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Blindsight by Peter Watts - Echopraxia

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Building the Human Body: The Bionic Hand - …

HMI is the interaction of humans with machines. The advent of machines fascinated mankind and its interaction with human dates back to several decades. Machines were crafted to act as passive extensions of the human body. However, the development of prosthetics has changed the way humans interact with machines []. Hogan [], noted the challenges and possibilities of human interactive machinery and reviewed that the machines designed for cooperating physically with humans are emerging technology to support human activity. He highlighted the design of control system that can endow the amputee’s motorized arm prosthesis to take advantage of mechanical constraints and cooperation between natural and artificial limb such that increased motor abilities can be obtained. He further added that the development of robots capable of safely interacting and cooperating with humans are enabling new form of therapy for neurologically injured patients. Machines are now designed to cooperate physically with humans, enabling new ways to support human activity. Human machine relation is reported in literature with different terminologies such as man machine interaction (MMI), Brain computer interaction (BCI) and Neuroprosthetics. These terms ultimately narrow down to the basics of HMI with varying differences.

In this series of Building the Human Body, ..

In human motion and intention sensing, EMG signal analysis coupled with artificial neural network algorithm and alternate muscle activation sensors with assisting manipulators or prosthetic devices have been shown to predict the intention of the patient’s ability to move their artificial limb or prosthesis. In the quest to develop alternate muscle sensors to overcome the limitation of EMG, Cen [] developed the optical muscle activation sensors for measuring the optical density in muscle by emitting and gathering the single wavelength light source. The forearm force level was estimated and the comparative result of surface EMG and optical density of muscle showed that optical density can be used to measure muscle contraction. They further suggested that future work for detecting motion intention will require advanced algorithm in signal processing and modeling of optical tissue interaction. Many computational techniques and concept of artificial intelligence such as genetic algorithm, neural networks, and support vector machine are deployed to better implement the motion intention for better coordination of artificial limbs. However, till recently a general approach for the control of functional movements had been followed based on the biological principle of motor control such as representation of motor patterns, reflexes and motor skills for developing advanced assistive systems, but use of advance soft computing techniques like expert systems, fuzzy sets, analytical methods are being employed to design better devices for rehabilitation [].

Robust compliant motion for manipulators

This problem can be resolved by adopting a large bandwidth human-machine ..

Neuro or Neural prosthetics (NP) is a series of device which substitutes a motor, sensory or cognitive modality that might have been damaged as a result of an injury or disease []. In neuro-prosthetics, external devices are connected with the human nervous system that records the brain signals from user by computational analysis and relays this information to the external effector that act on those intentions. The cumulative voltage across motor cortex area encompasses the activity of millions of neurons and the generated action potential is conducted by peripheral nerves to desired body part with the help of output effectors. The corresponding brain or nerve signals are used to control computer cursor movements and robotic arms, or enable the reanimation of paralyzed limbs. NP enables direct interfacing with the brain and has great potential for restoring communication and limb control in disabled individuals. The key component of interface design is the electrode and the interface material that can record natural bioelectric signals and provide artificial excitation of nerves/muscles. Jiping He [], reported the use of neural interface in activating residual neural function and brain control of lower limb function. They touched upon recent progress in neural interface technologies and demonstrated the application of direct cortical control of robotic arm or computer cursor for simple movement using cortically controlled neuro-prosthetics to improve motor function in subjects with severe neurological deficits. They further emphasized that the ability of neural systems to adapt to changes and learning new functions are important considerations in the design and development of neuro-prosthetics such that an intelligent neural interface can be designed that can activate residual function and facilitate control. However, several challenging engineering and biological issues still remain to be resolved before a practical system can be developed for patients to receive real benefit of neuro-prostheses. Future approach in designing NP will require smart materials and sensors and also wired/wireless neural interfaces.

Most recently, research in VLSI field lead to the development of silicon neuron as evident by the works of Tenore and Etienne-Cummings, [] who demonstrated the use of silicon neuron designed using VLSI technology which can mimic the function of central pattern generator (CPG) in humans. They programmed the silicon to control robotic locomotion and further added that the same can be used in upper limb prosthetics. This opens new avenues in the fields of robotics and prosthetics. They demonstrated the lower limb application of silicon neuron by using a bipedal robot prototype having actuating hips and knees that facilitated walking. For upper limb application, they used the myoelectric signals from both normal and trans-radial amputee for developing real-time application that featured multi-degree of freedom of upper limb prostheses.

Quantitation of Human Shoulder Anatomy for Prosthesis Control

Computational Approach to Vision and Motor Control.

A pivotal point in the understanding of motor systems was highlighted approximately 130 years ago through experiments conducted by Eduard Hitzig, Gustav Fritsch, and David Ferrier. These researchers noted that limb movements occurred when electrical stimuli were applied in the frontal area of the brain in experimental animals. Ferrier conceptualized drawings on the brain of a monkey to locate the primary motor cortex area for effective stimulation sites in his studies. Further, studies have apprised that this area sends movement command signals directly to the spinal cord. Similarly, American neurosurgeon Wilder Penfield in 1960s constructed high resolution maps from human neurosurgical patients. He found that the primary motor cortex is reciprocally interconnected with numerous other cortical areas. In addition, most of the cerebral cortex is further interconnected with the cerebellum and basal ganglia, two other brain structures having important motor function. To better understand the functioning of cerebral cortex, further research involves studying the detailed representation of movement or muscle activity that is expressed by the physiological recordings from each of these motor signals []. Some studies examine the connections among the different areas of the brain, and attempt to relate these network connections to the signals being produced. Future applications could include recording the brain's natural control signals to extract meaningful information from them for controlling different external peripheral devices such as computer, prosthetic limb or a robotic arm.

The use of targeted muscle reinnervation for improved myoelectric prosthesis control in a ..
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