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Lower-extremity prosthetics
Lower-extremity prosthetics describes artificially replaced limbs located at the hip level or lower. Concerning all ages Ephraim et al. (2003) found a worldwide estimate of all-cause lower-extremity amputations of 2.0–5.9 per 10,000 inhabitants. For birth prevalence rates of congenital limb deficiency they found an estimate between 3.5–7.1 cases per 10,000 births.

The two main subcategories of lower extremity prosthetic devices are trans-tibial (any amputation transecting the tibia bone or a congenital anomaly resulting in a tibial deficiency), and trans-femoral (any amputation transecting the femur bone or a congenital anomaly resulting in a femoral deficiency). In the prosthetic industry a trans-tibial prosthetic leg is often referred to as a "BK" or below the knee prosthesis while the trans-femoral prosthetic leg is often referred to as an "AK" or above the knee prosthesis.

Other, less prevalent lower extremity cases include the following:
 * 1) Hip disarticulations – This usually refers to when an amputee or congenitally challenged patient has either an amputation or anomaly at or in close proximity to the hip joint.
 * 2) Knee disarticulations – This usually refers to an amputation through the knee disarticulating the femur from the tibia.
 * 3) Symes – This is an ankle disarticulation while preserving the heel pad.

Socket
This important part serves as an interface between the residuum and the prosthesis, allowing comfortable weight-bearing, movement control and proprioception. Its fitting is one of the most challenging aspects of the entire prosthesis. The difficulties accompanied with the socket are that it needs to have a perfect fit, with total surface bearing to prevent painful pressure spots. It needs to be flexible, but sturdy, to allow normal gait movement but not bend under pressure. '''In order to deal with this issue, state-of-the-art design for sockets is to implement a customized socket for each individual. By analyzing the stiffness of skin surfaces based on MRI images and force sensors, a customized socket can be built within soft material for soft and vulnerable tissue and relatively hard material for callous skin. These sockets provide a good fit for the controllability of prosthesis while allowing comfortable interface between amputees and prostheses.'''

Shank and connectors
This part creates distance and support between the knee-joint and the foot (in case of upper-leg prosthesis) or between the socket and the foot. The type of connectors that are used between the shank and the knee/foot determines whether the prosthesis is modular or not. Modular means that the angle and the displacement of the foot in respect to the socket can be changed after fitting. In developing countries prosthesis mostly are non-modular, in order to reduce cost. When considering children modularity of angle and height is important because of their average growth of 1.9 cm annually.

Foot
Providing contact to the ground, the foot provides shock absorption and stability during stance. Additionally it influences gait biomechanics by its shape and stiffness. This is because the trajectory of the center of pressure (COP) and the angle of the ground reaction forces is determined by the shape and stiffness of the foot and needs to match the subject's build in order to produce a normal gait pattern. Andrysek (2010) found 16 different types of feet, with greatly varying results concerning durability and biomechanics. The main problem found in current feet is durability, endurance ranging from 16–32 months These results are for adults and will probably be worse for children due to higher activity levels and scale effects.

Knee joint
In case of a trans-femoral amputation there also is a need for a complex connector providing articulation, allowing flexion during swing-phase but not during stance.

Microprocessor control
To mimic the knee's functionality during gait, microprocessor-controlled knee joints have been developed that control the flexion of the knee. Some examples are Otto Bock’s C-leg, introduced in 1997, Ossur's Rheo Knee, released in 2005, the Power Knee by Ossur, introduced in 2006, the Plié Knee from Freedom Innovations and DAW Industries’ Self Learning Knee (SLK).

The idea was originally developed by Kelly James, a Canadian engineer, at the University of Alberta.

A microprocessor is used to interpret and analyse signals from knee-angle sensors and moment sensors. The microprocessor receives signals from its sensors to determine the type of motion being employed by the amputee. Most microprocessor controlled knee-joints are powered by a battery housed inside the prosthesis.

The sensory signals computed by the microprocessor are used to control the resistance generated by hydraulic cylinders in the knee-joint. Small valves control the amount of hydraulic fluid that can pass into and out of the cylinder, thus regulating the extension and compression of a piston connected to the upper section of the knee.

The main advantage of a microprocessor-controlled prosthesis is closer approximation to an amputee’s natural gait. Some allow amputees to walk near walking speed or run. Variations in speed are also possible and are taken into account by sensors and communicated to the microprocessor, which adjusts to these changes accordingly. It also enables the amputees to walk down stairs with a step-over-step approach, rather than the one step at a time approach used with mechanical knees. However, some have some significant drawbacks that impair its use. They can be susceptible to water damage and thus great care must be taken to ensure that the prosthesis remains dry.

Myoelectric
A myoelectric prosthesis uses the electrical tension generated every time a muscle contracts, as information. This tension can be captured from voluntarily contracted muscles by electrodes applied on the skin to control the movements of the prosthesis, such as elbow flexion/extension, wrist supination/pronation (rotation) or opening/closing of the fingers. A prosthesis of this type utilizes the residual neuromuscular system of the human body to control the functions of an electric powered prosthetic hand, wrist, elbow or foot. This is different from an electric switch prosthesis, which requires straps and/or cables actuated by body movements to actuate or operate switches that control the movements of the prosthesis.

The USSR was the first to develop a myoelectric arm in 1958, while the first myoelectric arm became commercial in 1964 by the Central Prosthetic Research Institute of the USSR, and distributed by the Hangar Limb Factory of the UK.

Researchers at the Rehabilitation Institute of Chicago announced in September 2013 that they have developed a robotic leg that translates neural impulses from the user's thigh muscles into movement, which is the first prosthetic leg to do so. It is currently in testing.

Robotic prostheses
Robots can be used to generate objective measures of patient's impairment and therapy outcome, assist in diagnosis, customize therapies based on patient's motor abilities, and assure compliance with treatment regimens and maintain patient's records. It is shown in many studies that there is a significant improvement in upper limb motor function after stroke using robotics for upper limb rehabilitation. In order for a robotic prosthetic limb to work, it must have several components to integrate it into the body's function: Biosensors detect signals from the user's nervous or muscular systems. It then relays this information to a controller located inside the device, and processes feedback from the limb and actuator (e.g., position, force) and sends it to the controller. Examples include surface electrodes that detect electrical activity on the skin, needle electrodes implanted in muscle, or solid-state electrode arrays with nerves growing through them. One type of these biosensors are employed in myoelectric prostheses.

A device known as the controller is connected to the user's nerve and muscular systems and the device itself. It sends intention commands from the user to the actuators of the device, and interprets feedback from the mechanical and biosensors to the user. The controller is also responsible for the monitoring and control of the movements of the device.

An actuator mimics the actions of a muscle in producing force and movement. Examples include a motor that aids or replaces original muscle tissue.

Targeted muscle reinnervation (TMR) is a technique in which motor nerves, which previously controlled muscles on an amputated limb, are surgically rerouted such that they reinnervate a small region of a large, intact muscle, such as the pectoralis major. As a result, when a patient thinks about moving the thumb of his missing hand, a small area of muscle on his chest will contract instead. By placing sensors over the reinervated muscle, these contractions can be made to control movement of an appropriate part of the robotic prosthesis.

A variant of this technique is called targeted sensory reinnervation (TSR). This procedure is similar to TMR, except that sensory nerves are surgically rerouted to skin on the chest, rather than motor nerves rerouted to muscle. Recently, robotic limbs have improved in their ability to take signals from the human brain and translate those signals into motion in the artificial limb. DARPA, the Pentagon’s research division, is working to make even more advancements in this area. Their desire is to create an artificial limb that ties directly into the nervous system.

Robotic arms
Advancements in the processors used in myoelectric arms has allowed developers to make gains in fine tuned control of the prosthetic. The Boston Digital Arm is a recent artificial limb that has taken advantage of these more advanced processors. The arm allows movement in five axes and allows the arm to be programmed for a more customized feel. Recently the i-Limb hand, invented in Edinburgh, Scotland, by David Gow has become the first commercially available hand prosthesis with five individually powered digits. The hand also possesses a manually rotatable thumb which is operated passively by the user and allows the hand to grip in precision, power and key grip modes.

Another neural prosthetic is Johns Hopkins University Applied Physics Laboratory Proto 1. Besides the Proto 1, the university also finished the Proto 2 in 2010. Early in 2013, Max Ortiz Catalan and Rickard Brånemark of the Chalmers University of Technology, and Sahlgrenska University Hospital in Sweden, succeeded in making the first robotic arm which is mind-controlled and can be permanently attached to the body (using osseointegration).

An approach that is very useful is called arm rotation which is common for unilateral amputees which is an amputation that affects only one side of the body; and also essential for bilateral amputees, a person who is missing or has had amputated either both arms or legs, to perform tasks of daily living. This involves inserting a small permanent magnet into the distal end of the residual bone of subjects with upper limb amputations. When a subject rotates the residual arm, the magnet will rotate with the residual bone, causing a change in magnetic field distribution. EEG signals which is electroencephalogram, a test that detects electrical activity in the brain using small flat metal discs attached to the scalp, essentially decoding human brain activity used for physical movement, are used to control the robotic limbs. This is very essential being that it provides a more lively affect to the robotic limb, giving oneself control over the part as if it was their own.

Prosthesis design
'''The main goal of a robotic prosthesis is to provide active actuations during gaits to improve the biomechanics and metabolic costs for amputees. What make designing robotic prosthesis difficult is that of the prosthesis needs to be an complete, and independent system which includes an actuator, a battery, and a controller at a weight comparable to the weight of a biological limb. Although a number of actuators have been considered as candidates for prosthesis use, currently, successful prosthesis designs use electric servo actuators. In general, the electric servo actuators are used as series-elastic-actuators (SEA) where elastic components is embedded between the gear box and the electric servo motor. These SEAs not only allow compliance load bearing during a heel strike, but also enable transferring mechanical energy into elastic energy which improve the overall energy efficiency of the prosthesis. Designing robotic prostheses for transfemoral amputees may be more challenging than that of transtibial amputees due to mechanical issues such as spatial problems, weight limits, and battery durations. These issues may be resolved by implementing an efficient passive actuation which save mechanical energy into elastic energy and release them at the right phase of a gait. Although knee joints produce non-ignorable joint torques during gaits, a number of studies indicate the net work done by knee joints is negative, indicating the possibility of implementing biomechanics for knee joints without an active actuation. The potential of these mechanism was explored via clutchable SEA which successfully emulate biological knee joint torques without an active actuation .'''

Muscle reflex model based control
'''The main issue in designing controllers for the prostheses is to generate torque references to meet biomechanical requirements. The main challenge is that the controllers of prostheses cannot access all joint kinematics of the amputees unlike controllers for humanoids since attaching sensors on every biological joint would be impractical. Although a number of methods based on EMG signals and gait phases have been proposed, these conventional methods are sensitive to signal noise and they only able to generate joint torques for limited motions such as walking at a certain speed. To deal with this issue, a reflex model of human neuromuscular system is developed to be used as a torque generator. This reflex model is elaborated based on muscle reflex (the positive feedback), which found it to play a major role during load bearing. The biggest advantage of the reflex-model-based-control strategy is that it does not involve central pattern generators (CPG) in the model, which minimize dependency on the neural signals, e.g., EMG signals. Also, because the principal of muscle reflex does not vary depend on the motions but vary based on external disturbances (e.g., ground reaction forces and joint kinematics), the reflex model is able to generate appropriate joint torque references under external disturbances without changing any parameters. These reflex models have been implemented into actual prosthesis for clinical trials and have showed that they can produce proper joint torques during walking, running, and ascent on stairs. Recently, the reflex model was extended to not only sagittal plane motions but also to coronal plane motions, which demonstrate how a muscle is activated for turning, acceleration, and deceleration. In addition, by imitating the way human nervous system adjust muscle stimulations for the leg placement to avoid obstacles or prevent one from falling, the prosthesis can assist the amputee in the similar circumstances. Since these reflex models illustrate how neural signals and muscle reflex are integrated, the muscle reflex models may provide insight into designing a controller for brain-machine-interfaces or neural interfaces where a bi-directional communication between the amputees and the prostheses is available.'''