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1.
J Neural Eng ; 18(1)2021 02 05.
Article in English | MEDLINE | ID: mdl-33152715

ABSTRACT

Objective.Researchers are developing biomedical devices with embedded closed-loop algorithms for providing advanced adaptive therapies. As these devices become more capable and algorithms become more complex, tasked with integrating and interpreting multi-channel, multi-modal electrophysiological signals, there is a need for flexible bench-top testing and prototyping. We present a methodology for leveraging off-the-shelf audio equipment to construct a biosignal waveform generator capable of streaming pre-recorded biosignals from a host computer. By re-playing known, well-characterized, but physiologically relevant real-world biosignals into a device under test, researchers can evaluate their systems without the need for expensivein vivoexperiments.Approach.An open-source design based on the proposed methodology is described and validated, the NeuroDAC. NeuroDAC allows for 8 independent channels of biosignal playback using a simple, custom designed attenuation and buffering circuit. Applications can communicate with the device over a USB interface using standard audio drivers. On-board analog amplitude adjustment is used to maximize the dynamic range for a given signal and can be independently tuned for each channel.Main results.Low noise component selection yields a no-signal noise floor of just 5.35 ± 0.063. NeuroDAC's frequency response is characterized with a high pass -3 dB rolloff at 0.57 Hz, and is capable of accurately reproducing a wide assortment of biosignals ranging from EMG, EEG, and ECG to extracellularly recorded neural activity. We also present an application example using the device to test embedded algorithms on a closed-loop neural modulation device, the Medtronic RC+S.Significance.By making the design of NeuroDAC open-source we aim to present an accessible tool for rapidly prototyping new biomedical devices and algorithms than can be easily modified based on individual testing needs.ClinicalTrials.gov Identifiers: NCT04281134, NCT03437928, NCT03582891.


Subject(s)
Algorithms , Electrophysiological Phenomena , Computers , Equipment Design , Signal Processing, Computer-Assisted
2.
Front Microbiol ; 10: 1802, 2019.
Article in English | MEDLINE | ID: mdl-31428079

ABSTRACT

A wide range of Arcobacter species have been described from shellfish in various countries but their presence has not been investigated in Australasia, in which shellfish are a popular delicacy. Since several arcobacters are considered to be emerging pathogens, we undertook a small study to evaluate their presence in several different shellfish, including greenshell mussels, oysters, and abalone (paua) in New Zealand. Arcobacter cryaerophilus, a species associated with human gastroenteritis, was the only species isolated, from greenshell mussels. Whole-genome sequencing revealed a range of genomic traits in these strains that were known or associated virulence factors. Furthermore, we describe the first putative virulence plasmid in Arcobacter, containing lytic, immunoavoidance, adhesion, antibiotic resistance, and gene transfer traits, among others. Complete genome sequence determination using a combination of long- and short-read genome sequencing strategies, was needed to identify the plasmid, clearly identifying its benefits. The potential for plasmids to disseminate virulence traits among Arcobacter and other species warrants further consideration by researchers interested in the risks to public health from these organisms.

3.
Int J Comput Assist Radiol Surg ; 14(1): 83-92, 2019 Jan.
Article in English | MEDLINE | ID: mdl-30073453

ABSTRACT

PURPOSE: To evaluate the accuracy and reliability of image-based safety analysis for robotic cochlear implantation (RCI) in an ex vivo assessment. METHODS: The accuracy was evaluated in a study on 23 human temporal bones. For image analysis, a computer-assisted safety analysis based on intraoperative cone beam computed tomography was implemented. The method automatically segments the drill tunnel and predicts the distance between the tunnel and the facial nerve. In addition, the drilling error at the target is predicted. The predicted distances were compared with the actually drilled distances measured in postoperative high-resolution micro-computed tomography scans. The automatic method was compared to accuracies associated with a manual analysis of the image data. RESULTS: The presented computerized image-based analysis enabled the proximity of the facial nerve to the drill trajectory to be predicted with an accuracy of 0.22 ± 0.15 mm and drilling error at the target to be predicted with an accuracy of 0.11 mm ± 0.08 during N = 19 RCI procedures. The manual assessment of facial nerve proximity was performed with an accuracy of 0.34 ± 0.20 mm by a trained clinical expert. CONCLUSION: The assessment of intraoperative CT-based imaging presents multiple benefits over alternative safety mechanisms including early detection and applicability even in cases of malformation of the mastoid. This work presents a computer-assisted approach to image analysis that enables procedure safety measurements to be reliably performed with superior accuracy to other proposed safety methodologies, at a safe distance from the facial nerve. Its application must, however, be considered in relation to associated costs (time, cost, irradiation) and the dependence of the measure on a reliable preoperative segmentation.


Subject(s)
Cochlear Implantation/methods , Cochlear Implants , Robotic Surgical Procedures/methods , Surgery, Computer-Assisted/methods , Temporal Bone/diagnostic imaging , Humans , Reproducibility of Results , Temporal Bone/surgery , X-Ray Microtomography
4.
Sci Robot ; 2(4)2017 03 15.
Article in English | MEDLINE | ID: mdl-30246168

ABSTRACT

Surgical robot systems can work beyond the limits of human perception, dexterity and scale making them inherently suitable for use in microsurgical procedures. However, despite extensive research, image-guided robotics applications for microsurgery have seen limited introduction into clinical care to date. Among others, challenges are geometric scale and haptic resolution at which the surgeon cannot sufficiently control a device outside the range of human faculties. Mechanisms are required to ascertain redundant control on process variables that ensure safety of the device, much like instrument-flight in avionics. Cochlear implantation surgery is a microsurgical procedure, in which specific tasks are at sub-millimetric scale and exceed reliable visuo-tactile feedback. Cochlear implantation is subject to intra- and inter-operative variations, leading to potentially inconsistent clinical and audiological outcomes for patients. The concept of robotic cochlear implantation aims to increase consistency of surgical outcomes such as preservation of residual hearing and reduce invasiveness of the procedure. We report successful image-guided, robotic CI in human. The robotic treatment model encompasses: computer-assisted surgery planning, precision stereotactic image-guidance, in-situ assessment of tissue properties and multipolar neuromonitoring (NM), all based on in vitro, in vivo and pilot data. The model is expandable to integrate additional robotic functionalities such as cochlear access and electrode insertion. Our results demonstrate the feasibility and possibilities of using robotic technology for microsurgery on the lateral skull base. It has the potential for benefit in other microsurgical domains for which there is no task-oriented, robotic technology available at present.

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