WO2010088635A1 - Model-based neuromechanical controller for a robotic leg - Google Patents
Model-based neuromechanical controller for a robotic leg Download PDFInfo
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- WO2010088635A1 WO2010088635A1 PCT/US2010/022783 US2010022783W WO2010088635A1 WO 2010088635 A1 WO2010088635 A1 WO 2010088635A1 US 2010022783 W US2010022783 W US 2010022783W WO 2010088635 A1 WO2010088635 A1 WO 2010088635A1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
- A61F2/68—Operating or control means
- A61F2/70—Operating or control means electrical
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
- A61F2/60—Artificial legs or feet or parts thereof
- A61F2/64—Knee joints
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
- A61F2/60—Artificial legs or feet or parts thereof
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
- A61F2/68—Operating or control means
- A61F2/74—Operating or control means fluid, i.e. hydraulic or pneumatic
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
- A61F2002/5003—Prostheses not implantable in the body having damping means, e.g. shock absorbers
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
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- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
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- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
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- A—HUMAN NECESSITIES
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- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
- A61F2/76—Means for assembling, fitting or testing prostheses, e.g. for measuring or balancing, e.g. alignment means
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
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- A—HUMAN NECESSITIES
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- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
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- A61F2002/7645—Measuring means for measuring torque, e.g. hinge or turning moment, moment of force
Definitions
- the CPG consists of layers of neuron pools in the spinal cord [Rybak, I. A., Shevtsova, N. A., Lafreniere-Roula, M., McCrea, D. A., 2006. Modelling spinal circuitry involved in locomotor pattern generation: insights from deletions during fictive locomotion. J Physiol 577 (Pt 2), 617-639] which, through other neuron pools channeling muscle synergies, provide rhythmic activity to the leg extensor and flexor muscles [Dietz, V., 2003. Spinal cord pattern generators for locomotion.
- Biol Cybern 84 (1), 1- 11; Paul, C, Bellotti, M., Jezernik, S., Curt, A., 2005. Development of a human neuro-musculo-skeletal model for investigation of spinal cord injury. Biol Cybern 93 (3), 153-170] have developed into essential tools for studying different control strategies in animal and human locomotion. The emphasis of these models has been to reproduce the architecture of the CPG and underlying reflexes suggested by experiments [Pearson, K., Ekeberg, O., Buschges, A., 2006. Assessing sensory function in locomotor systems using neuro-mechanical simulations. Trends Neurosci 29 (11), 625-631].
- the invention is a model-based method for controlling a robotic limb comprising at least one joint, comprising the steps of receiving feedback data relating to the state of the robotic limb at a finite state machine, determining the state of the robotic limb using the finite state machine and the received feedback data, determining, using a neuromuscular model, muscle geometry and reflex architecture information, and state information from the finite state machine, at least one desired joint torque or stiffness command to be sent to the robotic limb and commanding the biomimetric torques and stiffnesses determined by the muscle model processor at the robotic limb joint.
- FIGs. 4A and 4B depict walking of a human model self-organized from dynamic interplay between model and ground, and the corresponding ground reaction force, respectively, according to one aspect of the present invention
- Figs. 6A-D depict adaptation to walking up stairs, including snapshots of the model (Fig. 6A), net work (Fig. 6B), extensor muscle activation patterns (Fig.
- Figs. 7A-D depict adaptation to walking down stairs, including snapshots of the model (Fig. 7A), net work (Fig. 7B), extensor muscle activation patterns (Fig. 7C), and the corresponding ground reaction force (Fig. 7D), according to one aspect of the present invention
- FIG. 8 is a schematic of a muscle-tendon model, according to one aspect of the present invention.
- FIG. 9 depicts a contact model, according to one aspect of the present invention.
- Figs. lOA-C depict an exemplary embodiment of an ankle-foot prosthesis used in a preferred embodiment, depicting the physical system (Fig. 10A), a diagram of the drive train (Fig. 10B), and a mechanical model (Fig. 10C), respectively, according to one aspect of the present invention;
- FIG. 11 is a diagram of an exemplary embodiment of a finite state machine synchronized to the gait cycle, with state transition thresholds and equivalent ankle-foot biomechanics during each state, used to implement top level control of the ankle-foot prosthesis of Figs. lOA-C, according to one aspect of the present invention
- FIG. 12 is a block diagram of an exemplary embodiment of a control system for an ankle-foot prosthesis, according to one aspect of the present invention.
- Figs. 13A-C are exemplary plots of prosthesis torque over one complete gait cycle for three walking conditions: level-ground (Fig. 13A), ramp ascent (Fig. 13B), and ramp descent (Fig. 13C), according to one aspect of the present invention
- Figs. 14A-C depict an exemplary embodiment of the musculoskeletal model as implemented on the prosthetic microcontroller, including the two-link ankle joint model (Fig. 14A), detailed Hill-type muscle model (Fig. 14B), and geometry of the muscle model skeletal attachment (Fig. 14C), according to one aspect of the present invention;
- Fig. 15 depicts an exemplary embodiment of a reflex scheme for the virtual plantar flexor muscle, including the relationship among ankle angle, muscle force, and the plantar flexor component of ankle torque, according to one aspect of the present invention
- Figs. 16A and 16B depict prosthesis-measured torque and angle trajectories during trials with an amputee subject compared to those of the biological ankle of a weight and height-matched subject with intact limbs, including ankle torque and ankle angle, respectively;
- Fig. 17 is a comparison of the torque profile after parameter optimization to the biologic torque profile, according to one aspect of the present invention.
- Figs. 18A-C are plots of experimentally measured prosthesis torque- angle trajectories for an exemplary embodiment of the invention for three different walking conditions: level ground (Fig. 18A), ramp ascent (Fig. 18B), and ramp descent (Fig. 18C).
- a control architecture is presented to command biomimetic torques at the ankle, knee, and hip joints of a powered leg prosthesis, orthosis, or exoskeleton during walking.
- the powered device includes artificial ankle and knee joints that are torque controllable.
- Appropriate joint torques are provided to the user as determined by the feedback information provided by sensors mounted at each joint of the robotic leg device. These sensors include, but are not limited to, angular joint displacement and velocity using digital encoders, hall-effect sensors or the like, torque sensors at the ankle and knee joints and at least one inertial measurement unit (IMU) located between the knee and the ankle joints.
- IMU inertial measurement unit
- Actuator means a type of motor, as defined below.
- Antist-antagonist actuator means a mechanism comprising (at least) two actuators that operate in opposition to one another: an agonist actuator that, when energized, draws two elements together and an antagonist actuator that, when energized, urges the two elements apart.
- Extension means a bending movement around a joint in a limb that increases the angle between the bones of the limb at the joint.
- “Flexion” means a bending movement around a joint in a limb that decreases the angle between the bones of the limb at the joint.
- “Motor” means an active element that produces or imparts motion by converting supplied energy into mechanical energy, including electric, pneumatic, or hydraulic motors and actuators.
- a muscle stimulation parameter STIM(t) is required.
- This parameter can be determined from either an outside input or a local feedback loop.
- the STIM(t) is computed based on local feedback loops.
- This architecture is based on the reflex feedback framework developed by Geyer and Herr [H. Geyer, H. Herr, "A muscle-reflex model that encodes principles of legged mechanics predicts human walking dynamics and muscle activities," (Submitted for publication), herein incorporated by reference in its entirety].
- the neural-control is designed to mimic the stretch reflex of an intact human muscle.
- This neuromuscular reflex-based control methodology allows the biomimetic robotic leg to replicate human-like joint mechanics.
- Neuromechanical model A human model with a reflex control that encodes principles of legged mechanics predicts human walking dynamics and muscle activities. While neuroscientists identify increasingly complex neural networks that control animal and human gait, biomechanists find that locomotion requires little motor control if principles of legged mechanics are heeded. Here it is shown how muscle reflex behavior could be vital to link these two observations.
- a model of human locomotion was developed that is driven by muscle reflex behaviors that encode principles of legged mechanics. Equipped with this principle-based reflex control, the model stabilizes into the walking gait from its dynamic interplay with the ground, tolerates ground disturbances, and self-adapts to stairs. Moreover, the model shows qualitative agreement with joint angles, joint torques and muscle activations known from experiments, suggesting that human motor output could largely be shaped by muscle reflex behaviors that link principles of legged mechanics into the neural networks responsible for locomotion.
- a human walking model with a motor control is based on muscle reflexes, which are designed to include such principles of legged mechanics. These principles derive from simple conceptual models of legged locomotion and include the reliance on compliant leg behavior in stance [Blickhan, R., 1989. The spring-mass model for running and hopping. J. of Biomech. 22, 1217- 1227; Ghigliazza, R., Altendorfer, R., Holmes, P., Koditschek, D., 2003. A simply stabilized running model. SIAM J. Applied. Dynamical Systems 2 (2), 187-218; Geyer, H., Seyfarth, A., Singhhan, R., 2006. Compliant leg behaviour explains the basic dynamics of walking and running.
- the landing of the other (leading) leg initiates swing by adding/subtracting a constant stimulation to HFL/GLU, respectively, and by suppressing VAS proportionally to the load borne by the other leg (Fig. 2E).
- the actual leg swing is facilitated by HFL using L+ until it gets suppressed by L- of HAM (Fig. 2F).
- HFL's stimulation is biased dependent on the upper body's lean at take-off.
- using F+ for GLU and HAM retracts and straightens the leg toward the end of swing.
- the now unsuppressed L+ of TA drives the ankle to a flexed position (Fig. 2G).
- GAS gastrocnemius
- TA tibialis anterior
- Fig. 2C tibialis anterior
- F+ local positive force feedback
- This reflex inhibition is only active if ⁇ > 0 and the knee is actually extending.
- the point mass representation is discarded and an upper body 255 around which the legs can be swung (Fig. 2D) is introduced.
- This upper body 255 combines head, arms and trunk (HAT).
- GLU gluteus muscle group
- HFL hip flexor muscle group
- the GLU 260 and the HFL 265 are stimulated with a proportional-derivative signal of the HAT's 255 forward lean angle ⁇ with respect to gravity, S GLU/HFL ⁇ ⁇ [k P ( ⁇ - ⁇ re f ) + k d d ⁇ /dt], where k p and kd are the proportional and derivative gains, and ⁇ re f is a reference lean angle [for similar approaches compare, for instance, G ⁇ nther, M., Ruder, H., 2003. Synthesis of two-dimensional human walking: a test of the ⁇ - model. Biol. Cybern. 89, 89-106].
- HAM biarticular hamstring muscle group
- S HAM ⁇ S GLU to counter knee hyperextension that results from a large hip torque developed by the GLU 260 when pulling back the heavy HAT 255. Since hip torques can only balance the HAT 255 if the legs bear sufficient weight, the stimulations of the GLU 260, HAM 270, and HFL 265 are modulated for each leg proportionally to the amount of body weight it bears. As a result, each leg's hip muscles contribute to the HAT's balance control only during stance.
- Swing leg pro- and retraction The human model's structure is complete, except for a muscle-reflex control that produces swing leg pro- and retraction. It is assumed that a stance leg's functional importance reduces in proportion to the amount of body weight (bw) borne by the contralateral leg, and initiate swing leg protraction already in double support (Fig. 2E).
- the human model detects which leg enters stance last (contralateral leg), and suppresses F+ of the ipsilateral leg's VAS 240 in proportion to the weight the contralateral leg bears, S VAS .
- the contralateral suppression allows the knee to break its functional spring behavior, and flex while the ankle extends, pushing the leg off the ground and forward.
- Table 2 presents the swing reflex equations used in the preferred embodiment
- FIG. 3 graphically depicts pattern generation according to this aspect of the invention.
- reflexes instead of a central pattern, reflexes generate the muscle stimulations, S m 305, 310.
- Left (L) 320 and right (R) 330 leg have separate stance 340, 345 and swing 350, 355 reflexes, which are selected based on contact sensing 360, 365 from ball and heel sensors 370, 375.
- the reflex outputs depend on mechanical inputs, M 1 380, 385, intertwining mechanics and motor control.
- FIG. 4 A and 4B depict walking of a human model self- organized from dynamic interplay between model and ground and the corresponding ground reaction force, respectively, according to one aspect of the present invention.
- snapshots of human model taken every 250ms (Fig. 4A) and corresponding model GRF (Fig.
- the model slightly collapses and slows down in its first step (Fig. 4A). If its parameters are chosen properly, however, the model rapidly recovers in the following steps, and walking self-organizes from the dynamic interplay between model and ground.
- the vertical ground reaction force (GRF) of the legs in stance shows the M-shape pattern characteristic for walking gaits (Fig. 4B), indicating similar whole-body dynamics of model and humans for steady state walking.
- FIGs. 5 A-C compare steady state walking at 1.3ms "1 for the model and a human subject for hip (Fig. 5A), knee (Fig. 5B), and ankle (Fig. 5C), respectively, according to one aspect of the present invention.
- Figs. 5A-C normalized to one stride from heel-strike to heel-strike of the same leg, the model's steady-state patterns of muscle activations, torques, and angles of hip, knee and ankle are compared to human walking data (adapted from Perry, 1992).
- HFL adductor longus
- GLU gluteus maximum
- HAM semimembranosis
- VAS vastus lateralis
- the reflex model not only generates ankle kinematics ⁇ a and torques ⁇ a observed for the human ankle in walking, but also predicts SOL, TA and GAS activities that resemble the experimental SOL, TA and GAS activities as inferred from their surface electromyographs. For SOL and GAS, this activity is generated exclusively by their local F+ reflexes in stance. For TA, its L+ reflex responds with higher activity to plantar flexion of the foot in early stance, but gets suppressed by F- from SOL during the remainder of that phase. Only when SOL activity reduces at the transition from stance to swing (60% of stride), does the TA's L+ resume, pulling the foot against plantar flexion.
- the model lacks the observed VAS activity in late swing that continues into early stance. Only after heel-strike, the F+ of VAS engages and can activate the muscle group in response to the loading of the leg. The delay in extensor activities causes not only a relatively weak knee in early stance, but also the heavy HAT to tilt forward after impact.
- the balance control of the HAT engages gradually with the weight borne by the stance leg, the balance reflexes are silent until heel-strike and then must produce unnaturally large GLU and HAM activities to return the HAT to its reference lean (Fig. 5C).
- the model's hip trajectory cph and torque pattern Th least resemble that of humans whose hip extensors GLU and HAM are active before impact and can prevent such an exaggerated tilt of the trunk.
- FIGs. 6A-D show an example in which the model encounters a sequence of stairs going up 4cm each.
- Figs. 6A-D depict adaptation to walking up stairs, including snapshots of the model (Fig. 6A), net work (Fig. 6B), extensor muscle activation patterns (Fig. 6C), and the corresponding ground reaction force (Fig. 6D), according to one aspect of the present invention.
- Figs. 6A-D approaching from steady- state walking at 1.3ms ⁇ eight strides of the human model are shown covering five steps of 4cm incline each.
- the model returns to steady-state walking on the 8th stride.
- One stride is defined from heel-strike to heel-strike of the right leg.
- Shown in Fig. 6A are snapshots of the model at heel-strike and toe-off of the right leg. For this leg are further shown, in Fig. 6B, the net work during stance generated at hip, knee and ankle with positive work being extension work; in Fig. 6C, the activation patterns of the five extensor muscles of each stride; and, in Fig. 6D, the corresponding ground reaction forces 650 normalized to body weight (bw), with ground reaction forces of the left leg 660 are included for comparison.
- the slow down of the model reduces the force the ankle extensors GAS and SOL feel during stance, and their force feedback reflexes produce slightly less muscle stimulation, lowering the net work of the ankle (Fig. 6B and 6C).
- strides 4 and 5 the model settles into upstair walking at about lms l where the forward and upward thrust is generated mainly at the hip and knee. After reaching the plateau in the 6th stride, the model recovers into its original steady- state walking speed of 1.3ms l in the 8th stride.
- Figs. 7A-D depict adaptation to walking down stairs, including snapshots of the model (Fig. 7A), net work (Fig. 7B), extensor muscle activation patterns (Fig. 7C), and the corresponding ground reaction force (Fig. 7D), according to one aspect of the present invention.
- Figs. 7A-D approaching from steady-state walking at 1.3ms ⁇ eight strides of the human model are shown covering five steps of 4cm incline each. The model returns to steady-state walking on the 8th stride.
- One stride is defined from heel-strike to heel-strike of the right leg.
- Shown in Fig. 7A are snapshots of the model at heel-strike and toe-off of the right leg.
- Fig. 7B the net work during stance generated at hip, knee and ankle with positive work being extension work
- Fig. 7C the activation patterns of the five extensor muscles of each stride
- Fig. 7D the corresponding ground reaction forces 750 normalized to body weight (bw), with ground reaction forces of the left leg 760 are included for comparison.
- the model returns to steady state walking at 1.3ms l in the 14th stride after covering five steps down with 4cm decline each.
- Figs. 7A-D continues the walking sequence with the model encountering stairs going down. At the end of the 9th stride, the model hits the first step down with its right foot (Fig. 7A).
- the model keeps the larger step length in the downward motion (strides 11 and 12), where the model's downward acceleration is countered by increased activity of the GLU, HAM and VAS immediately following impact (Fig. 7C and 7D), which reduces net positive work at the hip and increases net negative work at the knee (Fig. 7B), and stabilizes the model into walking down at about 1.5ms "1 .
- the lack of downward acceleration slows down the model, which automatically reduces its step length (Fig. 7A) and drives it back into steady-state walking at 1.3ms "1 within the 13th and 14th step.
- the key to the model's tolerance and adaptation are its dynamic muscle -reflex responses.
- the rebound of the stance leg depends on how much load the leg extensors SOL, GAS and VAS feel, which guarantees that the leg yields sufficiently to allow forward progression when going up, but brakes substantially when going down.
- the forward propulsion of the swing leg varies with the model dynamics. Sudden deceleration after impact of the opposite leg, forward lean of the upper body, and ankle extension rate near the end of stance-all contribute to leg propulsion in swing.
- FIG. 8 is a schematic of a muscle-tendon model, according to one aspect of the present invention.
- active, contractile element (CE) 810 together with series elasticity (SE) 820 form the muscle -tendon unit (MTU) in normal operation.
- CE 810 stretches beyond its optimum length ZQ E 830 (ZQ E > £ op t 840)
- parallel elasticity (PE) 850 engages.
- buffer elasticity (BE) 860 prevents the active CE 810 from collapsing if SE 820 is slack (£ M ⁇ u 870 - £ CE 830 ⁇
- an active, Hill-type contractile element produces force in line with a series elasticity (SE).
- SE series elasticity
- the MTU model includes a parallel elasticity (PE), which engages if the CE stretches beyond its optimum length Copt .
- PE parallel elasticity
- BE buffer elasticity
- Table 3 presents individual MTU parameters. All parameters are estimated from Yamaguchi et al. [Yamaguchi, G. T., Sawa, A. G. -U., Moran, D. W., Fessler, M. J., Winters, J. M., 1990. A survey of human musculotendon actuator parameters. In: Winters, J., Woo, S. -Y. (Eds.), Multiple Muscle Systems: Biomechanics and Movement Organization. Springer- Verlag, New York, pp. 717- 778].
- the maximum isometric forces F max are estimated from individual or grouped muscle -physio logical cross-sectional areas assuming a force of 25N per cm "2 .
- the maximum contraction speeds v max are set to 6£ opt s "1 for slow muscles and to 12£ opt s "1 for medium fast muscles.
- the optimum CE lengths £ opt and the SE slack lengths £ s i ac k reflect muscle fiber and tendon lengths.
- the MTUs have common and individual parameters.
- the MTUs connect to the skeleton by spanning one or two joints.
- r m ( ⁇ ) ro.
- the seven segments of the human model are simple rigid bodies whose parameters are listed in Table 5. Their values are similar to those used in other modeling studies, for instance, in G ⁇ nther and Ruder [G ⁇ nther, M., Ruder, H., 2003. Synthesis of two-dimensional human walking: a test of the ⁇ - model. Biol. Cybern. 89, 89-106].
- the segments are connected by revolute joints. As in humans, these joints have free ranges of operation (70 ° ⁇ ⁇ a ⁇ 130 ° , cpk ⁇ 175 ° and cph ⁇ 230 ° ) outside of which mechanical soft limits engage, which is modelled in the same way as the ground impact points.
- the model's segments have different masses ms and lengths Z$, and characteristic distances of their local center of mass, d ⁇ s, and joint location, dj,s (measured from distal end), and inertias ⁇ s.
- a ground stiffness k F re f / ⁇ y re f and a maximum relaxation speed v max , which characterizes how quickly the ground surface can restore its shape after being deformed.
- v max ⁇ describes a perfectly elastic ground impact where the ground always pushes back against the CP
- v max 0 describes a perfectly inelastic impact where the ground, like sand, pushes back on the CP for downward velocities, but cannot push back for upward velocities.
- the same impact model is used to describe the mechanical soft limits of the model's joints (see previous section) with a soft limit stiffness of 0.3N m deg l and a maximum relaxation speed of ldeg s "1 .
- Fig. 9 depicts a contact model, according to one aspect of the present invention.
- contact occurs 910 if contact point 920 falls below yo .
- the horizontal ground reaction force F x is modeled as sliding friction proportional to Fy with sliding coefficient ⁇ s i .
- F x is also modeled as the product of force-length and force-velocity relationships, which slightly differ from those earlier in order to allow for interactions with the ground in both directions around the stiction reference point xo.
- the model switches back to sliding friction if F x exceeds the stiction limit force ⁇ st F y .
- a neuromuscular model of human locomotion self-organizes into the walking gait after an initial push, tolerates sudden changes in ground level, and adapts to stair walking without interventions.
- Central to this model's tolerance and adaptiveness is its reliance on muscle reflexes, which integrate sensory information about locomotion mechanics into the activation of the leg muscles.
- the model shows that in principle no central input is required to generate walking motions, suggesting that reflex inputs that continuously mediate between the nervous system and its mechanical environment may even take precedence over central inputs in the control of normal human locomotion.
- the model not only converges to known joint angle and torque trajectories of human walking, but also predicts some individual muscle activation patterns observed in walking experiments. This match between predicted and observed muscle activations suggests that principles of legged mechanics could play a larger role in motor control than anticipated before, with muscle reflexes linking these principles into the neural networks responsible for locomotion.
- the neuromechanical model of the invention has been implemented as a muscle reflex controller for a powered ankle- foot prosthesis.
- This embodiment is an adaptive muscle-reflex controller, based on simulation studies, that utilizes an ankle plantar flexor comprising a Hill-type muscle with a positive force feedback reflex.
- the model's parameters were fitted to match the human ankle's torque-angle profile as obtained from level-ground walking measurements of a weight and height-matched intact subject walking at 1 m/sec. Using this single parameter set, clinical trials were conducted with a transtibial amputee walking on level ground, ramp ascent, and ramp descent conditions.
- the neuromuscular model with a positive force feedback reflex scheme as the basis of control of the invention was used as part of the control system for a powered ankle- foot prosthesis.
- the controller presented here employs a model of the ankle-foot complex for determining the physical torque to command at the ankle joint.
- the ankle joint is provided with two virtual actuators.
- the actuator is a Hill-type muscle with a positive force feedback reflex scheme. This scheme models the reflexive muscle response due to some combination of afferent signals from muscle spindles and Golgi tendon organs.
- an impedance is provided by a virtual rotary spring-damper.
- the parameters of this neuromuscular model were fitted by an optimization procedure to provide the best match between the measured ankle torque of an intact subject walking at a target speed of 1.0 m/sec, and the model's output torque when given as inputs the measured motion of the intact subject.
- the neuromuscular model-based prosthetic controller was used to provide torque commands to a powered ankle-foot prosthesis worn by an amputee. This control strategy was evaluated using two criteria. First, the controller was tested for the ability to produce prosthesis ankle torque and ankle angle profiles that qualitatively match those of a comparable, intact subject at a target level-ground walking speed. The second performance criterion was the controller's ability to exhibit a biologically- consistent trend of increasing gait cycle net- work for increasing walking slope without changing controller parameters. Detecting variations in ground slope is difficult using typical sensors, so a controller with an inherent ability to adapt to these changes is of particular value.
- Figs. lOA-C depict the physical system (Fig. 10A), a diagram of the drive train (Fig. 10B), and a mechanical model (Fig. 10C) for an exemplary embodiment of an ankle-foot prosthesis used in a preferred embodiment.
- the ankle- foot prosthesis used for this study is one in development by iWalk, LLC.
- This prosthesis is a successor to the series of prototypes developed in the Biomechatronics Group of the MIT Media Laboratory, which are described in U.S. Pat. App. Ser. No. 12/157,727, filed June 12, 2008, the entire disclosure of which has been incorporated by reference herein in its entirety.
- the prosthesis is a completely self-contained device having the weight (1.8 kg) and size of the intact biological ankle-foot complex.
- Fig. 1OA Seen in Fig. 1OA are housing 1005 for the motor, transmission, and electronics, ankle joint 1010, foot 1015, unidirectional parallel leaf spring 1020, and series leaf spring 1025.
- Fig. 1OB Depicted in Fig. 1OB are timing belt 1030, pin joint main housing 1035, motor 1040, ball screw 1045, ankle joint 1010, ball nut 1050 pin joint (series spring) 1055, and foot motion indicator 1060.
- Depicted in the mechanical model of Fig. 1OC are parent link 1065, motor 1040, transmission 1070, series spring 1025, unidirectional parallel spring 1020, foot 1015, series spring movement arm r s 1075, spring rest length 1080, and SEA 1085.
- the rotary elements in the physical system are shown as linear equivalents in the model schematic for clarity.
- the ankle joint is a rolling bearing design joining a lower foot structure to an upper leg shank structure topped with a prosthetic pyramid fixture for attachment to the amputee's socket.
- the foot includes a passive low profile Flex- FootTM (OsurTM) to minimize ground contact shock to the amputee.
- a unidirectional leaf spring, the parallel spring acts across the ankle joint, engaging when the ankle and foot are perpendicular to each other. It acts in parallel to a powered drive train, providing the passive function of an Achilles tendon.
- the powered drive train is a motorized link across the ankle joint as represented in Figure 1OB.
- the upper leg shank end From the upper leg shank end, it consists, in series, of a brushless motor, (Powermax EC-30, 200 Watt, 48V, Maxon) operating at 24V, a belt drive transmission with 40/15 reduction, and a 3 mm pitch linear ball screw. At this operating voltage, the theoretical maximum torque that can be generated by the motor through the drivetrain is approximately 340 Nm.
- a brushless motor Powermax EC-30, 200 Watt, 48V, Maxon
- the theoretical maximum torque that can be generated by the motor through the drivetrain is approximately 340 Nm.
- the series spring a Kevlar-composite leaf spring
- the effective rotary stiffness of the series spring is 533 N'm/rad for positive torque, and 1200 N'm/rad for negative torque, where positive torque (or plantar flexion torque) is that tending to compress the series spring as represented in Figure 1OC.
- the drive train and the series spring together comprise a series-elastic actuator (SEA) [G. A. Pratt and M. M.
- a hall-effect angle sensor at the ankle joint is a primary control input, and has a range of -0.19 to 0.19 radians, where zero corresponds to the foot being perpendicular to the shank.
- Joint angle is estimated with a linear hall-effect sensor (Allegro A1395) mounted on the main housing. This sensor is proximate to a magnet that is rigidly connected to the foot structure so that the magnetic axis is tangent to the arc of the magnet's motion.
- the magnetic field strength at the sensor location varies as the magnet rotates past the sensor.
- Strain gauges are located inside the prosthetic pyramid attachment, allowing for an estimate of the torque at the ankle joint. Strain gauges located on the series spring permit sensing of the output torque of the motorized drive train, thereby allowing for closed- loop force control of the SEA.
- the motor itself contains Hall- effect commutation sensors and is fitted with an optical shaft encoder that enables the use of advanced brushless motor control techniques.
- Microcontroller Overall control and communications for the ankle- foot prosthesis are provided by a single-chip, 16-bit, DSP oriented microcontroller, the Microchip Technology Incorporated dsPIC33FJ128MC706.
- the microcontroller operates at 40 million instructions per second, with 128 kilo-bytes of flash program memory, and 16384 bytes of RAM. It provides adequate computation to support real time control.
- a second 16-bit dsPIC33FJ128MC706 was used as a dedicated motor controller.
- a high speed digital link between the main microcontroller and the motor microcontroller supplied virtually instantaneous command of the motor.
- a high speed serial port of the microcontroller is dedicated to external communications. This port may be used directly via cable or may have a wide variety of wireless communication devices attached. For the present study, the 500 Hz sensor and internal state information is telemetered over the serial port at 460 Kilobaud and transmitted via an IEEE 802.1 Ig wireless local area network device (Lantronix Wiport).
- Battery All power for the prosthesis was provided by a 0.22 kg lithium polymer battery having a 165 Watt-Hour/kg energy density. The battery was able to provide a day's power requirements including 5000 steps of powered walking.
- Optimal Mechanical Component Selection was provided by a 0.22 kg lithium polymer battery having a 165 Watt-Hour/kg energy density. The battery was able to provide a day's power requirements including 5000 steps of powered walking.
- Control Architecture The purpose of the control architecture is to command an ankle torque appropriate to the amputee's gait cycle as determined from available sensor measurements of prosthetic ankle state.
- the controller determines the appropriate torque using a neuromuscular model of the human ankle-foot complex.
- a hinge joint representing the human ankle joint
- a dorsiflexor which acts as either a bi-directional proportional- derivative position controller, or a unidirectional virtual rotary spring-damper, depending on the gait phase.
- a finite state machine maintains an estimate of the phase of the amputee's gait.
- one or the other, or both of the virtual actuators produce torques at the virtual ankle joint.
- the net virtual torque is then used as the ankle torque command to the prosthesis hardware.
- Physical torque at the ankle joint is produced by both the motorized drive train and the parallel spring.
- the ankle angle sensor is used to determine the torque produced by the parallel spring, and the remaining desired torque is commanded through the motor controller.
- Top Level State Machine Control Top level control of the prosthesis is implemented by a finite state machine synchronized to the gait cycle. During walking, two states are recognized: swing phase and stance phase. Prosthesis sensor inputs (ankle torque as estimated from the pyramid strain gauges, ankle angle, and motor velocity) are continuously observed to determine state transitions. Conditions for these state transitions were experimentally determined. Fig. 11 depicts the operation of the state machine and the transition conditions. The dorsiflexor and plantar flexor virtual actuators develop torque depending on the gait state estimate from the state machine.
- the swing state 1110 is visually depicted as SW 1120, and stance 1130 is divided into controlled plantar flexion (CP) 1140, controlled dorsiflexion (CD) 1150, and powered plantar flexion (PP) 1160.
- State transitions 1170, 1180 are determined using the prosthesis ankle torque, Tp, as measured from the pyramid strain gauges, and prosthesis ankle angle, ⁇ .
- Tp prosthesis ankle torque
- ⁇ prosthesis ankle angle
- the transition to swing phase when the foot leaves the ground is detected by either a drop in total ankle torque to less than 5 N'm, as measured using the pyramid strain gauges, or a drop in measured ankle angle, ⁇ , below -0.19 radians to prevent angle sensor saturation.
- Positive torque is defined as actuator torque tending to plantar flex the ankle, and positive angles correspond to dorsiflexion.
- the ankle torque developed during the stance phase must exceed 20 N'm for these transitions to be enabled.
- a 200 ms buffer time provides a minimum time frame for the stance period. The transition to stance phase upon heel-strike is detected by a decrease in torque below -7 N'm as measured using the pyramid strain gauges.
- FIG. 12 A block diagram of an exemplary embodiment of a control system for an ankle-foot prosthesis according to this aspect of the invention is shown in Fig. 12. Depicted in Fig. 12 are neuromuscular model 12010, parallel spring model 1220, lead compensator 1230, friction compensator 1240, motor controller 1250, and prosthesis 1260 (shown as a mechanical model according to Fig. 10C). [00118] The prosthesis measured ankle state, ( ⁇ m , ⁇ m ) is used to produce a torque command from the neuromuscular model, ⁇ ⁇ /. This desired ankle torque is fed through a torque control system to obtain a current command to the prosthesis actuator.
- Figs. 13A-C are plots of prosthesis torque over one complete gait cycle
- Fig. 13A level-ground
- Fig. 13B ramp ascent
- Fig. 13C ramp descent
- Fig. 13A level-ground
- Fig. 13B ramp ascent
- Fig. 13C ramp descent
- Fig. 13C commanded torque mean 1305, 1310, 1315 (thin line) ⁇ standard deviation (dashed lines)
- prosthesis torque as estimated using the measured SEA torque contribution and angle-based estimate of the parallel spring torque contribution 1320, 1325, 1330 (thick line).
- Vertical (dash-dot) lines 1335, 1340, 1345 indicate the end of the stance phase.
- Figs. 14A-C depict an exemplary embodiment of the musculoskeletal model as implemented on the prosthetic microcontroller, including the Hill-type muscle model and spring-damper attachments to the two-link ankle joint model (Fig. 14A), detailed Hill-type muscle model (Fig. 14B), and geometry of the muscle model skeletal attachment (Fig. 14C) including the variable moment-arm implementation and angle coordinate frame for the muscle model.
- Figs. 14A and 14C are mechanical representations of dorsiflexor (spring- damper) 1405, planar flexor (MTC) 1410, foot 1415, shank 1420, and heel 1425.
- the dorsiflexor in Fig. 14A is the dorsiflexor actuator. It represents the
- Kp is the spring constant
- Ky is the damping constant
- ⁇ is the ankle angle
- ⁇ is the ankle angular velocity.
- Ky was experimentally tuned for stance phase to 5 Nm-s/rad to prevent the forefoot from bouncing off the ground at foot-flat.
- the dorsiflexor acts only to provide dorsiflexion torque, so to mimic the unidirectional property of biological muscles.
- the dorsiflexor acts as a position controller, driving the foot to the set-point
- Plantar Flexor Model The virtual plantar flexor in Figs. 14A-C comprises a muscle-tendon complex, (MTC) which represents a combination of human plantar flexor muscles.
- MTC muscle-tendon complex
- the MTC is based on S. K. Au, J. Weber, and H. Herr, "Biomechanical design of a powered ankle-foot prosthesis," Proc. IEEE Int. Conf. On Rehabilitation Robotics, Noordwijk, The Netherlands, pp. 298-303, June 2007, where it is discussed in further detail. It consists of a contractile element (CE) which models muscle fibers and a series element (SE) which models a tendon.
- CE contractile element
- SE series element
- the contractile element consists of three unidirectional components: a Hill-type muscle with a positive force feedback reflex scheme, a high-limit parallel elasticity, and a low-limit, or buffer, parallel elasticity.
- the series element In series with the contractile element is the series element, which is a nonlinear, unidirectional spring representing the Achilles tendon.
- the attachment geometry of the muscle-tendon complex to the ankle joint model is nonlinear, complicating the calculation of torques resulting from the actuator force.
- SE Plantar Flexor Series Elastic Element.
- the series elastic element (SE) operates as a tendon in series with the muscle contractile element as in [H. Geyer, A. Seyfarth, R. Singhhan, "Positive force feedback in bouncing gaits?,” Proc. R Society. Lond. B 270, pp. 2173-2183, 2003]. Taking ⁇ as the tendon strain defined as:
- I SE is the length of the series element and l slaclc is its rest length
- the series element is specified to be a nonlinear spring described by H. Geyer, A. Seyfarth, R. Singhhan, "Positive force feedback in bouncing gaits?,” Proc. R Society. Lond. B 270, pp. 2173-2183, 2003:
- F max is the maximum isometric force that the muscle can exert.
- this quadratic form was used as an approximation of the commonly-modeled piecewise exponential-linear tendon stiffness curve. This approximation was made so to reduce the number of model parameters.
- the contractile element (CE) of the plantar flexor virtual actuator, Fig. 14B is a Hill-type muscle model with a positive force feedback reflex scheme. It includes active muscle fibers to generate force, and two parallel elastic components, as in H. Geyer, H. Herr, "A muscle-reflex model that encodes principles of legged mechanics predicts human walking dynamics and muscle activities," (Submitted for publication).
- the Hill-type muscle fibers exert a unidirectional force. This force is a function of the muscle fiber length, I CE , velocity, vcE, and muscle activation, A.
- the resulting force, F MF is, as in H. Geyer, A. Seyfarth, R. Singhhan, "Positive force feedback in bouncing gaits?,” Proc. R Society. Lond. B 270, pp. 2173-2183, 2003, given by:
- l opt is the contractile element length, I CE , at which the muscle can provide the maximum isometric force, F max .
- v max ⁇ 0 is the maximum contractile velocity of the muscle
- V CE is the fiber contraction velocity
- K is the curvature constant
- N defines the dimensionless muscle force (normalized by F max ) such that
- LPE buffer parallel elasticity
- F CE F MF ( 1 CE , V CE , A ) + F HPE ⁇ F LPE ⁇ ( l l )
- Fig. 15 depicts an exemplary embodiment of a reflex scheme for the virtual plantar flexor muscle, including the relationship among ankle angle, muscle force, and the plantar flexor component of ankle torque.
- this feedback loop includes a stance phase switch for disabling the plantar flexor force development during the swing phase.
- the plantar flexor force, F M ⁇ c is multiplied by a reflex gain Gain RF , delayed by DelayRF and added to an offset stimulation, PRESTIM to obtain the neural stimulation signal.
- the stimulation is constrained to range from 0 to 1, and is low-pass filtered with time constant T to simulate the muscle excitation-contraction coupling.
- the resulting signal is used as activation in equation (4) with an initial value of PreA.
- a suppression gain, Gainsupp following H. Geyer, H.
- p is a scaling factor representing the pennation angle of the muscle fibers
- the fiber contraction velocity, V CE can then be obtained via differentiation. This creates a first order differential equation governed by the dynamics of the neuromuscular model. This equation can be solved for F M ⁇ c given the time history of ⁇ foot and initial condition. However, since integration is computationally more robust than differentiation, an integral form of this implementation was used to solve for F M ⁇ c, as described in H. Geyer, H.
- the plantar flexor model can ultimately be treated as a dynamical system linking a single input, ⁇ foot, to a single output, T p i antar .
- the plantar flexor model is a lumped representation of all of the biological plantar flexor muscles.
- the dorsiflexor represents all biological dorsiflexor muscles.
- joint and torque measurements were taken only at the ankle joint.
- the state of multi-articular muscles, such as the gastrocnemius could not be accurately estimated. Therefore the plantar flexor was based upon the dominant monarticular plantar flexor in humans, the Soleus. Therefore, the majority of the plantar flexor parameters values are those reported in H. Geyer, H.
- Non-amputee Subject Data Collection Kinetic and kinematic walking data were collected at the Gait Laboratory of Spaulding Rehabilitation Hospital, Harvard Medical School, in a study approved by the Spaulding committee on the Use of Humans as Experimental Subjects [H. Herr, M. Popovic, "Angular momentum in human walking," The Journal of Experimental Biology, Vol. 211, pp 487-481, 2008].
- a healthy adult male (81.9kg) was asked to walk at slow walking speed across a 10m walkway in the motion capture laboratory after informed consent was given.
- the motion-capture was performed using a VICON 512 motion- capture system with eight infrared cameras.
- Reflective markers were placed at 33 locations on the subject's body in order to allow the infrared cameras to track said locations during the trials.
- the cameras were operated at 120 Hz and were able to track a given marker to within approximately 1 mm.
- the markers were placed at the following bony landmarks for tracking the lower body: bilateral anterior superior iliac spines, posterior superior iliac spines, lateral femoral condyles, lateral malleoli, forefeet and heels.
- Wands were placed over the tibia and femur, and markers were attached to the wands over the mid- shaft of the tibia and the mid- femur.
- Figs. 16A and 16B depict prosthesis-measured torque and angle trajectories during trials with an amputee subject compared to those of the biological ankle of a weight and height-matched subject with intact limbs. Shown in Figs.
- FIGs. 16A and 16B are ankle torque (Fig. 16A) and ankle angle (Fig. 16B) over a level-ground gait cycle from heel-strike (0% Cycle) to heel-strike of the same foot (100% Cycle).
- Plotted in Figs. 16A and 16B are mean 1610, 1620 (thin line) ⁇ one standard deviation (dashed lines) for the prosthesis measured torque and angle profiles resulting from the neuromuscular-model control, and the ankle biomechanics 1630, 1640 (thick line) for a gait cycle of the weight and height-matched subject with intact limbs at the same walking speed (1 m/sec).
- Vertical lines indicate the average time of the beginning of swing phase 1650, 1660 (thin dash-dot line) for the prosthesis gait cycles and the beginning of the swing phase 1670, 1680 (thick dash-dot line) of the biological ankle.
- the goal of the parameter tuning was to find the parameter set that would enable the neuromuscular model to best match a biological ankle torque trajectory for a particular walking condition, given the corresponding biological ankle angle trajectory as input to the model.
- the cost function for the optimization was defined as the squared error between the biologic and model torque profiles during the stance phase, given the biological ankle angle trajectory, i.e.: where T n is the torque output of the model, and T bw is the biological ankle torque.
- a Genetic Algorithm optimization was chosen to perform the initial search for optimal parameter values, and a direct search was included to pinpoint the optimal parameter set.
- the Genetic- Algorithm tool in Matlab was used to implement both optimization methods.
- the level-ground human walking data at the selected 1.0 m/s walking speed was used to provide the reference behavior for the optimization.
- the allowable range for each of the optimization parameters are shown in Table 7.
- Fig. 17 a comparison of the ankle moment profile from the intact biological ankle to that of the neuromuscular model with the biological ankle angle profile as the input and with optimized parameter values, are biological ankle moment (grey line) 1710, modeled dorsiflexor component (dash-dot line) 1720, modeled plantar flexor muscle component (thin line) 1730, and total neuromuscular model (plantar flexor and dorsiflexor) moment (dashed line) 1740.
- the neuromuscular model ankle moment matches the biological ankle moment almost exactly for most of the gait cycle.
- the prosthesis was placed on the right leg of a healthy, active, 75 kg transtibial amputee. The subject was allowed time to walk on the prosthesis for natural adjustment. The wireless link to the prosthesis was used to record the walking data from these trials. During the level-ground walking trials, the subject was asked to walk across a 10 m long path. The target intended walking speed was set to 1.0 m/s to match that of the intact subject. The subject began walking approximately 5 m from the beginning of the pathway, and stopped walking approximately 3 m past the end of the path. Markers on the ground were used to note the beginning and end of the 10 m path.
- a stopwatch was used to verify the average walking speed for each trial by noting when the subject's center of mass passed over each of the markers. A total of 10 trials were captured. Trials with walking speeds within 5% of the target speeds were used for processing, resulting in 45 gait cycles. The subject was next asked to walk up an 11 -degree, 2 m long incline at a self- selected speed. The subject started on level-ground approximately 2 m from the start of the incline and stopped approximately 1 m past the incline on a platform for 10 ramp-ascent trials. This same path was then navigated in reverse for 12 ramp-descent trials.
- FIGs. 16A and 16B show the level-ground walking torque and angle profiles from the prosthesis along with those of a weight and height-matched subject with intact limbs.
- Figs. 18A-C are plots of measured prosthesis torque-angle trajectories for three different walking conditions: level ground (Fig. 18A), ramp ascent (Fig. 18B), and ramp descent (Fig. 18C). Shown in Figs.
- 18A-C are mean 1810, 1820, 1830 ⁇ one standard deviation. Arrows indicate forward propagation in time. The average prosthesis net work increases with increasing ground slope. This result is consistent with human ankle data from the literature [A. S. Mclntosh, K. T. Beatty, L. N. Dwan, and D. R. Vickers, "Gait dynamics on an inclined walkway,” Journal of Biomechanics, Vol. 39, pp 2491-2502, 2006].
- the measured ankle torque and ankle angle profiles of the prosthesis qualitatively match those of a comparable intact individual for level-ground walking.
- the differences observed are of a low order, and may reasonably be attributed to a number of factors, including atrophy and/or hypertrophy in the clinical subject's leg muscles resulting from amputation, differences in limb lengths, and perhaps the lack of a functional biarticular gastrocnemius muscle.
- the limited range of the prosthetic angle sensor prohibited the prosthesis from reaching the full range of motion of the intact ankle.
- the ability of the neuromuscular model to produce these biomimetic changes in behavior suggests that the model embodies an important characteristic of the human plantar flexor muscles.
- the model has the potential for speed adaptation. In an attempt to move faster, the wearer may push harder on the prosthesis. This additional force could cause the modeled reflex to command higher virtual muscle forces, resulting in greater energy output, and hence higher walking speeds.
Abstract
Description
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JP2011548380A JP2012516780A (en) | 2009-01-30 | 2010-02-01 | A model-based neuromechanical controller for robotic legs |
CN2010800152080A CN102378669A (en) | 2009-01-30 | 2010-02-01 | Model-based neuromechanical controller for a robotic leg |
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WO2013172968A1 (en) * | 2012-05-15 | 2013-11-21 | Vanderbilt University | Stair ascent and descent control for powered lower limb devices |
US8864846B2 (en) | 2005-03-31 | 2014-10-21 | Massachusetts Institute Of Technology | Model-based neuromechanical controller for a robotic leg |
US8870967B2 (en) | 2005-03-31 | 2014-10-28 | Massachusetts Institute Of Technology | Artificial joints using agonist-antagonist actuators |
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US9603724B2 (en) | 2013-08-27 | 2017-03-28 | Carnegie Mellon University, A Pennsylvania Non-Profit Corporation | Robust swing leg controller under large disturbances |
US10561563B2 (en) | 2013-12-16 | 2020-02-18 | Massachusetts Institute Of Technology | Optimal design of a lower limb exoskeleton or orthosis |
TWI736358B (en) * | 2019-07-19 | 2021-08-11 | 日商三菱電機股份有限公司 | Parameter identification device, parameter identification method and computer program |
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WO2010088616A1 (en) | 2010-08-05 |
EP2398425A1 (en) | 2011-12-28 |
EP2391486A4 (en) | 2013-09-04 |
AU2010208020A1 (en) | 2011-09-15 |
JP2012516780A (en) | 2012-07-26 |
KR20110122150A (en) | 2011-11-09 |
AU2010207942A1 (en) | 2011-09-15 |
KR20110120927A (en) | 2011-11-04 |
EP2391486A1 (en) | 2011-12-07 |
CN102378669A (en) | 2012-03-14 |
CN102481194A (en) | 2012-05-30 |
CA2787955A1 (en) | 2010-08-05 |
EP2398425A4 (en) | 2013-09-18 |
JP2012516717A (en) | 2012-07-26 |
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