966 results found
Deligianni F, Ravi D, Roots S, et al., Pervasive monitoring of mental health for preventing financial distress, Body Sensor Networks Conference (BSN’17), Publisher: IEEE
Mental health disorders are rankedamong the top twenty main causes of disability worldwide. It was found that thereis an intriguing relationship between mental health problems and financial difficulties.Current technology uses mobile apps for self-monitoring of mental health conditions with a potential to avoid debt crisis caused by mental illness. In this paper, we propose the use of a wearable sensor as an objective evaluation tool for monitoring the emotional well-being of the subject. By fusing the sensory data with financial data, an intelligent self-guard system is proposed for preventing excessive spending caused by mental condition.
Deligianni F, Wong CW, Lo B, et al., A fusion framework to estimate plantar ground force distributions and ankle dynamics, Information Fusion, ISSN: 1566-2535
Grammatikopoulou M, Zhang L, Yang GZ, Depth estimation of optically transparent laser-driven microrobots, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Publisher: IEEE
Six degree-of-freedom (DoF) pose feedback isessential for the development of closed-loop control techniquesfor microrobotics. This paper presents two methods for depthestimation of transparent microrobots inside an Optical Tweez-ers (OT) setup using image sharpness measurements and model-based tracking. Thex-yposition and the 3D orientation ofthe object are estimated using online model-based templatematching. The proposed depth estimation methodologies arevalidated experimentally by comparing the results with theground truth.
Gras G, Payne CJ, Hughes M, et al., A Flexible Robotic Probe for Osteoarthritis Intervention, Medical Engineering Centres Annual Meeting and Bioengineering (MECbioeng) 2014
Huang B, Ye M, Lee S, et al., A Vision-Guided Multi-Robot Cooperation Framework for Learning-By-Demonstration and Task Reproduction, IEEE/RSJ International Conference on Intelligent Robots and Systems, Publisher: IEEE
This paper presents a multi-robot system for manufacturingpersonalized medical stent graft. The proposed system is a modularizedsystem with three major components: a (personalized) mandrel module,a bimanual sewing module and a vision module. The mandrel module in-corporates the personalization of the product, while the bimanual sewingmodule adopts a learning-by-demonstration approach to transfer humanhand sewing skills to the robots. The human demonstrations were firstlyobserved by the vision module, and then encoded using a statisticalmodel to generate the reference motion trajectory. During autonomousrobot sewing, the vision module plays the role of coordinating multi-robot collaboration. Experiment results show that the robots can sewwith sub-millimeter accuracy and adapt to multiple personalized stentdesigns. The proposed system is generalizable to other manipulationtasks, especially for mass production of customized products and wherebimanual or multi-robot cooperation is required.
Leff DR, Shetty K, Yang GZ, et al., Persistent Attentional Demands Despite Laparoscopic Skills Acquisition, JAMA Surgery, ISSN: 2168-6262
Marcus HJ, Hughes-Hallett A, Payne CJ, et al., TRENDS IN THE DIFFUSION OF ROBOTIC SURGERY: A RETROSPECTIVE OBSERVATIONAL STUDY, International Journal of Medical Robotics and Computer Assisted Surgery, ISSN: 1478-5951
Modi HN, Singh H, Yang G, et al., A decade of imaging surgeons' brain function (Part II): a systematic review of applications for technical and non-technical skills assessment, Surgery, ISSN: 1532-7361
Background: Functional neuroimaging technologies enable assessment of operator brain function, and can deepen our understanding of skills learning, ergonomic optima and cognitive processes in surgeons. Whilst there has been a critical mass of data detailing surgeons’ brain function, this literature has not been systematically reviewed.Methods: A systematic search of original neuroimaging studies assessing surgeons’ brain function, and published up until November 2016, was conducted using Medline, Embase and PsycINFO databases.Results: Twenty-seven studies fulfilled the inclusion criteria, including three feasibility studies, fourteen studies exploring the neural correlates of technical skill acquisition, and the remainder investigating brain function in the context of intraoperative decision-making (n=1), neurofeedback training (n=1), robot-assisted technology (n=5), and surgical teaching (n=3). Early stages of learning open surgical tasks (knot-tying) are characterised by prefrontal cortical (PFC) activation which subsequently attenuates with deliberate practice. However, with complex laparoscopic skills (intra-corporeal suturing), PFC engagement requires substantial training and attenuation occurs over a longer time-course, following years of refinement. Neurofeedback and interventions that improve neural efficiency may enhance technical performance and skills learning. Conclusions: Imaging surgeons’ brain function has identified neural signatures of expertise which might help inform objective assessment and selection processes. Interventions which improve neural efficiency may target skill-specific brain regions and augment surgical performance.
Seneci CA, Shang JS, Yang GZY, Design and FEM Simulation of a Miniaturized WristedSurgical Grasper, Hamlyn Symposium on Surgical Robotics 2013
Seneci CA, shang JS, Yang GZY, Design of a bimanual end-effector for an endoscopicsurgical robot., The Hamlyn Symposium on Medical Robotics 2014.
Wisanuvej P, Gras GG, Leibrandt KL, et al., Master Manipulator Designed for Highly Articulated Robotic Instruments in Single Access Surgery, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Publisher: IEEE
The performance of a master-slave robotic system depends significantly on the ergonomics and the capability of its master device to correctly interface the user with the slave robot. Master manipulators generating commands in task space represent a commonly adopted solution for controlling a range of slave robots while retaining an ergonomic design. However, these devices present several drawbacks, such as requiring the use of clutching mechanics to compensate for the mismatch between slave and master workspaces, and the lack of capability to intuitively transmit important information such as specific joint limits to the user. In this paper, a novel joint-space master manipulator is presented. This manipulator emulates the kinematic structure of highly flexible surgical instruments which it is designed to control. This system uses 6 active degrees of freedom to compensate for its own weight, as well as to provide force feedback corresponding to the slave robot's joint limits. A force/torque sensor integrated at the end effector is used to relay user-generated forces and torques directly to specific joints. This is performed to counteract the friction stemming from structural constraints imposed by the kinematic design of the instruments. Finally, a usability study is carried out to test the validity of the system, proving that the instruments can be intuitively controlled even at the extremities of the workspace.
Zhang L, Ye M, Giataganas P, et al., Autonomous Scanning for Endomicroscopic Mosaicing and 3D Fusion, IEEE International Conference on Robotics and Automation
Zuo SZ, Hughes MH, Giataganas PG, et al., Development of a large area scanner for intraoperative breast endomicroscopy., In 2014 IEEE International Conference on Robotics and Automation (ICRA)
berthet-rayne PBR, Hubot: A Three State Human-Robot Collaborative Framework for Bimanual Surgical Tasks Based on Learned Models, IEEE International Conference on Robotics and Automation (ICRA)
cundy TPC, patel NP, shang JS, et al., Per-Oral Endoscopic Cardiomyotomy and Pyloromyotomy using a Flexible Snake Robot–Proof of Concept with a Porcine Model., In The Hamlyn Symposium on Medical Robotics
king HK, shang JS, liu JL, et al., Micro-IGES Robot for Transanal Robotic Microsurgery., In The Hamlyn Symposium on Medical Robotics.
patel NP, cundy TPC, shang JS, et al., Endoscopic Submucosal Dissection for Gastric Lesions using a Flexible Snake Robot–Early Assessment and Feasibility Study., In The Hamlyn Symposium on Medical Robotics
patel NP, seneci CS, yang GZY, et al., Flexible platforms for natural orifice transluminal and endoluminal surgery. Endoscopy International Open, 2(02), E117-E123., Endoscopy International Open
zhang ZZ, shang JS, Seneci CA, et al., Snake robot shape sensing using microinertial sensors., In 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
zuo SZ, hughes MH, Seneci CA, et al., Toward Intraoperative Breast Endomicroscopy With a Novel Surface-Scanning Device., IEEE Transactions on Biomedical Engineering
Orihuela-Espina F, Leff DR, James DRC, et al., 2018, Imperial College near infrared spectroscopy neuroimaging analysis framework., Neurophotonics, Vol: 5, ISSN: 2329-423X
This paper describes the Imperial College near infrared spectroscopy neuroimaging analysis (ICNNA) software tool for functional near infrared spectroscopy neuroimaging data. ICNNA is a MATLAB-based object-oriented framework encompassing an application programming interface and a graphical user interface. ICNNA incorporates reconstruction based on the modified Beer-Lambert law and basic processing and data validation capabilities. Emphasis is placed on the full experiment rather than individual neuroimages as the central element of analysis. The software offers three types of analyses including classical statistical methods based on comparison of changes in relative concentrations of hemoglobin between the task and baseline periods, graph theory-based metrics of connectivity and, distinctively, an analysis approach based on manifold embedding. This paper presents the different capabilities of ICNNA in its current version.
Anastasova S, Crewther B, Bembnowicz P, et al., 2017, A wearable multisensing patch for continuous sweat monitoring (vol 93, pg 139, 2017), BIOSENSORS & BIOELECTRONICS, Vol: 94, Pages: 730-730, ISSN: 0956-5663
Anastasova S, Crewther B, Bembnowicz P, et al., 2017, A wearable multisensing patch for continuous sweat monitoring, BIOSENSORS & BIOELECTRONICS, Vol: 93, Pages: 139-145, ISSN: 0956-5663
Andreu-Perez J, Garcia-Gancedo L, McKinnell J, et al., 2017, Developing Fine-Grained Actigraphies for Rheumatoid Arthritis Patients from a Single Accelerometer Using Machine Learning, SENSORS, Vol: 17, ISSN: 1424-8220
Avci E, Grammatikopoulou M, Yang GZ, 2017, Laser-Printing and 3D Optical-Control of Untethered Microrobots, Advanced Optical Materials
© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. The two-photon photo-polymerization (2PP) method is used to manufacture an articulated micro-robot for indirect manipulation of cellular structures under laser light. To tackle the stickiness issue between the components of the proposed mechanism, optimizing the contact surface areas is carried out. A step-by-step procedure to manufacture and control an untethered articulated micro-robot under laser light is demonstrated. The manufacture and optical control of a floating multi-component micro-mechanism has not been achieved before. This is significant because it is anticipated that the articulated microrobots could be used in complex biomedical applications where control in 3D space is required such as single-cell analysis, embryo injection, polar-body biopsy, nuclear transplantation, and multi-dimensional imaging for microsurgery.
Berthelot M, Yang GZ, Lo B, 2017, Preliminary study for hemodynamics monitoring using a wearable device network, Pages: 115-118
© 2017 IEEE. Blood flow, posture and phenotype (such as age, sex, smoking habit or physical activity) are closely related to vascular health. Episodic monitoring of the vascular system in clinical setting can lead to late diagnose. Inexpensive wearable devices for continuous monitoring of vascular parameters have been widely used, however, they often have limitations in data interpretation: changes in the environment setting can significantly affect the meaning of the results. This paper proposes a low cost networked body worn sensors for real-Time analysis of hemodynamics and reports preliminary results on the relation between blood flow (measured through pulse arrival time (PAT)), the effect of postures and age ranges based on experiments with 13 volunteers of different age ranges ( < 25 years old and > 50 years old). Standing, supine and sitting postures were investigated while photoplethysmograph (PPG) sensors were placed at different locations (ear, wrist and ankle). Results show the PAT changes according to the investigated locations and postures for both age group. Also, the average PAT values of the older group are generally higher than those of the younger group. In the older group, the average PAT value is higher for the supine posture than that of the sitting posture which is itself higher than that of the standing posture. In the younger group, the average PAT is higher in supine than that of the sitting and standing postures which have similar average PAT values. This indicates that hemodynamics vary with posture and age.
Chi W, Rafii-Tari H, Payne CJ, et al., 2017, A learning based training and skill assessment platform with haptic guidance for endovascular catheterization, Pages: 2357-2363, ISSN: 1050-4729
© 2017 IEEE. Increasing demands in endovascular intervention have motivated technical skill training and competency-based measures of performance. However, there are no well-established online metrics for technical skill assessment; few studies have explored operator behavioral patterns from catheter motion and operator hand motions. This paper proposes a platform for active online training and objective assessment of endovascular skills, through learning optimum catheter motions from multiple demonstrations. An ungrounded hand-held haptic device for providing intuitive haptic guidance to novice users based on this learnt information is also proposed. Statistical models are implemented to extract the underlying catheter motion patterns, and utilize them for performance evaluation and haptic guidance. The results show significant improvements in endovascular navigation for inexperienced operators. Finer catheter motions were achieved with the provided haptic guidance. The results suggest that the proposed platform can be integrated into current clinical training setups, and motivate the improvement of endovascular training platforms with better realism.
Constantinescu M, Lee SL, Ernst S, et al., 2017, Statistical atlases for electroanatomical mapping of cardiac arrhythmias, Pages: 301-310, ISSN: 0302-9743
© Springer International Publishing AG 2017. Electroanatomical mapping is a mandatory time-consuming planning step in cardiac catheter ablation. In practice, interventional cardiologists target specific endocardial areas for mapping based on personal experience, general electrophysiology principles, and preoperative anatomical scans. Effective fusion of all available information towards a useful mapping strategy has not been standardised and achieving the optimal map within time and space constraints is challenging. In this paper, a novel framework for computing optimal endocardial mapping locations in patients with congenital heart disease (CHD) is proposed. The method is based on a statistical electroanatomical model (SEAM) which is instantiated from preoperative anatomy in order to achieve an initial prediction of the electrical map. Simultaneously, the anatomical areas with the highest frequency of mapping among the similar cases in the dataset are detected and a classifier is trained to filter these points based on the electroanatomical data. The framework was tested in an iterative process of adding mapping points to the SEAM and computing the instantiation error, with retrospective clinical data of 66 CHD cases available.
Freer DR, Liu J, Yang GZ, 2017, Optimization of EMG movement recognition for use in an upper limb wearable robot, Pages: 202-205
© 2017 IEEE. To functionally aid patients suffering from neurological disorder, a 3 degrees-of-freedom (DoF) upper limb wearable robot is presented (Fig. 1). In order to provide seamless user assistance, the intention of the wearer must be determined. As a sensing mechanism, electromyographic (EMG) signals have commonly been used to estimate human movement. In this study, the effectiveness of movement recognition using a generalized 8-port EMG sensor (Myo Armband) around the forearm was evaluated. Four fundamental movements of the arm (wrist flexion/extension and forearm pronation/supination) were classified using a neural network (NN) with a single hidden layer. The classification method was optimized through analysis of pre-processing algorithms and window size (0.25 to 1 second) to reduce computational expense and maintain classification accuracy. Through these accomplishments, significant groundwork has been provided for the development of a robust and non-invasive solution to tremor of the upper limb.
Gambini J, Quinn T, Vila R, et al., 2017, Upgraded portable Indocyanine Green (ICG) detection system - towards Image Guided Cancer Surgery, Annual Meeting of the Society-of-Nuclear-Medicine-and-Molecular-Imaging (SNMMI), Publisher: SOC NUCLEAR MEDICINE INC, ISSN: 0161-5505
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