Displaying all 7 publications

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  1. Abdullah MZ, Awang MS, Tan YC, Abdullah JM
    J Neurol Surg A Cent Eur Neurosurg, 2014 Mar;75(2):155-7.
    PMID: 23636911 DOI: 10.1055/s-0032-1330954
    The study assesses the capability and accuracy of a robotic arm to perform burr holes.
    Matched MeSH terms: Robotics/methods*
  2. Yap HJ, Taha Z, Dawal SZ, Chang SW
    PLoS One, 2014;9(10):e109692.
    PMID: 25360663 DOI: 10.1371/journal.pone.0109692
    Traditional robotic work cell design and programming are considered inefficient and outdated in current industrial and market demands. In this research, virtual reality (VR) technology is used to improve human-robot interface, whereby complicated commands or programming knowledge is not required. The proposed solution, known as VR-based Programming of a Robotic Work Cell (VR-Rocell), consists of two sub-programmes, which are VR-Robotic Work Cell Layout (VR-RoWL) and VR-based Robot Teaching System (VR-RoT). VR-RoWL is developed to assign the layout design for an industrial robotic work cell, whereby VR-RoT is developed to overcome safety issues and lack of trained personnel in robot programming. Simple and user-friendly interfaces are designed for inexperienced users to generate robot commands without damaging the robot or interrupting the production line. The user is able to attempt numerous times to attain an optimum solution. A case study is conducted in the Robotics Laboratory to assemble an electronics casing and it is found that the output models are compatible with commercial software without loss of information. Furthermore, the generated KUKA commands are workable when loaded into a commercial simulator. The operation of the actual robotic work cell shows that the errors may be due to the dynamics of the KUKA robot rather than the accuracy of the generated programme. Therefore, it is concluded that the virtual reality based solution approach can be implemented in an industrial robotic work cell.
    Matched MeSH terms: Robotics/methods*
  3. Abdullah BJ, Yeong CH, Goh KL, Yoong BK, Ho GF, Yim CC, et al.
    Eur Radiol, 2015 Jan;25(1):246-57.
    PMID: 25189152 DOI: 10.1007/s00330-014-3391-7
    OBJECTIVE: This study aimed to assess the technical success, radiation dose, safety and performance level of liver thermal ablation using a computed tomography (CT)-guided robotic positioning system.

    METHODS: Radiofrequency and microwave ablation of liver tumours were performed on 20 patients (40 lesions) with the assistance of a CT-guided robotic positioning system. The accuracy of probe placement, number of readjustments and total radiation dose to each patient were recorded. The performance level was evaluated on a five-point scale (5-1: excellent-poor). The radiation doses were compared against 30 patients with 48 lesions (control) treated without robotic assistance.

    RESULTS: Thermal ablation was successfully completed in 20 patients with 40 lesions and confirmed on multiphasic contrast-enhanced CT. No procedure related complications were noted in this study. The average number of needle readjustment was 0.8 ± 0.8. The total CT dose (DLP) for the entire robotic assisted thermal ablation was 1382 ± 536 mGy.cm, while the CT fluoroscopic dose (DLP) per lesion was 352 ± 228 mGy.cm. There was no statistically significant (p > 0.05) dose reduction found between the robotic-assisted versus the conventional method.

    CONCLUSION: This study revealed that robotic-assisted planning and needle placement appears to be safe, with high accuracy and a comparable radiation dose to patients.

    KEY POINTS: • Clinical experience on liver thermal ablation using CT-guided robotic system is reported. • The technical success, radiation dose, safety and performance level were assessed. • Thermal ablations were successfully performed, with an average performance score of 4.4/5.0. • Robotic-assisted ablation can potentially increase capabilities of less skilled interventional radiologists. • Cost-effectiveness needs to be proven in further studies.

    Matched MeSH terms: Robotics/methods*
  4. Lim MS, Melich G, Min BS
    Surg Endosc, 2013 Mar;27(3):1021.
    PMID: 23052525 DOI: 10.1007/s00464-012-2549-0
    Potential morbidities related to multiport laparoscopic surgeries have led to the current excitement about single-incision laparoscopic techniques. However, multiport laparoscopy is technically demanding and ergonomically challenging. We present our technique of using the Alexis wound retractor and a surgical glove to fashion an access port and the da Vinci surgical robot to perform single-incision anterior resection.
    Matched MeSH terms: Robotics/methods*
  5. Al-Quraishi MS, Ishak AJ, Ahmad SA, Hasan MK, Al-Qurishi M, Ghapanchizadeh H, et al.
    Med Biol Eng Comput, 2017 May;55(5):747-758.
    PMID: 27484411 DOI: 10.1007/s11517-016-1551-4
    Electromyography (EMG)-based control is the core of prostheses, orthoses, and other rehabilitation devices in recent research. Nonetheless, EMG is difficult to use as a control signal given the complex nature of the signal. To overcome this problem, the researchers employed a pattern recognition technique. EMG pattern recognition mainly involves four stages: signal detection, preprocessing feature extraction, dimensionality reduction, and classification. In particular, the success of any pattern recognition technique depends on the feature extraction stage. In this study, a modified time-domain features set and logarithmic transferred time-domain features (LTD) were evaluated and compared with other traditional time-domain features set (TTD). Three classifiers were employed to assess the two feature sets, namely linear discriminant analysis (LDA), k nearest neighborhood, and Naïve Bayes. Results indicated the superiority of the new time-domain feature set LTD, on conventional time-domain features TTD with the average classification accuracy of 97.23 %. In addition, the LDA classifier outperformed the other two classifiers considered in this study.
    Matched MeSH terms: Robotics/methods
  6. Dawood F, Loo CK
    Int J Neural Syst, 2018 May;28(4):1750038.
    PMID: 29022403 DOI: 10.1142/S0129065717500381
    Imitation learning through self-exploration is essential in developing sensorimotor skills. Most developmental theories emphasize that social interactions, especially understanding of observed actions, could be first achieved through imitation, yet the discussion on the origin of primitive imitative abilities is often neglected, referring instead to the possibility of its innateness. This paper presents a developmental model of imitation learning based on the hypothesis that humanoid robot acquires imitative abilities as induced by sensorimotor associative learning through self-exploration. In designing such learning system, several key issues will be addressed: automatic segmentation of the observed actions into motion primitives using raw images acquired from the camera without requiring any kinematic model; incremental learning of spatio-temporal motion sequences to dynamically generates a topological structure in a self-stabilizing manner; organization of the learned data for easy and efficient retrieval using a dynamic associative memory; and utilizing segmented motion primitives to generate complex behavior by the combining these motion primitives. In our experiment, the self-posture is acquired through observing the image of its own body posture while performing the action in front of a mirror through body babbling. The complete architecture was evaluated by simulation and real robot experiments performed on DARwIn-OP humanoid robot.
    Matched MeSH terms: Robotics/methods*
  7. Patil NN, Mottrie A, Sundaram B, Patel VR
    Urology, 2008 Jul;72(1):47-50; discussion 50.
    PMID: 18384858 DOI: 10.1016/j.urology.2007.12.097
    To report the collective experience of three multinational institutions with the use of robotics to evaluate and treat complex distal ureteral obstruction.
    Matched MeSH terms: Robotics/methods*
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