question: How does prosthetic arms know how/when to move its fingers?
comment: That's an entire 300-level college course, right there, but the basic answer is electronics and black sorcery in coding. The prosthetic uses special sensors that read electrical signals from nerves or brain neurons, and turns them into signals that run the prosthetic limb. The brain doesn't get feedback from the arm, but it does eventually adapt to moving it. Kinda like moving your hand if it's completely numb.
passages: Section::::How It Works.
  
  The i-LIMB Hand is controlled through the use of myoelectric signals, which uses the muscle signals in the patient's residual arm to move the i-LIMB Hand around. Electrodes are placed at two pre-determined muscle sites. The electrodes pick up the muscle signals when the patient contracts his/her muscles. These signals are then sent to a microprocessor which causes the device to move. The i-LIMB Hand has up to four different muscle triggers. The user is able to assign a grip to move the device to a certain position.
  
  These muscle triggers include:
   In February 2013, researchers from École Polytechnique Fédérale de Lausanne in Switzerland and the Scuola Superiore Sant'Anna in Italy, implanted electrodes into an amputee's arm, which gave the patient sensory feedback and allowed for real time control of the prosthetic. With wires linked to nerves in his upper arm, the Danish patient was able to handle objects and instantly receive a sense of touch through the special artificial hand that was created by Silvestro Micera and researchers both in Switzerland and Italy.
  
  Section::::Current technology and manufacturing.:Body-powered arms.:Terminal devices.
  
  Terminal devices contain a range of hooks, prehensors, hands or other devices.
   Section::::Upper limb control.
  
  Commercial solutions exploit superficial EMG signals to control the prosthesis. Furthermore, researchers are investigating alternative solutions that exploit different biological sources: 
  
  BULLET::::- implanted electrodes (neural, intramuscular and epymisial electrodes) to record neural or muscle activity;
  
  BULLET::::- pressure sensor matrices to detect force changes during muscle contraction;
  
  BULLET::::- the myokinetic approach to measure muscle deformation.
  
  Section::::Upper limb control.:Myokinetic control.
   In 2014, APL made history with the successful use of the "Modular Prosthetic Limb —" a fully artificial articulated arm and hand "— by" a bilateral shoulder-level amputee. APL used pattern recognition algorithms to track which muscles were contracting and enable the prosthetics to move in conjunction with the amputee's body.
  
  Similar technology was used in 2016 for a demonstration in which a paralyzed man was able to "fist-bump" Barack Obama using signals sent from an implanted brain chip. The limb returned sensory feedback from the arm to the wearer's brain.
  
  Section::::Research.:Drones.
   Section::::Lower limb control.:Speed-adaptation mechanism.
   Cosmetic prosthesis has long been used to disguise injuries and disfigurements. With advances in modern technology, cosmesis, the creation of lifelike limbs made from silicone or PVC has been made possible. Such prosthetics, including artificial hands, can now be designed to simulate the appearance of real hands, complete with freckles, veins, hair, fingerprints and even tattoos.
   Section::::Current products.
  
  Hand of Hope is an intention-driven exoskeleton hand that focuses on improving motion of the hand and fingers in stroke victims, developed by Rehab-Robotics. The robotic hand is controlled by EMG signals in the forearm muscles, meaning that patients can move their hand using only their brain. The device also has a continuous passive motion mode, where the actions of hand opening and closing are done involuntarily.
   Section::::Active orthoses.:Control.
  
  Ferris discusses the influence of controller types in his paper, A Physiologist's Perspective on Robotic Exoskeletons for Human Locomotion.
  
  Various methods for controlling lower limb active orthoses or exoskeletons:
  
  BULLET::::- Utilize sensory information from the exoskeleton and only use the human to provide a gentle push in the direction he/she wants to go
  
  BULLET::::- Foot sensors detect where the user wants to go
  
  BULLET::::- User freely moves hips in flexion and a set of full-bridge strain gauges attach to the shin of the exoskeleton and a potentiometer on the knee joint
   Section::::Forward models.
  
  In their simplest form, forward models take the input of a motor command to the “plant” and output a predicted position of the body.
   Current robotic and prosthetic hands receive far less tactile information than the human hand. Recent research has developed a tactile sensor array that mimics the mechanical properties and touch receptors of human fingertips. The sensor array is constructed as a rigid core surrounded by conductive fluid contained by an elastomeric skin. Electrodes are mounted on the surface of the rigid core and are connected to an impedance-measuring device within the core. When the artificial skin touches an object the fluid path around the electrodes is deformed, producing impedance changes that map the forces received from the object. The researchers expect that an important function of such artificial fingertips will be adjusting robotic grip on held objects.
   Scientists from several European countries and Israel developed a prosthetic hand in 2009, called SmartHand, which functions like a real one—allowing patients to write with it, type on a keyboard, play piano and perform other fine movements. The prosthesis has sensors which enable the patient to sense real feeling in its fingertips.
  
  Section::::Components.:Sensing.:Vision.
  
  Computer vision is the science and technology of machines that see. As a scientific discipline, computer vision is concerned with the theory behind artificial systems that extract information from images. The image data can take many forms, such as video sequences and views from cameras.
   Advancements in the processors used in myoelectric arms have 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.
   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.
   Robotic lower-limb exoskeletons can be controlled by several methods, including a footswitch (a pressure sensor attached to the bottom of the foot), gait-phase estimation (using joint angles to determine the current phase of walking), and myoelectric control (using electromyography). This article focuses on myoelectric control.
  
  Section::::Control methods.
   All hands have Hall effect sensors integrated into every joint to provide precise positional feedback. The motor hand includes force sensors for each degree of freedom and the muscle hand includes pressure sensors for each muscle. There are also several options for tactile sensing on the hand from basic pressure sensors to the BioTac multimodal tactile sensor from Syntouch LLC.
  
  The Shadow Hand software system is based on Robot Operating System, through which configuration, calibration, simulation and control of the hand is implemented. A simulation of the Shadow hand can be downloaded and installed in ROS.
  
  Section::::See also.
  
  BULLET::::- Robonaut
   The idea of Limbitless Solutions came to life in 2014 after a team of engineering students at the University of Central Florida led an initiative to provide bionic 3D printed limbs to children. In their free time, the students took advantage of a donated Stratasys Dimension 3D printer in the engineering manufacturing lab on campus to create an affordable prosthetic that displayed their ideas of art and engineering all into one. Their method was the first of its kind and minimized the cost and time of traditional prosthetic manufacturing processes like CNC milling. The first 3D printed arm the students created was run with off-the-shelf servos and batteries  which are activated by the electromyography muscle energy on the child’s limb.  Most prosthetic arms are mechanical, which presents a challenge for children without elbows because they have to open and close their mechanical prosthetic by bending their elbow. That led the Limbitless team to come up with the idea for an electronic arm with a muscle sensor that allows the child to open and close their prosthetic hand by flexing their biceps.  
   Section::::Current technology and manufacturing.:Robotic prostheses.:Robotic legs.
  
  The research of Robotic legs has made some advancement over time, allowing exact movement and control. A company in Switzerland called Ossur, has created a robotic leg that moves through algorithms and sensors that automatically adjust the angle of the foot during different points in its wearer's stride. Also there are brain-controlled bionic legs that allow an individual to move his limbs with a wireless transmitter.
  
  Section::::Current technology and manufacturing.:Robotic prostheses.:Robotic legs.:Prosthesis design.
   Section::::Lower limb control.
  
  Section::::Lower limb control.:Impedance control.
   Developments continue in replacing lost arms with cybernetic replacements by using nerves normally connected to the pectoralis muscles. These arms allow a slightly limited range of motion, and reportedly are slated to feature sensors for detecting pressure and temperature.
  
  Dr. Todd Kuiken at Northwestern University and Rehabilitation Institute of Chicago has developed a method called targeted reinnervation for an amputee to control motorized prosthetic devices and to regain sensory feedback.
  
  Section::::Motor prosthetics.:Sensory/motor prosthetics.
   The technology behind motor neuroprostheses is still in its infancy. Investigators and study participants continue to experiment with different ways of using the prostheses. Having a patient think about clenching a fist, for example, produces a different result than having him or her think about tapping a finger. The filters used in the prostheses are also being fine-tuned, and in the future, doctors hope to create an implant capable of transmitting signals from inside the skull wirelessly, as opposed to through a cable.
   The arms also correct for tremors in a surgeon's hands, which are normal even without fatigue, though a highly trained surgeon will be able to lessen the negative effects. However, some surgeries can last for hours, in which case the surgeon's arms will get tired, and the resulting tremors from fatigue can make the surgeon create false cuts, which can be devastating during a delicate operation. To handle this, the ZEUS is designed to track and nullify these tremors while still responding to the movements/commands of the surgeon's hands.
   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 reinnervated muscle, these contractions can be made to control the movement of an appropriate part of the robotic prosthesis.
   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 carry out activities 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 (electroencephalogram) signals, detected using small flat metal discs attached to the scalp, essentially decoding human brain activity used for physical movement, is used to control the robotic limbs. This allows the user to control the part directly.
   Prosthetics may not seem like a mechanical arm, but they are. It uses hinges and a wire harness to allow an incapable being to perform everyday functions. They have started creating arms that take a structure of a human arm and even though it looks like a skeletal metal arm, it moves like a normal arm and hand. This arm was made by Johns Hopkins University in 2015. It has 26 joints (way more than the old outdated arms) and is capable of lifting up to 45 pounds. This is all great, the best part is that each arm has 100 sensors that connect to the human mind. These sensors allow the person with the arm to move the arm like it was just another part of his or her body. People who have used this new prosthetic can say that they have actually been able to feel the texture, ultimately making prosthetics a huge part of the mechanical arm category.
   To capture electrical signals from the brain, scientists have developed microelectrode arrays smaller than a square centimeter that can be implanted in the skull to record electrical activity, transducing recorded information through a thin cable. After decades of research in monkeys, neuroscientists have been able to decode neuronal signals into movements. Completing the translation, researchers have built interfaces that allow patients to move computer cursors, and they are beginning to build robotic limbs and exoskeletons that patients can control by thinking about movement.
  