In this research, we are about to present an agentbased model of human muscle which can be used in analysis of human movement. As the model is designed based on the physiological structure of the muscle, The simulation calculations would be natural, and also, It can be possible to analyze human movement using reverse engineering methods. The model is also a suitable choice to be used in modern prostheses, because the calculation of the model is less than other machine learning models such as artificial neural network algorithms and It makes our algorithm battery-friendly. We will also devise a method that can calculate the intensity of human muscle during gait cycle using a reverse engineering solution. The algorithm called Boots is different from some optimization methods, so It would be able to compute the activities of both agonist and antagonist muscles in a joint. As a consequence, By having an agent-based model of human muscle and Boots algorithm, We would be capable to develop software that can calculate the nervous stimulation of human's lower body muscle based on the angular displacement during gait cycle without using painful methods like electromyography. By developing the application as open-source software, We are hopeful to help researchers and physicians who are studying in medical and biomechanical fields.

Functional Electrical Stimulation (FES) is an established and safe technique for contracting muscles by stimulating the skin above a muscle to induce its contraction. However, an open challenge remains on how to restore motor abilities to human limbs through FES, as the problem of controlling the stimulation is unclear. We are taking a robotics perspective on this problem, by developing robot learning algorithms that control the ultimate humanoid robot, the human body, through electrical muscle stimulation. Human muscles are not trivial to control as actuators due to their force production being non-stationary as a result of fatigue and other internal state changes, in contrast to robot actuators which are wellunderstood and stationary over broad operation ranges. We present our Deep Reinforcement Learning approach to the control of human muscles with FES, using a recurrent neural network for dynamic state representation, to overcome the unobserved elements of the behaviour of human muscles under external stimulation. We demonstrate our technique both in neuromuscular simulations but also experimentally on a human. Our results show that our controller can learn to manipulate human muscles, applying appropriate levels of stimulation to achieve the given tasks while compensating for advancing muscle fatigue which arises throughout the tasks. Additionally, Figure 1: Our 3 scenarios for FES control: (a) arm vertical motion our technique can learn quickly enough to be implemented in in simulation (b) and human volunteers, (c) arm horizontal motion real-world human-in-the-loop settings.

Researchers in Tokyo are developing human muscles that can be attached to, and used by, machines.

Since the 1920's, some researchers and studies have suggested that chimps are'super strong' compared to humans. These past studies implied that chimps' muscle fibers - the cells that make up muscles - are superior to humans'. But a new study has found that contrary to this belief, a chimp muscles' power output is just about 1.35 times higher than human muscle of similar size - a difference the researchers call'modest' compared with historical, popular accounts of chimp'super strength' being many times stronger than humans. When all factors were integrated in a computer model, chimp muscle produces about 1.35 times more dynamics force and power than human muscle Dr Brian Umberger, a researcher at the University of Massachusetts Amherst and a co-author of the study, said that the researchers found that this modest performance advantage wasn't actually due to strong muscle fibers found in chimpanzees compared to humans - but due to the different mix of muscle fibers found in chimpanzees compared to humans. According to the authors of the research, if the long-standing, untested assumption about chimpanzee's exceptional strength was true, it'would indicate a significant and previously unappreciated evolutionary shift in the force and/or power-producing capabilities of skeletal muscle' in either chimps or humans, whose lines diverged about 7 or 8 million years ago.

In 1937, robot hobbyist "Bill" Griffith P. Taylor of Toronto invented the world's first industrial robot. It was a crude machine, dubbed the Robot Gargantua by its creator. The crane-like device was powered by a single electric motor and controlled via punched paper tape, which threw a series of switches controlling each of the machine's five axes of movement. Still, it could stack wooden blocks in preprogrammed patterns, an accomplishment that Meccano Magazine, an English monthly hobby magazine from the era, hailed as "a Wells-ian vision of'Things to Come' in which human labor will not be necessary in building up the creations of architects and engineers." In the 80 years since, Gargantua's progeny have revolutionized how we work.

Robots have become one step closer to being more human-like. Researchers have developed actuators that generate movements similar to those of a bicep muscle and are also shock absorbent. This innovated technology uses vacuum power to automate soft, rubber beams, which could one-day allow robots and humans to safely work alongside each other. Researchers have developed actuators for cyborgs that generates movements similar to those of skeletal muscles and are even shock absorbing. Similar to human muscles, actuators are soft, shock absorbing and are not harmful to the robots environment or the humans in it.

The lightest material on Earth now packs a powerful punch. Scientists from Texas and around the world have created a material that, by density, is lighter than air yet, when electrified, instantly and powerfully contracts. Their work is detailed in this week's issue of the journal Science. "These artificial muscles are very lightweight and can do wonderful things," said Ray Baughman, the study author from the University of Texas at Dallas. While the artificial muscle is unlikely to be used in humans or prosthetic limbs, Baughman says "these sheets of carbon nanotubes ... are of great practical interest for LEDs, solar cells, and other applications."