Simulation-Informed Power Budget Estimate of a Fully-Implantable Brain-Computer Interface.

This study aims to estimate the maximum power consumption that guarantees a thermally safe operation for a titanium-enclosed chest wall unit (CWU) subcutaneously implanted in the pre-pectoral area. This unit is a central piece of an envisioned fully-implantable bi-directional brain-computer interface (BD-BCI). To this end, we created a thermal simulation model using the finite element method implemented in COMSOL.

A CMOS BD-BCI: Neural Recorder with Two-Step Time-Domain Quantizer and Multi-Polar Stimulator with Dual-Mode Charge Balancing.

This work presents a bi-directional brain-computer interface (BD-BCI) including a high-dynamic-range (HDR) two-step time-domain neural acquisition (TTNA) system and a high-voltage (HV) multipolar neural stimulation system incorporating dual-mode time-based charge balancing (DTCB) technique. The proposed TTNA includes four independent recording modules that can sense microvolt neural signals while tolerating large stimulation artifacts. In addition, it exhibits an integrated input-referred noise of 2.

Power Budget of a Skull Unit in a Fully-Implantable Brain-Computer Interface: Bio-Heat Model.

The aim of this study is to estimate the maximum power consumption that guarantees the thermal safety of a skull unit (SU). The SU is part of a fully-implantable bi-directional brain computer-interface (BD-BCI) system that aims to restore walking and leg sensation to those with spinal cord injury (SCI). To estimate the SU power budget, we created a bio-heat model using the finite element method (FEM) implemented in COMSOL.

Suppression of cortical electrostimulation artifacts using pre-whitening and null projection.

Invasive brain-computer interfaces (BCIs) have shown promise in restoring motor function to those paralyzed by neurological injuries. These systems also have the ability to restore sensation via cortical electrostimulation. Cortical stimulation produces strong artifacts that can obscure neural signals or saturate recording amplifiers.

Benchtop and bedside validation of a low-cost programmable cortical stimulator in a testbed for bi-directional brain-computer-interface research.

Introduction: Bi-directional brain-computer interfaces (BD-BCI) to restore movement and sensation must achieve concurrent operation of recording and decoding of motor commands from the brain and stimulating the brain with somatosensory feedback.

Methods: A custom programmable direct cortical stimulator (DCS) capable of eliciting artificial sensorimotor response was integrated into an embedded BCI system to form a safe, independent, wireless, and battery powered testbed to explore BD-BCI concepts at a low cost. The BD-BCI stimulator output was tested in phantom brain tissue by assessing its ability to deliver electrical stimulation equivalent to an FDA-approved commercial electrical cortical stimulator.

Artifact propagation in subdural cortical electrostimulation: Characterization and modeling.

Cortical stimulation electrocorticography (ECoG) may be an effective method for inducing artificial sensation in bi-directional brain-computer interfaces (BD-BCIs). However, strong electrical artifacts caused by electrostimulation may significantly degrade or obscure neural information. A detailed understanding of stimulation artifact propagation through relevant tissues may improve existing artifact suppression techniques or inspire the development of novel artifact mitigation strategies.

The role of anthropometrics in predicting the maximum oxygen consumption in emergency medicine students.

Background: Maximum oxygen consumption (VO2 max) is an important measure of cardiovascular capacity to deliver oxygen to the working muscle at maximal exercise. Anthropometrics is one of the factors that contribute to the maximum oxygen consumption.

Objective: This study aimed to predict the maximum oxygen consumption based on anthropometrics in the emergency medicine students.

A Fully-Integrated 1µW/Channel Dual-Mode Neural Data Acquisition System for Implantable Brain-Machine Interfaces.

This paper presents an ultra-low power mixed-signal neural data acquisition (MSN-DAQ) system that enables a novel low-power hybrid-domain neural decoding architecture for implantable brain-machine interfaces with high channel count. Implemented in 180nm CMOS technology, the 32-channel custom chip operates at 1V supply voltage and achieves excellent performance including 1.07µW/channel, 2.

Pre-whitening and Null Projection as an Artifact Suppression Method for Electrocorticography Stimulation in Bi-Directional Brain Computer Interfaces.

Electrocorticography (ECoG)-based bi-directional (BD) brain-computer interfaces (BCIs) are a forthcoming technology promising to help restore function to those with motor and sensory deficits. A major problem with this paradigm is that the cortical stimulation necessary to elicit artificial sensation creates strong electrical artifacts that can disrupt BCI operation by saturating recording amplifiers or obscuring useful neural signal. Even with state-of-the-art hardware artifact suppression methods, robust signal processing techniques are still required to suppress residual artifacts that are present at the digital back-end.

A Prototype of a Fully-Implantable Charge-Balanced Artificial Sensory Stimulator for Bi-directional Brain-Computer-Interface (BD-BCI).

Bi-directional brain-computer interfaces (BD-BCI) to restore movement and sensation must achieve concurrent operation of recording and decoding of motor commands from the brain and stimulating the brain with somatosensory feedback. Previously we developed and validated a benchtop prototype of a fully implantable BCI system for motor decoding. Here, a prototype artificial sensory stimulator was integrated into the benchtop system to develop a prototype of a fully-implantable BD-BCI.

Thermal Analysis of a Skull Implant in Brain-Computer Interfaces.

The goal of this study is to estimate the thermal impact of a titanium skull unit (SU) implanted on the exterior aspect of the human skull. We envision this unit to house the front-end of a fully implantable electrocorticogram (ECoG)-based bi-directional (BD) brain-computer interface (BCI). Starting from the bio-heat transfer equation with physiologically and anatomically constrained tissue parameters, we used the finite element method (FEM) implemented in COMSOL to build a computational model of the SU's thermal impact.

Optimal artifact suppression in simultaneous electrocorticography stimulation and recording for bi-directional brain-computer interface applications.

Objective: Electrocorticogram (ECoG)-based brain-computer interfaces (BCIs) are a promising platform for the restoration of motor and sensory functions to those with neurological deficits. Such bi-directional BCI operation necessitates simultaneous ECoG recording and stimulation, which is challenging given the presence of strong stimulation artifacts. This problem is exacerbated if the BCI's analog front-end operates in an ultra-low power regime, which is a basic requirement for fully implantable medical devices.

An Energy-Efficient CMOS Dual-Mode Array Architecture for High-Density ECoG-Based Brain-Machine Interfaces.

This article presents an energy-efficient electrocorticography (ECoG) array architecture for fully-implantable brain machine interface systems. A novel dual-mode analog signal processing method is introduced that extracts neural features from high- γ band (80-160 Hz) at the early stages of signal acquisition. Initially, brain activity across the full-spectrum is momentarily observed to compute the feature weights in the digital back-end during full-band mode operation.

A benchtop system to assess the feasibility of a fully independent and implantable brain-machine interface.

Objective: State-of-the-art invasive brain-machine interfaces (BMIs) have shown significant promise, but rely on external electronics and wired connections between the brain and these external components. This configuration presents health risks and limits practical use. These limitations can be addressed by designing a fully implantable BMI similar to existing FDA-approved implantable devices.

Characterization of Stimulation Artifact Behavior in Simultaneous Electrocorticography Grid Stimulation and Recording.

Bi-directional brain-computer interfaces (BCIs) require simultaneous stimulation and recording to achieve closed-loop operation. It is therefore important that the interface be able to distinguish between neural signals of interest and stimulation artifacts. Current bi-directional BCIs address this problem by temporally multiplexing stimulation and recording.

Subspace-Based Suppression of Cortical Stimulation Artifacts.

Bi-directional brain-computer interfaces for the restoration of movement and sensation must simultaneously record neural signals and deliver cortical stimulation. This poses a challenge since stimulation artifacts can be orders of magnitude stronger than neural signals. In this article, we propose a novel subspace-based method for the removal of cortical electrical stimulation artifacts.

Correlation of Gerkin, Queen's College, George, and Jackson methods in estimating maximal oxygen consumption.

Background And Aim: Test of maximal oxygen consumption is the gold standard for measuring cardio-pulmonary fitness. This study aimed to determine correlation of Gerkin, Queen's College, George, and Jackson methods in estimating maximal oxygen consumption, and demographic factors affecting maximal oxygen consumption.

Methods: This descriptive cross-sectional study was conducted in a census of medical emergency students (n=57) in Qazvin University of Medical Sciences in 2016.

Electrocorticographic Encoding of Human Gait in the Leg Primary Motor Cortex.

While prior noninvasive (e.g., electroencephalographic) studies suggest that the human primary motor cortex (M1) is active during gait processes, the limitations of noninvasive recordings make it impossible to determine whether M1 is involved in high-level motor control (e.

CMOS Ultralow Power Brain Signal Acquisition Front-Ends: Design and Human Testing.

Two brain signal acquisition (BSA) front-ends incorporating two CMOS ultralow power, low-noise amplifier arrays and serializers operating in mosfet weak inversion region are presented. To boost the amplifier's gain for a given current budget, cross-coupled-pair active load topology is used in the first stages of these two amplifiers. These two BSA front-ends are fabricated in 130 and 180 nm CMOS processes, occupying 5.

Step Test: a method for evaluating maximum oxygen consumption to determine the ability kind of work among students of medical emergencies.

Introduction: Maximum oxygen consumption shows the maximum oxygen rate of muscle oxygenation that is acceptable in many cases, to measure the fitness between person and the desired job. Given that medical emergencies are important, and difficult jobs in emergency situations require people with high physical ability and readiness for the job, the aim of this study was to evaluate the maximum oxygen consumption, to determine the ability of work type among students of medical emergencies in Qazvin in 2016.

Methods: This study was a descriptive - analytical, and in cross-sectional type conducted among 36 volunteer students of medical emergencies in Qazvin in 2016.

Performance Assessment of a Custom, Portable, and Low-Cost Brain-Computer Interface Platform.

Objective: Conventional brain-computer interfaces (BCIs) are often expensive, complex to operate, and lack portability, which confines their use to laboratory settings. Portable, inexpensive BCIs can mitigate these problems, but it remains unclear whether their low-cost design compromises their performance. Therefore, we developed a portable, low-cost BCI and compared its performance to that of a conventional BCI.

Feasibility of an ultra-low power digital signal processor platform as a basis for a fully implantable brain-computer interface system.

A fully implantable brain-computer interface (BCI) can be a practical tool to restore independence to those affected by spinal cord injury. We envision that such a BCI system will invasively acquire brain signals (e.g.

A small, portable, battery-powered brain-computer interface system for motor rehabilitation.

Motor rehabilitation using brain-computer interface (BCI) systems may facilitate functional recovery in individuals after stroke or spinal cord injury. Nevertheless, these systems are typically ill-suited for widespread adoption due to their size, cost, and complexity. In this paper, a small, portable, and extremely cost-efficient (<;$200) BCI system has been developed using a custom electroencephalographic (EEG) amplifier array, and a commercial microcontroller and touchscreen.

Electrostatic excitation for the force amplification of microcantilever sensors.

This paper describes an electrostatic excited microcantilever sensor operating in static mode that is more sensitive than traditional microcantilevers. The proposed sensor comprises a simple microcantilever with electrostatic excitation ability and an optical or piezoresistive detector. Initially the microcantilever is excited by electrostatic force to near pull-in voltage.