Brian Villani, 26, tall and in khakis, extroverted, both opinionated and earnest, shares a garden-level apartment with two roommates in greater Boston that's outfitted with the material culture of young adulthood: big overstuffed couch, multiple gaming systems, oversize posters, a clutter of plastic kitchenware. He commutes by train to a job he's held for years at a corporate mail room downtown, a job he loves--"I pick up all the packages, and all my vendors know me," he says. He lives close--"but not too close," he says wryly--to his parents and has an abiding passion for sports, especially the art of play-by-play announcing. He is counting down the days to his brother's wedding. Villani moves through life, home to work and back again, with an extended set of technologies that are a mix of the familiar and distinctive.

In this modern era of the digital world where people are trying to find simplicity and ease in doing works, moreover, these new inventions are booming out for making mankind a way to lead a simple life using different technologies and ways among that one is Artificial intelligence or shortly known as AI a progressively increasing field of study which having its touch in every area starting from social media to e-commerce websites for a good recommendation of posts of our type and products based on search recommendations along within the different domains like agriculture, virtual assistance, shopping recommendations and for physically disabled people, security, stock market prediction, self-driving cars and many more. This modern era of AI can visualize things and understand real-time around us and can make optimal decisions and remove real-time problems moreover for the efficient work in addition with the reduction of human errors. How Ai is useful for disabled persons? Nowadays everyone has a mobile phone or any electronic devices, we spend more time of day with these devices and the development of this advanced technology like artificial intelligence and natural language processing, iot made their roots into our daily life's electronics and these developed features can be used in different ways where people who are suffering from disabilities can remove their problems or inconvenience related easily without any help of other person using apps and software's developed by advance technology. There is a different type of disabilities people face and mainly with Vision, Hearing, Prosthetics are three kinds mostly we can observe in the world, different technologies are present for vision-related issues such as braille displays and writing and many more for a long time, and in recent times AI has changed this thing and improved the way of interacting.

In the NeurIPS 2018 Artificial Intelligence for Prosthetics challenge, participants were tasked with building a controller for a musculoskeletal model with a goal of matching a given time-varying velocity vector. Top participants were invited to describe their algorithms. In this work, we describe the challenge and present thirteen solutions that used deep reinforcement learning approaches. Many solutions use similar relaxations and heuristics, such as reward shaping, frame skipping, discretization of the action space, symmetry, and policy blending. However, each team implemented different modifications of the known algorithms by, for example, dividing the task into subtasks, learning low-level control, or by incorporating expert knowledge and using imitation learning.

In this paper, We Apply Reinforcement learning (RL) techniques to train a realistic biomechanical model to work with different people and on different walking environments. We benchmarking 3 RL algorithms: Deep Deterministic Policy Gradient (DDPG), Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO) in OpenSim environment, Also we apply imitation learning to a prosthetics domain to reduce the training time needed to design customized prosthetics. We use DDPG algorithm to train an original expert agent. We then propose a modification to the Dataset Aggregation (DAgger) algorithm to reuse the expert knowledge and train a new target agent to replicate that behaviour in fewer than 5 iterations, compared to the 100 iterations taken by the expert agent which means reducing training time by 95%. Our modifications to the DAgger algorithm improve the balance between exploiting the expert policy and exploring the environment. We show empirically that these improve convergence time of the target agent, particularly when there is some degree of variation between expert and naive agent.

Quad amputee Moshe runs for the very first time, thanks to state-of-the-art prosthetics). A 9-year-old quadruple amputee – the son of a Hasidic student who survived a bullet to the brain in the fatal 1994 Brooklyn Bridge shooting – has learned to run for the very first time thanks to a pair of brand new prosthetics. A broad smile plastered to his face, Moshe Sasokin joyfully bounds through the halls of Prosthetics in Motion, which fitted him with custom-made running blades, in video taken last month. Moshe was just 6 months old when he was diagnosed with a severe case of meningitis – leading doctors to amputate below his elbow and knee in order to save his life. In 2015, he first learned how to walk at age 6 after being fitted with his first pair of prosthetic legs.

Prosthetics have advanced drastically in recent years. The technology's potential has even inspired many, like Elon Musk, to ask whether we may be living as "cyborgs" in the not-too-far future. For Johnny Matheny of Port Richey, Florida, that future is now. Matheny, who lost his arm to cancer in 2005, has recently become the first person to live with an advanced mind-controlled robotic arm. He received the arm in December and will be spending the next year testing it out.

This is the fifth post in our Startup Spotlight series featuring new robotics companies from around the world. We're inviting representatives from these startups to describe their technologies and how they see the marketplace. The views expressed here are solely those of the author and do not represent positions of IEEE Spectrum or the IEEE. Researchers have long been trying to build robotic hands that mimic the extraordinary capabilities of the human hand. The goal has been a device with size and weight similar to our own hands, capable of performing multiple grasping motions, and powered by advanced controllers.

Medical science is seeing a significant boost from 3D printing. New startups in the 3D manufacturing realm are creating better prosthetics and customisable medical devices that are worlds more advanced than what came before. For example two startups – Bioniks and Voodoo Manufacturing – are creating unique prosthetics for patients. Bioniks, a bio-medical printing startup based in Pakistan, has now created a total of 25 bionic arms. These are advanced prosthetics like those of the Bioniks'Robotic Arm' prosthetic that includes motorised joints as well as custom fitting through 3D printing, says Bharathidasan Moorthi, a digital marketing manager representing the company.

The gift of a new toy is met with enthusiasm by most children, but for one Texas girl, a doll that looks just like her triggered tears of joy. Courtney Fletcher Bennett gave her daughter Emma a new American Girl doll that was custom fitted with a prosthetic right leg, just like hers. In a video posted to Facebook Wednesday, Emma, whose last name was not disclosed, is presented the box by her little sister and told to read the enclosed letter. Emma lifts a flap covering the doll's legs, sees the pink prosthetic leg, flips the cover back down and gasps in surprise. "You gotta be kidding me!" she says before taking the doll out of the box and hugging it closely, tears streaming down her face.