Robotic prosthesis control

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Robotic prosthesis control is a method for controlling a prosthesis in such a way that the controlled robotic prosthesis restores a biologically accurate gait to a person with a loss of limb. [1] This is a special branch of control that has an emphasis on the interaction between humans and robotics.

Contents

Background

Basic control block diagram used in the designing of controllers for a system. Block diagram.png
Basic control block diagram used in the designing of controllers for a system.

In the 1970s several researchers developed a tethered electrohydraulic transfemoral prosthesis. [2] [3] [4] [5] [6] [7] It only included a hydraulically actuated knee joint controlled by off-board electronics using a type of control called echo control. [4] Echo control tries to take the kinematics from the sound leg and control the prosthetic leg to match the intact leg when it reaches that part of the gait cycle. [3] In 1988 a battery-powered active knee joint powered by DC motors and controlled by a robust position tracking control algorithm was created by Popovic and Schwirtlich. [8] [9] Tracking control is a common method of control used to force a particular state, such as position, velocity, or torque, to track a particular trajectory. These are just two examples of previous work that has been done in this field.

Lower limb control

Impedance control

This form of control is an approach used to control the dynamic interactions between the environment and a manipulator. [10] This works by treating the environment as an admittance and the manipulator as the impedance. [11] The relationship this imposes for robotic prosthesis the relationship in between force production in response to the motion imposed by the environment. This translates into the torque required at each joint during a single stride, represented as a series of passive impedance functions piece wise connected over a gait cycle. [10] Impedance control doesn't regulate force or position independently, instead it regulates the relationship between force and position and velocity. To Design an impedance controller, a regression analysis of gait data is used to parameterize an impedance function. For lower limb prosthesis the impedance function looks similar to the following equation. [12]

Hugh Herr demonstrating new robotic prosthetic legs at TED 2014: "That was the first demonstration of a running gait under neural command. The more I fire my muscles, the more torque I get." Hugh Herr, TED 2014.jpg
Hugh Herr demonstrating new robotic prosthetic legs at TED 2014: "That was the first demonstration of a running gait under neural command. The more I fire my muscles, the more torque I get."

The terms k (spring stiffness), θ0 (equilibrium angle), and b (dampening coefficient) are all parameters found through regression and tuned for different parts of the gait cycle and for a specific speed. This relationship is then programmed into a micro controller to determine the required torque at different parts of the walking phase.

Myoelectric control

Electromyography (EMG) is a technique used for evaluating and recording the electrical activity produced by skeletal muscles. [13] Advanced pattern recognition algorithms can take these recordings and decode the unique EMG signal patterns generated by muscles during specific movements. The patterns can be used to determine the intent of the user and provide control for a prosthetic limb. [14] For lower limb robotic prosthesis it is important to be able to determine if the user wants to walk on level ground, up a slope, or up stairs. Currently this is where myoelectric control comes intro play. During transitions between these different modes of operation EMG signal becomes highly variable and can be used to complement information from mechanical sensors to determine the intended mode of operation. [14] Each patient that uses a robotic prosthesis that is tuned for this type of control has to have their system trained for them specifically. This is done by having them go through the different modes of operation and using that data to train their pattern recognition algorithm. [14]

Speed-adaptation mechanism

The speed-adaption mechanism is a mechanism used to determine the required torque from the joints at different moving speeds. [1] During the stance phase it has been seen that quasistiffness, which is the derivative of the torque angle relationship with respect the angle, changes constantly as a function of walking speed. [1] This means that over the stance phase, depending on the speed the subject is moving, there is a derivable torque angle relationship that can be used to control a lower limb prosthesis. During the swing phase joint torque increases proportionally to walking speed and the duration of the swing phase decreases proportionally to the stride time. [1] These properties allow for trajectories to be derived that can be controlled around that accurately describe the angle trajectory over the swing phase. Because these two mechanism remain constant from person to person this method removes the speed and patient specific tuning required by most lower limb prosthetic controllers. [1]

Model-independent quadratic programs (MIQP)+Impedance control

Walking gait is classified as hybrid system, meaning that it has split dynamics. With this unique problem, a set of solutions to hybrid systems that undergo impacts was developed called Rapid Exponentially Stabilizing Control Lyapunov Functions(RES-CLF). [15] Control Lyapunov function are used to stabilize a nonlinear system to a desired set of states. RES-CLFs can be realized using quadratic programs that take in several inequality constraints and return an optimal output. [15] One problem with these are that they require a model of the system to develop the RES-CLFs. To remove the need of tuning to specific individuals Model Independent Quadratic Programs (MIQP) were used to derive CLFs. These CLFs are only focused on reducing the error in the desired output without any knowledge of what the desired torque should be. To provide this information an impedance control is added to provide a feed forward term that allows the MIQP to gather information about the system it is controlling without having a full model of the system. [15]

Upper limb control

Commercial solutions exploit superficial EMG signals to control the prosthesis. Furthermore, researchers are investigating alternative solutions that exploit different biological sources:

Myokinetic control

Myokinetic control represents an alternative to standard myoelectric control. It aims at measuring muscle deformation during contraction instead of muscle electrical activity. A novel approach recently emerged in 2017 which is based on sensing the magnetic field of permanent magnets directly implanted into residual muscles. [16] [17] Localizing the position of the magnet is equivalent to measuring the contraction/elongation of the muscle it is implanted in as the magnet moves with it. This information can be used to interpret the voluntary movement of the subject and consequently control the prosthesis. The magnetic signals generated by the magnets are detected by external sensors placed around the residual limb. Localization is then implemented by an optimization method that performs the tracking by solving the magnetic inverse problem (e.g., Levenberg–Marquardt algorithm). [16]

Related Research Articles

<span class="mw-page-title-main">Prosthesis</span> Artificial device that replaces a missing body part

In medicine, a prosthesis, or a prosthetic implant, is an artificial device that replaces a missing body part, which may be lost through trauma, disease, or a condition present at birth. Prostheses are intended to restore the normal functions of the missing body part. Amputee rehabilitation is primarily coordinated by a physiatrist as part of an inter-disciplinary team consisting of physiatrists, prosthetists, nurses, physical therapists, and occupational therapists. Prostheses can be created by hand or with computer-aided design (CAD), a software interface that helps creators design and analyze the creation with computer-generated 2-D and 3-D graphics as well as analysis and optimization tools.

<span class="mw-page-title-main">Gait (human)</span> A pattern of limb movements made during locomotion

A gait is a manner of limb movements made during locomotion. Human gaits are the various ways in which humans can move, either naturally or as a result of specialized training. Human gait is defined as bipedal forward propulsion of the center of gravity of the human body, in which there are sinuous movements of different segments of the body with little energy spent. Varied gaits are characterized by differences such as limb movement patterns, overall velocity, forces, kinetic and potential energy cycles, and changes in contact with the ground.

<span class="mw-page-title-main">Electromyography</span> Electrodiagnostic medicine technique

Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG is performed using an instrument called an electromyograph to produce a record called an electromyogram. An electromyograph detects the electric potential generated by muscle cells when these cells are electrically or neurologically activated. The signals can be analyzed to detect abnormalities, activation level, or recruitment order, or to analyze the biomechanics of human or animal movement. Needle EMG is an electrodiagnostic medicine technique commonly used by neurologists. Surface EMG is a non-medical procedure used to assess muscle activation by several professionals, including physiotherapists, kinesiologists and biomedical engineers. In computer science, EMG is also used as middleware in gesture recognition towards allowing the input of physical action to a computer as a form of human-computer interaction.

Neuroprosthetics is a discipline related to neuroscience and biomedical engineering concerned with developing neural prostheses. They are sometimes contrasted with a brain–computer interface, which connects the brain to a computer rather than a device meant to replace missing biological functionality.

Inverse dynamics is an inverse problem. It commonly refers to either inverse rigid body dynamics or inverse structural dynamics. Inverse rigid-body dynamics is a method for computing forces and/or moments of force (torques) based on the kinematics (motion) of a body and the body's inertial properties. Typically it uses link-segment models to represent the mechanical behaviour of interconnected segments, such as the limbs of humans or animals or the joint extensions of robots, where given the kinematics of the various parts, inverse dynamics derives the minimum forces and moments responsible for the individual movements. In practice, inverse dynamics computes these internal moments and forces from measurements of the motion of limbs and external forces such as ground reaction forces, under a special set of assumptions.

Passive dynamics refers to the dynamical behavior of actuators, robots, or organisms when not drawing energy from a supply. Depending on the application, considering or altering the passive dynamics of a powered system can have drastic effects on performance, particularly energy economy, stability, and task bandwidth. Devices using no power source are considered "passive", and their behavior is fully described by their passive dynamics.

In physiology, motor coordination is the orchestrated movement of multiple body parts as required to accomplish intended actions, like walking. This coordination is achieved by adjusting kinematic and kinetic parameters associated with each body part involved in the intended movement. The modifications of these parameters typically relies on sensory feedback from one or more sensory modalities, such as proprioception and vision.

Extended physiological proprioception (EPP) is a concept pioneered by D.C. Simpson (1972) to describe the ability to perceive at the tip of a tool. Proprioception is the concept is that proprioceptors in the muscles and joints, couple with cutaneous receptors to identify and manage contacts between the body and the world. Extended physiological proprioception allows for this same process to apply to contacts between a tool that is being held and the world. The work was based on prostheses developed at the time in response to disabilities incurred by infants as the result of use of the drug thalidomide by mothers from 1957 to 1962, with the tool in this case simply being the prosthesis itself. How a person identifies with themself changes after a lower limb amputation affects body image, functioning, awareness, and future projections.

Targeted reinnervation enables amputees to control motorized prosthetic devices and to regain sensory feedback. The method was developed by Dr. Todd Kuiken at Northwestern University and Rehabilitation Institute of Chicago and Dr. Gregory Dumanian at Northwestern University Division of Plastic Surgery.

<span class="mw-page-title-main">Undulatory locomotion</span>

Undulatory locomotion is the type of motion characterized by wave-like movement patterns that act to propel an animal forward. Examples of this type of gait include crawling in snakes, or swimming in the lamprey. Although this is typically the type of gait utilized by limbless animals, some creatures with limbs, such as the salamander, forgo use of their legs in certain environments and exhibit undulatory locomotion. In robotics this movement strategy is studied in order to create novel robotic devices capable of traversing a variety of environments.

<span class="mw-page-title-main">Orthotics</span> Medical specialty that focuses on the building and designing of artificial legs

Orthotics is a medical specialty that focuses on the design and application of orthoses, or braces. An orthosis is "an externally applied device used to influence the structural and functional characteristics of the neuromuscular and skeletal systems." Orthotists are professionals who specialize in designing these braces.

Terrestrial locomotion by means of a running gait can be accomplished on level surfaces. However, in most outdoor environments an individual will experience terrain undulations requiring uphill running. Similar conditions can be mimicked in a controlled environment on a treadmill also. Additionally, running on inclines is used by runners, both distance and sprinter, to improve cardiovascular conditioning and lower limb strength.

Neuromechanics of orthoses refers to how the human body interacts with orthoses. Millions of people in the U.S. suffer from stroke, multiple sclerosis, postpolio, spinal cord injuries, or various other ailments that benefit from the use of orthoses. Insofar as active orthoses and powered exoskeletons are concerned, the technology to build these devices is improving rapidly, but little research has been done on the human side of these human-machine interfaces.

<span class="mw-page-title-main">Neuromechanics</span> Interdisciplinary field

Neuromechanics is an interdisciplinary field that combines biomechanics and neuroscience to understand how the nervous system interacts with the skeletal and muscular systems to enable animals to move. In a motor task, like reaching for an object, neural commands are sent to motor neurons to activate a set of muscles, called muscle synergies. Given which muscles are activated and how they are connected to the skeleton, there will be a corresponding and specific movement of the body. In addition to participating in reflexes, neuromechanical process may also be shaped through motor adaptation and learning.

As humans move through their environment, they must change the stiffness of their joints in order to effectively interact with their surroundings. Stiffness is the degree to a which an object resists deformation when subjected to a known force. This idea is also referred to as impedance, however, sometimes the idea of deformation under a given load is discussed under the term "compliance" which is the opposite of stiffness . In order to effectively interact with their environment, humans must adjust the stiffness of their limbs. This is accomplished via the co-contraction of antagonistic muscle groups.

<span class="mw-page-title-main">Proportional myoelectric control</span>

Proportional myoelectric control can be used to activate robotic lower limb exoskeletons. A proportional myoelectric control system utilizes a microcontroller or computer that inputs electromyography (EMG) signals from sensors on the leg muscle(s) and then activates the corresponding joint actuator(s) proportionally to the EMG signal.

X-ray motion analysis is a technique used to track the movement of objects using X-rays. This is done by placing the subject to be imaged in the center of the X-ray beam and recording the motion using an image intensifier and a high-speed camera, allowing for high quality videos sampled many times per second. Depending on the settings of the X-rays, this technique can visualize specific structures in an object, such as bones or cartilage. X-ray motion analysis can be used to perform gait analysis, analyze joint movement, or record the motion of bones obscured by soft tissue. The ability to measure skeletal motions is a key aspect to one's understanding of vertebrate biomechanics, energetics, and motor control.

<span class="mw-page-title-main">Gait deviations</span> Medical condition

Gait deviations are nominally referred to as any variation of standard human gait, typically manifesting as a coping mechanism in response to an anatomical impairment. Lower-limb amputees are unable to maintain the characteristic walking patterns of an able-bodied individual due to the removal of some portion of the impaired leg. Without the anatomical structure and neuromechanical control of the removed leg segment, amputees must use alternative compensatory strategies to walk efficiently. Prosthetic limbs provide support to the user and more advanced models attempt to mimic the function of the missing anatomy, including biomechanically controlled ankle and knee joints. However, amputees still display quantifiable differences in many measures of ambulation when compared to able-bodied individuals. Several common observations are whole-body movements, slower and wider steps, shorter strides, and increased sway.

The term “soft robots” designs a broad class of robotic systems whose architecture includes soft elements, with much higher elasticity than traditional rigid robots. Articulated Soft Robots are robots with both soft and rigid parts, inspired to the muscloloskeletal system of vertebrate animals – from reptiles to birds to mammalians to humans. Compliance is typically concentrated in actuators, transmission and joints while structural stability is provided by rigid or semi-rigid links.

Álvaro Ríos Poveda is a Colombian electronic engineer, university professor, and researcher who specializes in biomedical engineering and mechatronics. He has performed research on myoelectric prostheses, sensory feedback, and bionic vision technologies.

References

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  2. ↑ Stein, J. L.; Flowers, W. C. (1988). "Stance phase control of above-knee prostheses: knee control versus SACH foot design". Journal of Biomechanics. 20 (1): 19–28. doi:10.1016/0021-9290(87)90263-6. hdl: 2027.42/26850 . PMID   3558425.
  3. 1 2 Grimes, D. L. (1979). An active multi-mode above knee prosthesis controller. PhD Thesis, Cambridge, MA, MIT, Department of Mechanical Engineering.
  4. 1 2 Grimes, D. L.; Flowers, W. C.; Donath, M. (1977). "Feasibility of an active control scheme for above knee prostheses". Journal of Biomechanical Engineering. 99 (4): 215–221. doi:10.1115/1.3426293.
  5. ↑ Flowers, W. C.; Mann, R. W. (1977). "Electrohydraulic knee-torque controller for a prosthesis simulator". Journal of Biomechanical Engineering. 99 (4): 3–8. doi:10.1115/1.3426266. PMID   23720163.
  6. ↑ Donath, M. (1974). Proportional EMG control for above-knee prosthesis. Master’s Thesis Cambridge, MA, MIT, Department of Mechanical Engineering
  7. ↑ Flowers, W. C. (1973). A man-interactive simulator system forabove-knee prosthetics studies. PhD Thesis, Cambridge, MA, MIT, Department of Mechanical Engineering.
  8. ↑ Popovic, D. and Schwirtlich, L. (1988). Belgrade active A/K prosthesis. Electrophysiological Kinesiology (International Congress Series, No. 804), de Vries, J. (ed.). Amsterdam, Excerpta Medica, pp. 337–343
  9. ↑ Au, S., Bonato, P.and Herr, H. (2005).An EMG-position controlled system for an active ankle-foot prosthesis: an initial experimental study. Proceedings of the IEEE International Conference on Rehabilitation Robotics, pp. 375–379
  10. 1 2 Aghasadeghi, Navid, et al. "Learning impedance controller parameters for lower-limb prostheses." Intelligent robots and systems (IROS), 2013 IEEE/RSJ international conference on. IEEE, 2013.
  11. ↑ Hogan, Neville. "Impedance control: An approach to manipulation." American Control Conference, 1984. IEEE, 1984.
  12. ↑ Sup, Frank; Bohara, Amit; Goldfarb, Michael (2008). "Design and control of a powered transfemoral prosthesis". The International Journal of Robotics Research. 27 (2): 263–273. doi:10.1177/0278364907084588. PMC   2773553 . PMID   19898683.
  13. ↑ Kamen, Gary. Electromyographic Kinesiology. In Robertson, DGE et al. Research Methods in Biomechanics. Champaign, IL: Human Kinetics Publ., 2004.
  14. 1 2 3 Hargrove LJ; Young AJ; Simon AM; et al. (2015-06-09). "Intuitive control of a powered prosthetic leg during ambulation: A randomized clinical trial". JAMA. 313 (22): 2244–2252. doi: 10.1001/jama.2015.4527 . ISSN   0098-7484. PMID   26057285.
  15. 1 2 3 Zhao, Huihua; Reher, Jake; Horn, Jonathan; Paredes, Victor; Ames, Aaron D. (2015-01-01). "Realization of nonlinear real-time optimization based controllers on self-contained transfemoral prosthesis". Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems. ICCPS '15. New York, NY, USA: ACM. pp. 130–138. doi:10.1145/2735960.2735964. ISBN   9781450334556. S2CID   5764182.
  16. 1 2 Tarantino, S.; Clemente, F.; Barone, D.; Controzzi, M.; Cipriani, C. (2017). "The myokinetic control interface: tracking implanted magnets as a means for prosthetic control". Scientific Reports. 7 (1): 17149. Bibcode:2017NatSR...717149T. doi:10.1038/s41598-017-17464-1. ISSN   2045-2322. PMC   5719448 . PMID   29215082.
  17. ↑ Visconti, P.; Gaetani, F.; Zappatore, G.A.; Primiceri, P. (2018). "Technical Features and Functionalities of Myo Armband: An Overview on Related Literature and Advanced Applications of Myoelectric Armbands Mainly Focused on Arm Prostheses". International Journal on Smart Sensing and Intelligent Systems. 11 (1): 1–25. doi: 10.21307/ijssis-2018-005 . ISSN   1178-5608.
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