the intrinsic oscillatory activity enabled us to extract state-dependent dominant frequencies at <4, ~7 and ~20 Hz, representing sleep-like periods, and phases of low and elevated arousal, respectively. In the absence of other biomarkers, ECoG proved to be a reliable tool for monitoring circadian rhythmicity, i.e., avoiding interference with the patient when he was sleeping and exploiting time windows of responsiveness. Moreover, the effects of interventions addressing the patient’s arousal, e.g., amantadine medication, could be evaluated objectively on the basis of physiological markers, even in the absence of behavioral parameters. Epidural ECoG constitutes a feasible trade-off between surgical risk and quality of recorded brain signals to gain information on the patient’s present level of arousal. This approach enables us to optimize the timing of interactions and medical interventions, all of which should take place when the patient is in a phase of high arousal. Furthermore, avoiding low-responsiveness periods will facilitate measures to implement alternative communication pathways involving brain-computer interfaces (BCI).

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Motion classification using epidural electrodes for low-invasive brain-machine interface

Cited by 12 publications

References 13 publications

Decoding continuous three-dimensional hand trajectories from epidural electrocorticographic signals in Japanese macaques

Decoding continuous three-dimensional hand trajectories from epidural electrocorticographic signals in Japanese macaques

The evolution of endovascular electroencephalography: historical perspective and future applications

Epidural electrocorticography for monitoring of arousal in locked-in state

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