Individuals with tetraplegia lack independent mobility, making them highly dependent on others to move from one place to another. Here, we describe how two macaques were able to use a wireless integrated system to control a robotic platform, over which they were sitting, to achieve independent mobility using the neuronal activity in their motor cortices. The activity of populations of single neurons was recorded using multiple electrode arrays implanted in the arm region of primary motor cortex, and decoded to achieve brain control of the platform. We found that free-running brain control of the platform (which was not equipped with any machine intelligence) was fast and accurate, resembling the performance achieved using joystick control. The decoding algorithms can be trained in the absence of joystick movements, as would be required for use by tetraplegic individuals, demonstrating that the non-human primate model is a good pre-clinical model for developing such a cortically-controlled movement prosthetic. Interestingly, we found that the response properties of some neurons differed greatly depending on the mode of control (joystick or brain control), suggesting different roles for these neurons in encoding movement intention and movement execution. These results demonstrate that independent mobility can be achieved without first training on prescribed motor movements, opening the door for the implementation of this technology in persons with tetraplegia.
Unlike traditional hard grippers, soft robotic grippers are commonly made of soft materials so that the soft grippers can produce motion via elastic deformations of their compliant components. The advantages of compliance allow soft grippers to effectively eliminate shocks caused by hard contact, which usually occurs when a hard robotic gripper manipulates a hard object. Until now, the soft robotic grippers are able to operate numerous objects with irregular geometries and different textures. Besides, with the help of embedded sensors, soft robotic grippers have facilitated the growing automation of many tasks, which are thought to be far too delicate for robotic manipulation. This paper reviews the advancement in soft robotic grippers. The paper first introduces the actuation technologies followed by the design and fabrication techniques. The use of 3D printing techniques in the fabrication of the soft gripper is also discussed. The Review then highlights the challenges and future outlook in the fabrication of soft grippers and sensors.
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