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James Avery

dblp:30/3250 · DBLP profile ↗
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6ranked-venue papers
2as first author
3since 2021 · last 2024
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 4 · 2 first-author · 2 since 2021Artificial intelligence and machine learning · 3 · 2 first-author · 2 since 2021Applied, interdisciplinary, general and emerging computing · 2 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot manipulation · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › soft robotics
soft robot proprioception
0.412019
Shape Sensing of Variable Stiffness Soft Robots using Electrical Impedance Tomography · ICRA 2019
Medical and health informatics › surgical robotics
minimally invasive surgery
0.112019
Shape Sensing of Variable Stiffness Soft Robots using Electrical Impedance Tomography · ICRA 2019

Methods — techniques the papers use, named apart from their topics

frequency division multiplexing · 0.8electrical impedance tomography · 0.8
YearPublicationVenuePosition
2024 Advancing Sensing Resolution of Impedance Hand Gesture Recognition Devices
abstract
Gestures are composed of motion information (e.g. movements of fingers) and force information (e.g. the force exerted on fingers when interacting with other objects). Current hand gesture recognition solutions such as cameras and strain sensors primarily focus on correlating hand gestures with motion information and force information is seldom addressed. Here we propose a bio-impedance wearable that can recognize hand gestures utilizing both motion information and force information. Compared with previous impedance-based gesture recognition devices that can only recognize a few multi-degrees-of-freedom gestures, the proposed device can recognize 6 single-degree-of-freedom gestures and 20 multiple-degrees-of-freedom gestures, including 8 gestures in 2 force levels. The device uses textile electrodes, is benchmarked over a selected frequency spectrum, and uses a new drive pattern. Experimental results show that 179 kHz achieves the highest signal-to-noise ratio (SNR) and reveals the most distinct features. By analyzing the 49,920 samples from 6 participants, the device is demonstrated to have an average recognition accuracy of 98.96%. As a comparison, the medical electrodes achieved an accuracy of 98.05%.
Zhiyuan Lou, Xue Min, Guanhan Li, James Avery, Rebecca Stewart
IEEE J. Biomed. Health Informatics4
2023 Model Based Position Control of Soft Hydraulic Actuators
abstract
In this article, we investigate the model based position control of soft hydraulic actuators arranged in an an-tagonistic pair. A dynamical model of the system is constructed by employing the port-Hamiltonian formulation. A control algorithm is designed with an energy shaping approach, which accounts for the pressure dynamics of the fluid. A nonlinear observer is included to compensate the effect of unknown external forces. Simulations demonstrate the effectiveness of the proposed approach, and experiments achieve positioning accuracy of 0.043 mm with a standard deviation of 0.033 mm in the presence of constant external forces up to 1 N.
Mark Runciman, Enrico Franco, James Avery, Ferdinando Rodriguez y Baena, George P. Mylonas
ICRA3
2022 Lumen Shape Reconstruction using a Soft Robotic Balloon Catheter and Electrical Impedance Tomography
abstract
Incorrectly sized balloon catheters can lead to increased post-surgical complications, yet even with preoperative imaging, correct selection remains a challenge. With limited feedback during surgery, it is difficult to verify correct deployment. We propose the use of integrated impedance measurements and Electrical Impedance Tomography (EIT) imaging to assess the deformation of the balloon and determine the size and shape of the surrounding lumen. Previous work using single impedance measurements, or pressure data and analytical models, whilst demonstrating high sizing accuracy, have assumed a circular cross section. Here we extend these methods by adding a multitude of electrodes to detect elliptical and occluded lumen and obtain EIT images to localise deformations. Using a 14 Fr (5.3 mm) catheter as an example, numerical simulations were performed to find the optimal electrode configuration of two rings of 8 electrodes spaced 10 mm apart. The simulations predicted that the maximum detectable aspect ratio decreased from 0.9 for a 14mm balloon to 0.5 at 30mm. The sizing and ellipticity detection results were verified experimentally. A prototype robotic balloon catheter was constructed to automatically inflate a compliant balloon while simultaneously recording EIT and pressure data. Data were collected in experiments replicating stenotic vessels with an elliptical and asymmetrical profile, and the widening of a lumen during angioplasty. After calibration, the system was able to correctly localise the occlusion and detect aspect ratios of 0.75. EIT images further localised the occlusion and visualised the dilation of the lumen during balloon inflation.
James Avery, Mark Runciman, Cristina Fiani, Elena Monfort Sanchez, Saina Akhond, Kirill Y. Aristovich, George P. Mylonas
IROS1
2020 Bi-Frequency Symmetry Difference EIT - Feasibility and Limitations of Application to Stroke Diagnosis
abstract
OBJECTIVE: Bi-Frequency Symmetry Difference (BFSD)-EIT can detect, localize and identify unilateral perturbations in symmetric scenes. Here, we test the viability and robustness of BFSD-EIT in stroke diagnosis. METHODS: A realistic 4-layer Finite Element Method (FEM) head model with and without bleed and clot lesions is developed. Performance is assessed with test parameters including: measurement noise, electrode placement errors, contact impedance errors, deviations in assumed tissue conductivity, deviations in assumed anatomy, and a frequency-dependent background. A final test is performed using ischemic patient data. Results are assessed using images and quantitative metrics. RESULTS: BFSD-EIT may be feasible for stroke diagnosis if a signal-to-noise ratio (SNR) of ≥60 dB is achievable. Sensitivity to errors in electrode positioning is seen with a tolerance of only ±5 mm, but a tolerance of up to ±30 mm is possible if symmetry is maintained between symmetrically opposite partner electrodes. The technique is robust to errors in contact impedance and assumed tissue conductivity up to at least ±50%. Asymmetric internal anatomy affects performance but may be tolerable for tissues with frequency-dependent conductivity. Errors in assumed external geometry marginally affect performance. A frequency-dependent background does not affect performance with carefully chosen frequency points or use of multiple frequency points across a band. The Global Left-Hand Side (LHS) & Right-Hand Side (RHS) Mean Intensity metric is particularly robust to errors. CONCLUSION: BFSD-EIT is a promising technique for stroke diagnosis, provided parameters are within the tolerated ranges. SIGNIFICANCE: BFSD-EIT may prove an important step forward in imaging of static scenes such as stroke.
Barry McDermott, Martin O'Halloran, James Avery, Emily Porter
IEEE J. Biomed. Health Informatics3
2019 Shape Sensing of Variable Stiffness Soft Robots using Electrical Impedance Tomography
abstract
Soft robotic systems offer benefits over traditional rigid systems through reduced contact trauma with soft tissues and by enabling access through tortuous paths in minimally invasive surgery. However, the inherent deformability of soft robots places both a greater onus on accurate modelling of their shape, and greater challenges in realising intraoperative shape sensing. Herein we present a proprioceptive (self-sensing) soft actuator, with an electrically conductive working fluid. Electrical impedance measurements from up to six electrodes enabled tomographic reconstructions using Electrical Impedance Tomography (EIT). A new Frequency Division Multiplexed (FDM) EIT system was developed capable of measurements of 66 dB SNR with 20 ms temporal resolution. The concept was examined in two two-degree-of-freedom designs: a hydraulic hinged actuator and a pneumatic finger actuator with hydraulic beams. Both cases demonstrated that impedance measurements could be used to infer shape changes, and EIT images reconstructed during actuation showed distinct patterns with respect to each degree of freedom (DOF). Whilst there was some mechanical hysteresis observed, the repeatability of the measurements and resultant images was high. The results show the potential of FDM-EIT as a low-cost, low profile shape sensor in soft robots.
James Avery, Mark Runciman, Ara Darzi, George P. Mylonas
ICRA1
2016 Fusion of Parallel Array Operations
abstract
We address the problem of fusing array operations based on criteria such as shape compatibility, data reuse, and minimizing for data reuse, the fusion problem has been formulated as a static weighted graph partitioning problem (known as the Weighted Loop Fusion problem). We show that this scheme cannot accurately track data reuse between multiple independent loops, since it overestimates total data reuse of certain cases. Our formulation in terms of partitions allows use of realistic cost functions that can track resource usage accurately. We give correctness proofs, and prove that WSP can maximize data reuse in programs exactly, in contrast to prior work.
Mads Ruben Burgdorff Kristensen, Simon Andreas Frimann Lund, Troels Blum, James Avery
PACT4