918 resultados para ROBOTIC ARM
Resumo:
Peer reviewed
Resumo:
Peer reviewed
Resumo:
Funding and trial registration: Scottish Government Chief Scientist Office grant CZH/3/17. ClinicalTrials.gov registration NCT01602705.
Resumo:
Peer reviewed
Resumo:
Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.
Resumo:
Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.
Resumo:
Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.
Resumo:
In this paper a surgical robotic device for cochlear implantation surgery is described that is able to discriminate tissue interfaces and other controlling parameters ahead of a drill tip. The advantage in surgery is that tissues at interfaces can be preserved. The smart tool is able to control interaction with respect to the flexing tissue to avoid penetration control the extent of protrusion with respect to the real-time position of the tissue. To interpret drilling conditions, and conditions leading up to breakthrough at a tissue interface, the sensing scheme used enables discrimination between the variety of conditions posed in the drilling environment. The result is a robust fully autonomous system able to respond to tissue type, behaviour and deflection in real-time. The paper describes the robotic tool that has been designed to be used in the surgical environment where it has been used in the operating room.
Resumo:
Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.
Resumo:
Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.
Resumo:
Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.
Resumo:
The world's oceans are slowly becoming more acidic. In the last 150 yr, the pH of the oceans has dropped by ~0.1 units, which is equivalent to a 25% increase in acidity. Modelling predicts the pH of the oceans to fall by 0.2 to 0.4 units by the year 2100. These changes will have significant effects on marine organisms, especially those with calcareous skeletons such as echinoderms. Little is known about the possible long-term impact of predicted pH changes on marine invertebrate larval development. Here we predict the consequences of increased CO2 (corresponding to pH drops of 0.2 and 0.4 units) on the larval development of the brittlestar Ophiothrix fragilis, which is a keystone species occurring in high densities and stable populations throughout the shelf seas of northwestern Europe (eastern Atlantic). Acidification by 0.2 units induced 100% larval mortality within 8 d while control larvae showed 70% survival over the same period. Exposure to low pH also resulted in a temporal decrease in larval size as well as abnormal development and skeletogenesis (abnormalities, asymmetry, altered skeletal proportions). If oceans continue to acidify as expected, ecosystems of the Atlantic dominated by this keystone species will be seriously threatened with major changes in many key benthic and pelagic ecosystems. Thus, it may be useful to monitor O. fragilis populations and initiate conservation if needed.
Resumo:
Stroke is a prevalent disorder with immense socioeconomic impact. A variety of chronic neurological deficits result from stroke. In particular, sensorimotor deficits are a significant barrier to achieving post-stroke independence. Unfortunately, the majority of pre-clinical studies that show improved outcomes in animal stroke models have failed in clinical trials. Pre-clinical studies using non-human primate (NHP) stroke models prior to initiating human trials are a potential step to improving translation from animal studies to clinical trials. Robotic assessment tools represent a quantitative, reliable, and reproducible means to assess reaching behaviour following stroke in both humans and NHPs. We investigated the use of robotic technology to assess sensorimotor impairments in NHPs following middle cerebral artery occlusion (MCAO). Two cynomolgus macaques underwent transient MCAO for 90 minutes. Approximately 1.5 years following the procedure these NHPs and two non-stroke control monkeys were trained in a reaching task with both arms in the KINARM exoskeleton. This robot permits elbow and shoulder movements in the horizontal plane. The task required NHPs to make reaching movements from a centrally positioned start target to 1 of 8 peripheral targets uniformly distributed around the first target. We analyzed four movement parameters: reaction time, movement time (MT), initial direction error (IDE), and number of speed maxima to characterize sensorimotor deficiencies. We hypothesized reduced performance in these attributes during a neurobehavioural task with the paretic limb of NHPs following MCAO compared to controls. Reaching movements in the non-affected limbs of control and experimental NHPs showed bell-shaped velocity profiles. In contrast, the reaching movements with the affected limbs were highly variable. We found distinctive patterns in MT, IDE, and number of speed peaks between control and experimental monkeys and between limbs of NHPs with MCAO. NHPs with MCAO demonstrated more speed peaks, longer MTs, and greater IDE in their paretic limb compared to controls. These initial results qualitatively match human stroke subjects’ performance, suggesting that robotic neurobehavioural assessment in NHPs with stroke is feasible and could have translational relevance in subsequent human studies. Further studies will be necessary to replicate and expand on these preliminary findings.
Resumo:
This paper describes the design, tuning, and extensive field testing of an admittance-based Autonomous Loading Controller (ALC) for robotic excavation. Several iterations of the ALC were tuned and tested in fragmented rock piles—similar to those found in operating mines—by using both a robotic 1-tonne capacity Kubota R520S diesel-hydraulic surface loader and a 14-tonne capacity Atlas Copco ST14 underground load-haul-dump (LHD) machine. On the R520S loader, the ALC increased payload by 18 % with greater consistency, although with more energy expended and longer dig times when compared with digging at maximum actuator velocity. On the ST14 LHD, the ALC took 61 % less time to load 39 % more payload when compared to a single manual operator. The manual operator made 28 dig attempts by using three different digging strategies, and had one failed dig. The tuned ALC made 26 dig attempts at 10 and 11 MN target force levels. All 10 11 MN digs succeeded while 6 of the 16 10 MN digs failed. The results presented in this paper suggest that the admittance-based ALC is more productive and consistent than manual operators, but that care should be taken when detecting entry into the muck pile