EEG-controlled tele-grasping for undefined objects
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ABSTRACT:
SUBMITTER: Kim M
PROVIDER: S-EPMC10770246 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
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Project description:Due to noisy motor commands and imprecise and ambiguous sensory information, there is often substantial uncertainty about the relative location between our body and objects in the environment. Little is known about how well people manage and compensate for this uncertainty in purposive movement tasks like grasping. Grasping objects requires reach trajectories to generate object-fingers contacts that permit stable lifting. For objects with position uncertainty, some trajectories are more efficient than others in terms of the probability of producing stable grasps. We hypothesize that people attempt to generate efficient grasp trajectories that produce stable grasps at first contact without requiring post-contact adjustments. We tested this hypothesis by comparing human uncertainty compensation in grasping objects against optimal predictions. Participants grasped and lifted a cylindrical object with position uncertainty, introduced by moving the cylinder with a robotic arm over a sequence of 5 positions sampled from a strongly oriented 2D Gaussian distribution. Preceding each reach, vision of the object was removed for the remainder of the trial and the cylinder was moved one additional time. In accord with optimal predictions, we found that people compensate by aligning the approach direction with covariance angle to maintain grasp efficiency. This compensation results in higher probability to achieve stable grasps at first contact than non-compensation strategies in grasping objects with directional position uncertainty, and the results provide the first demonstration that humans compensate for uncertainty in a complex purposive task.
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Project description:A robot's ability to grasp moving objects depends on the availability of real-time sensor data in both the far-field and near-field of the gripper. This research investigates the potential contribution of tactile sensing to a task of grasping an object in motion. It was hypothesised that combining tactile sensor data with a reactive grasping strategy could improve its robustness to prediction errors, leading to a better, more adaptive performance. Using a two-finger gripper, we evaluated the performance of two algorithms to grasp a ball rolling on a horizontal plane at a range of speeds and gripper contact points. The first approach involved an adaptive grasping strategy initiated by tactile sensors in the fingers. The second strategy initiated the grasp based on a prediction of the position of the object relative to the gripper, and provided a proxy to a vision-based object tracking system. It was found that the integration of tactile sensor feedback resulted in a higher observed grasp robustness, especially when the gripper-ball contact point was displaced from the centre of the gripper. These findings demonstrate the performance gains that can be attained by incorporating near-field sensor data into the grasp strategy and motivate further research on how this strategy might be expanded for use in different manipulator designs and in more complex grasp scenarios.
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Project description:Grasping relies on a network of parieto-frontal areas lying on the dorsolateral and dorsomedial parts of the hemispheres. However, the initiation and sequencing of voluntary actions also requires the contribution of mesial premotor regions, particularly the pre-supplementary motor area F6. We recorded 233 F6 neurons from 2 monkeys with chronic linear multishank neural probes during reaching-grasping visuomotor tasks. We showed that F6 neurons play a role in the control of forelimb movements and some of them (26%) exhibit visual and/or motor specificity for the target object. Interestingly, area F6 neurons form 2 functionally distinct populations, showing either visually-triggered or movement-related bursts of activity, in contrast to the sustained visual-to-motor activity displayed by ventral premotor area F5 neurons recorded in the same animals and with the same task during previous studies. These findings suggest that F6 plays a role in object grasping and extend existing models of the cortical grasping network.
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Project description:Efficiently manipulating objects in a group state poses an emerging challenge for soft robot hands. Overcoming this problem necessitates the development of hands with highly stable structures to bear heavy loads and highly compliant designs to universally adapt to various object geometries. This study introduces a novel platform for the development of robot hands aimed at manipulating multiple objects in each trial. In this setup, the objects come into soft contact with an elastic wire affixed to the finger skeletons. This combination results in a harmonious hybrid finger, inheriting both the soft, flexible properties of the wire and the robust stability provided by the finger skeleton. To facilitate this approach, a theoretical model was proposed to estimate the kinematics of manipulating multiple objects using wiring-based fingers. Based on this model, we designed a hybrid gripper comprising two wiring-based fingers for conducting experimental evaluations in manipulating four groups of samples: a pair of bevel gears, a pair of bevel gears plus a pneumatic connector, a pair of glue bottles, and a pair of silicon bottles. The experimental results demonstrated that our proposed gripper reached good performance with high success rates in durability tests conducted at various lifting velocities and high adaption with objects in soft-friendly ways. These findings hold promise for efficiently manipulating multiple complex objects in each trial without the need for complex control systems.
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Project description:Compared with conventional von Neumann's architecture-based processors, neuromorphic systems provide energy-saving in-memory computing. We present here a 3D neuromorphic humanoid hand designed for providing an artificial unconscious response based on training. The neuromorphic humanoid hand system mimics the reflex arc for a quick response by managing complex spatiotemporal information. A 3D structural humanoid hand is first integrated with 3D-printed pressure sensors and a portable neuromorphic device that was fabricated by the multi-axis robot 3D printing technology. The 3D neuromorphic robot hand provides bioinspired signal perception, including detection, signal transmission, and signal processing, together with the biomimetic reflex arc function, allowing it to hold an unknown object with an automatically increased gripping force without a conventional controlling processor. The proposed system offers a new approach for realizing an unconscious response with an artificially intelligent robot.
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Project description:The visual system is known to extract summary representations of visually similar objects which bias the perception of individual objects toward the ensemble average. Although vision plays a large role in guiding action, less is known about whether ensemble representation is informative for action. Motor behavior is tuned to the veridical dimensions of objects and generally considered resistant to perceptual biases. However, when the relevant grasp dimension is not available or is unconstrained, ensemble perception may be informative to behavior by providing gist information about surrounding objects. In the present study, we examined if summary representations of a surrounding ensemble display influenced grip aperture and orientation when participants reached-to-grasp a central circular target which had an explicit size but importantly no explicit orientation that the visuomotor system could selectively attend to. Maximum grip aperture and grip orientation were not biased by ensemble statistics during grasping, although participants were able to perceive and provide manual estimations of the average size and orientation of the ensemble display. Support vector machine classification of ensemble statistics achieved above-chance classification accuracy when trained on kinematic and electromyography data of the perceptual but not grasping conditions, supporting our univariate findings. These results suggest that even along unconstrained grasping dimensions, visually-guided behaviors toward real-world objects are not biased by ensemble processing.
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Project description:Nature evolved many ways to grasp objects without using hands: elephants, octopuses, and monkeys use highly dexterous appendices. From a roboticist's perspective, the elephant trunk is a fascinating manipulator, which strategies can empower robots' interaction capabilities. However, quantifying prehensile forces in such large animals in a safe, ethical, and reproducible manner is challenging. We developed two sensorized objects to investigate the grasping of an adult African elephant with deliberately occluded vision. A cylinder and a handle provided a distributed force (80 and 6 taxels) and inertial measurements in real-time, resisting dirt and shocks. The animal curled the distal portion of the trunk to grasp the tools. Using force and contact area data of the cylinder revealed the animal's ability to finely modulate pressure. The handle data provided insights into the energy-efficient behavior of the animal, with no significant grasping force changes despite variations imposed on both weight (5-15 kg) and initial position of the object.
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Project description:IntroductionSome critically ill patients are confirmed by continuous electroencephalography (cEEG) monitoring that non-convulsive seizure (NCS) and/or non-convulsive status epilepticus (NCSE) are causes of their depressed level of consciousness. Shortage of epilepsy specialists, especially in developing countries, is a major limiting factor in implementing cEEG in general practice. Delivery of care with tele-continous EEG (tele-cEEG) may be a potential solution as this allows specialists from a central facility to remotely assist local neurologists from distant areas in interpreting EEG findings and suggest proper treatment. No tele-cEEG programme has been implemented to help improve quality of care. Therefore, this study is conducted to assess the efficacy and cost utility of implementing tele-cEEG in critical care.Methods and analysisThe Tele-cRCT study is a 3-year prospective, randomised, controlled, parallel, multicentre, superiority trial comparing delivery of care through 'Tele-cEEG' intervention with 'Tele-routine EEG (Tele-rEEG)' in patients with clinical suspicion of NCS/NCSE. A group of EEG specialists and a tele-EEG system were set up to remotely interpret EEG findings in six regional government hospitals across Thailand. The primary outcomes are functional neurological outcome (modified Rankin Scale, mRS), mortality rate and incidence of seizures. The secondary outcomes are cost utility, length of stay, emergency visit/readmission, impact on changing medical decisions and health professionals' perceptions about tele-cEEG implementation. Functional outcome (mRS) will be assessed at 3 and 7 days after recruitment, and again at time of hospital discharge, and at 90 days, 6 months, 9 months and 1 year. Costs and health-related quality of life will be assessed using the Thai version of the EuroQol-five dimensions-five levels (EQ-5D-5L) at hospital discharge, and at 90 days, 6 months, 9 months and 1 year.Ethics and disseminationThis study has been approved by the ethics committees of the Faculty of Medicine, Chulalongkorn University, and of Ramathibodi Hospital, Mahidol University, and registered on Thai Clinical Trials Registry. The results will be disseminated in a peer-reviewed journal.Trial registration numberTCTR20181022002; preresults.
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Project description:Human can successfully grasp various objects in different acceptable relative positions between human hand and objects. This grasp functionality can be described as the grasp tolerance of human hand, which is a significant functionality of human grasp. To understand the motor control of human hand completely, an analysis of hand and wrist postural synergies in tolerance grasping of various objects is needed. Ten healthy right-handed subjects were asked to perform the tolerance grasping with right hand using 6 objects of different shapes, sizes and relative positions between human hand and objects. Subjects were wearing CyberGlove attaching motion tracker on right hand, allowing a measurement of the hand and wrist postures. Correlation analysis of joints and inter-joint/inter-finger modules were carried on to explore the coordination between joints or modules. As the correlation between hand and wrist module is not obvious in tolerance grasping, individual analysis of wrist synergies would be more practical. In this case, postural synergies of hand and wrist were then presented separately through principal component analysis (PCA), expressed through the principal component (PC) information transmitted ratio, PC elements distribution and reconstructed angle error of joints. Results on correlation comparison of different module movements can be well explained by the influence factors of the joint movement correlation. Moreover, correlation analysis of joints and modules showed the wrist module had the lowest correlation among all inter-finger and inter-joint modules. Hand and wrist postures were both sufficient to be described by a few principal components. In terms of the PC elements distribution of hand postures, compared with previous investigations, there was a greater proportion of movement in the thumb joints especially the interphalangeal (IP) and opposition rotation (ROT) joint. The research could serve to a complete understanding of hand grasp, and the design, control of the anthropomorphic hand and wrist.
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