OBJECTIVE: This study aims to determine the background of recent studies on wheelchair control based on BCI for disability and map the literature survey into a coherent taxonomy. The study intends to identify the most important aspects in this emerging field as an impetus for using BCI for disability in electric-powered wheelchair (EPW) control, which remains a challenge. The study also attempts to provide recommendations for solving other existing limitations and challenges.
METHODS: We systematically searched all articles about EPW control based on BCI for disability in three popular databases: ScienceDirect, IEEE and Web of Science. These databases contain numerous articles that considerably influenced this field and cover most of the relevant theoretical and technical issues.
RESULTS: We selected 100 articles on the basis of our inclusion and exclusion criteria. A large set of articles (55) discussed on developing real-time wheelchair control systems based on BCI for disability signals. Another set of articles (25) focused on analysing BCI for disability signals for wheelchair control. The third set of articles (14) considered the simulation of wheelchair control based on BCI for disability signals. Four articles designed a framework for wheelchair control based on BCI for disability signals. Finally, one article reviewed concerns regarding wheelchair control based on BCI for disability signals.
DISCUSSION: Since 2007, researchers have pursued the possibility of using BCI for disability in EPW control through different approaches. Regardless of type, articles have focused on addressing limitations that impede the full efficiency of BCI for disability and recommended solutions for these limitations.
CONCLUSIONS: Studies on wheelchair control based on BCI for disability considerably influence society due to the large number of people with disability. Therefore, we aim to provide researchers and developers with a clear understanding of this platform and highlight the challenges and gaps in the current and future studies.
METHODS: We report our preliminary experience of performing radiofrequency ablation of the liver using a robotic-assisted CT guidance system on 11 patients (17 lesions).
RESULTS/CONCLUSION: Robotic-assisted planning and needle placement appears to have high accuracy, is technically easier than the non-robotic-assisted procedure, and involves a significantly lower radiation dose to both patient and support staff.
KEY POINTS: • An early experience of robotic-assisted radiofrequency ablation is reported • Robotic-assisted RFA improves accuracy of hepatic lesion targeting • Robotic-assisted RFA makes the procedure technically easier with significant lower radiation dose.
Summary: The first Asia Pacific consensus meeting on laparoscopic liver resection for HCC was held in July 2016 in Hong Kong. A group of expert liver surgeons with experience in both open and laparoscopic hepatectomy for HCC convened to formulate recommendations on the role and perspective of laparoscopic liver resection for primary liver cancer. The recommendations consolidate the most recent evidence pertaining to laparoscopic hepatectomy together with the latest thinking of practicing clinicians involved in laparoscopic hepatectomy, and give detailed guidance on how to deploy the treatment effectively for patients in need.
Key Message: The panel of experts gathered evidence and produced recommendations providing guidance on the safe practice of laparoscopic hepatectomy for patients with HCC and cirrhosis. The inherent advantage of the laparoscopic approach may result in less blood loss if the procedure is performed in experienced centers. The laparoscopic approach to minor hepatectomy, particularly left lateral sectionectomy, is a preferred practice for HCC at experienced centers. Laparoscopic major liver resection for HCC remains a technically challenging operation, and it should be carried out in centers of excellence. There is emerging evidence that laparoscopic liver resection produces a better oncological outcome for HCC when compared with radiofrequency ablation, particularly when the lesions are peripherally located. Augmented features in laparoscopic liver resection, including indocyanine green fluorescence, 3D laparoscopy, and robot, will become important tools of surgical treatment in the near future. A combination of all of these features will enhance the experience of the surgeons, which may translate into better surgical outcomes. This is the first consensus workforce on laparoscopic liver resection for HCC, which is a unique condition that occurs in the Asia Pacific region.
OBJECTIVES: This paper discusses activity detection and analysis (ADA) using security robots in workplaces. The application scenario of this method relies on processing image and sensor data for event and activity detection. The events that are detected are classified for its abnormality based on the analysis performed using the sensor and image data operated using a convolution neural network. This method aims to improve the accuracy of detection by mitigating the deviations that are classified in different levels of the convolution process.
RESULTS: The differences are identified based on independent data correlation and information processing. The performance of the proposed method is verified for the three human activities, such as standing, walking, and running, as detected using the images and sensor dataset.
CONCLUSION: The results are compared with the existing method for metrics accuracy, classification time, and recall.
OBJECTIVES: In this paper, the Advanced Human-Robot Collaboration Model (AHRCM) approach is to enhance the risk assessment and to make the workplace involving security robots. The robots use perception cameras and generate scene diagrams for semantic depictions of their environment. Furthermore, Artificial Intelligence (AI) and Information and Communication Technology (ICT) have utilized to develop a highly protected security robot based risk management system in the workplace.
RESULTS: The experimental results show that the proposed AHRCM method achieves high performance in human-robot mutual adaption and reduce the risk.
CONCLUSION: Through an experiment in the field of human subjects, demonstrated that policies based on the proposed model improved the efficiency of the human-robot team significantly compared with policies assuming complete human-robot adaptation.
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.