Patent Application
20230390086
This disclosure generally relates to powered prostheses that provide volitional control of knee joint actuation. In particular, this disclosure relates to powered prostheses for above-knee amputations that provide control over knee joint actuation based at least partly on a determined thigh angle of the user's residual limb, through the use of continuous minimum-jerk planning to re-program desired prosthesis trajectory at multiple time points during the swing phase.
Most available knee prostheses are energetically passive devices with limited ability to reproduce the behavior of the healthy biological knee. In the simplest devices, the biomechanical behavior of the healthy knee joint is approximated by friction elements or hydraulic dampers. More advanced knee prostheses use a microcontroller to change the knee damping withing the gait cycle. These microprocessor-controlled knees allow for variable cadence while improving stance stability and reducing metabolic cost of walking compared to friction and hydraulic knees. Despite these improvements, ambulation is slower, less stable, and less efficient for individuals with above-knee amputation than able-bodied individuals. Moreover, negotiating common environmental barriers such as curbs, stairs, or uneven surfaces requires unnatural, destabilizing compensatory movements such as residual hip circumduction and plantar flexion of the sound ankle (i.e., vaulting) to compensate for the missing prosthesis knee flexion.
In contrast to passive prostheses, powered prostheses can actively regulate joint movements using battery-powered servomotors. To accomplish this goal, powered prostheses typically use controllers that aim to replicate the behavior of the healthy leg across different ambulation activities. One common control method consists of dividing the gait cycle into segments that are characteristic of the nominal gait pattern, such as stance and swing. In swing, the trajectory of the powered prosthetic joint is often determined by joint impedance parameters such as stiffness, damping, and equilibrium point, which are tuned by the experimenter to imitate the nominal knee joint trajectory. To accomplish this goal, swing must be divided into two segments with different impedance parameters. Furthermore, tuning of impedance parameters is necessary to change the swing timing as necessary to walk at different speeds. Despite their robustness, impedance-based controllers have limited adaptability, making it hard to adapt the swing trajectory to the user's needs.
Position-based controllers have been more recently proposed to simplify the tuning procedure and provide more flexibility over the powered prosthesis behavior. Rather than using a set of impedance parameters, position-based controllers define the whole swing trajectory either as a continuous function of time or residual-limb movements. Using this approach, the desired position trajectory can be conveniently extracted from the analysis of able-bodied biomechanics, which avoids the need for manual tuning. The desired trajectory can then be stored in look-up tables, encoded using parametric functions, or obtained online using minimum jerk programming. This control approach has been used successfully for different locomotion tasks such as variable-speed walking, variable inclines, and stair climbing. However, this control approach lacks the ability to adapt the prosthesis trajectory outside of the nominal gait pattern. Thus, available position-based controllers are not suitable to traverse environmental barriers such as curbs and uneven surfaces.
Classification-based controllers have been proposed to achieve ambulation over different terrains. The basic idea is to use separate controllers for different environmental conditions, which must be detected by an online classifier. The detection of environmental obstacles or constraints can rely on a combination of mechanical sensors, electromyography, sonomyography, lasers, or computer vision. These classification-based controllers have been originally developed for detecting ramps and stairs, and, more recently, have been used for obstacle detection. However, open challenges remain in obtaining an accuracy that is conducive to use in the community as well as in the training of the classification algorithms. Therefore, the clinical viability of classification-based controllers is uncertain.
Accordingly, improved prothesis technologies are necessary to address the needs of individuals with an above-knee amputation.
The present disclosure describes prostheses devices configured to adapt the prosthesis trajectory (e.g., knee and/or ankle joint angle over time) continuously during swing phase to enable enhanced volitional control of the prosthesis and to enable enhanced ability to traverse environmental barriers. Prostheses described herein represent an improvement over conventional powered prostheses, many of which operate by planning the desired prosthesis trajectory at the beginning of swing and keeping it constant throughout the swing duration. Prostheses described herein also represent an improvement over conventional powered prostheses that operate using a classification-based approach. That is, prostheses described herein modulate the swing trajectory according to movements of the user's residual limb without requiring an explicit classification of the environment.
The prostheses described herein beneficially enable users with above-knee amputations to volitionally control foot clearance, enabling such users to better navigate environmental barriers such as by enabling more controlled crossing over obstacles of different sizes.
In one embodiment, a powered prosthesis configured to provide volitional control of knee flexion during swing comprises a knee joint; one or more sensors for determining a thigh angle of a residual limb to which the prosthesis is attached; and a controller communicatively coupled to the knee joint and the one or more sensors. The controller includes one or more processors and one or more hardware storage devices having stored thereon computer-executable instructions. The controller is configured to determine that the swing phase has initiated; receive the thigh angle from the one or more sensors; and based on the time elapsed since initiation of the swing phase, and based on the received thigh angle, determine a desired maximum knee flexion angle. The controller then updates, at multiple time points during swing, the desired maximum knee flexion angle using subsequent measurements of thigh angle and time elapsed since initiation of the swing phase.
The controller can be further configured to determine a first swing state and a second swing state within the swing phase. The first swing state functions to control knee flexion and the second swing state functions to slow and end knee flexion, if necessary, and control knee extension. The controller transitions from the first swing state to the second swing state upon determining that the thigh angle has passed a thigh angle threshold or upon determining that the time elapsed since initiation of the swing phase has exceeded a time threshold. The thigh angle threshold may be variable. For example, the thigh angle threshold may vary as a function of the desired maximum knee flexion angle as determined and updated over time by the controller during swing.
The controller can be configured to determine the desired maximum knee flexion angle using the integral of the thigh angle over a time period from the initiation of the swing phase to the present duration of the swing phase. The controller can be configured to determine that the swing phase has initiated upon determining a ground reaction force (GRF) that is lower than a stance-to-swing threshold, the stance-to-swing threshold being proportional to a body weight of the user. The controller can also be configured to determine a transition from the swing phase to a first stance state upon determining a GRF that is higher than a swing-to-stance threshold, the swing-to-stance threshold being proportional to a body weight of the user. The controller can also be configured to determine a transition between a first stance state (i.e., a default standing state) and a second stance state (i.e., an energy-injection state) by determining that the ankle joint exceeds a dorsiflexion threshold and has positive plantarflexion velocity.
The controller can be configured to determine a desired knee joint position, velocity, and acceleration using a minimum jerk engine. The minimum jerk engine receives as inputs the desired maximum knee flexion angle, and the time remaining until desired duration of a first swing state, and outputs updated desired knee joint position, velocity, and acceleration to enable determination and updating of desired knee torque for the knee joint.
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an indication of the scope of the claimed subject matter.
Various objects, features, characteristics, and advantages of the invention will become apparent and more readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings and the appended claims, all of which form a part of this specification. In the Drawings, like reference numerals may be utilized to designate corresponding or similar parts in the various Figures, and the various elements depicted are not necessarily drawn to scale, wherein:
Crossing over obstacles with conventional passive prostheses requires individuals with above-knee amputations to circumduct the ipsilateral hip (i.e., prosthesis side) and plantarflex the contralateral ankle (i.e., sound side vaulting) to compensate for the lack of knee flexion. Powered prostheses have the potential to address this issue by directly controlling the knee flexion during swing. However, available powered prothesis controllers cannot automatically adapt the swing trajectory as necessary to traverse environmental barriers such as crossing over obstacles.
Classification-based controllers aim to address this issue by switching between different pre-planned swing trajectories that are appropriate to deal with different ambulation tasks and environmental barriers. However, this classification approach requires the prosthesis controller to detect the desired ambulation task or environmental barrier online before it is negotiated by the prosthesis user. This classification is typically performed using machine learning, which requires extensive training data sets. Furthermore, close to 100% online accuracy is necessary for classification-based controllers to work properly, as both a false positive and false negative may result in dangerous behavior of the powered prosthesis, potentially causing the prosthesis user to fall.
Conventional approaches have not provided the prosthesis user with volitional control of maximum knee flexion or foot clearance. Here, rather than classifying the environmental barrier and switching between different, pre-planned swing trajectories, the inventive prostheses continuously modulate the trajectory of the powered prosthesis based on the movements of the user's residual limb so that environmental barriers can be negotiated. This approach beneficially enables individuals with an above-knee amputation to ambulate at different speeds while seamlessly crossing over obstacles.
Biomechanics studies on able-bodied subjects show that crossing over an obstacle requires increasing both hip and knee flexion to shorten the limb and create clearance between the foot and the obstacle. Accordingly, continuous adaptation of the prosthesis knee flexion in swing can beneficially change foot clearance as required to cross over obstacles. The modulation of foot clearance using the controller described herein is obtained through two factors also observed in able-bodied individuals. The first factor is the increase of maximum knee flexion. The second factor is the time shift in the movements of the user's residual limb and the prosthetic knee, such as for the same thigh angle, the prosthesis knee flexion angle increases when crossing over obstacles.
Systems, methods, and techniques related to adaptive volitional control of powered prostheses, in accordance with the present disclosure, may be implemented utilizing various types of knee and ankle prostheses.
The example powered knee and ankle prosthesis 100 of
The example powered knee and ankle prosthesis 100 of
The example powered knee and ankle prosthesis 100 of
The AVT 112 of the example powered knee and ankle prosthesis 100 of
The primary actuator of the example powered knee and ankle prosthesis 100 represented in
Covers 118 (e.g., 3D printed covers) may be utilized to house the control unit and battery 102. The control unit and battery 102 may comprise a Li-Ion battery (e.g., 2500 mAh, 6S) and/or an onboard system-on-module (SOM) (e.g., myRIO 1900, National Instruments, 100 g without covers). The SOM can run all custom control algorithms in real time, interfacing with the sensors and servo drivers for the AVT 112 and the primary motor (e.g., Elmo, Gold Twitter G-TWI 30/60SE, 35 g). The SOM can be connected through Wi-Fi to a host computer, smartphone, and/or other device for data monitoring and/or controller tuning.
Experimental results (discussed in more detail hereinafter) were obtained by implementing an adaptive volitional controller with a powered knee and ankle prosthesis 100 that includes the features/components discussed with reference to
When the user is standing still, the prosthesis controller is in Stance 1. If the ankle joint exceeds a dorsiflexion threshold (θankle<θankleths) and has positive plantarflexion velocity ({dot over (θ)}ankle>0), the system transitions to Stance 2, which is an energy-injection state. From Stance 2, the prosthesis transitions to Swing 1 when a force sensor integrated with the prosthesis (e.g., an instrumented pyramid adapter) detects a GRF lower than some proportion of the of the user's body weight (e.g., 5% of the user's body weight).
In Swing 1, the knee joint flexes to increase foot clearance. In this state, the knee joint trajectory is modulated by the controller to continuously change the desired maximum knee flexion. From Swing 1, the system transitions to Swing 2 when the orientation of the user's residual limb crosses a position threshold (θthigh<θthighths) or if duration of Swing 1 exceeds a time threshold (tsw1>Tsw1ths). In Swing 2, a knee extension trajectory is programmed enabling timely placement of the prosthetic foot in preparation for the subsequent heel strike. Finally, the prosthesis transitions from Swing 2 to Stance 1 when the force sensor detects the GRF higher than some proportion of the user's body weight (e.g., 5% of the user's body weight).
As shown, the desired maximum knee flexion angle (θfinaldes) in Swing 1 is determined by the integral of the residual limb orientation with respect to gravity (θthigh), computed from the start to the end of Swing 1 (or to the time duration of Swing 1 up to the present time of measurement), according to Equation (1):
θfinaldes(t)=K1+K2∫0T
In the example presented in
According to Equation (1), the desired maximum knee flexion angle (θfinaldes) increases when the residual limb is positioned farther back (i.e., when θthigh is larger), or when it is moved forward slowly during Swing 1 (right after toe-off). Thus, the prosthesis knee swing trajectory can be modulated by the user through movement of the residual limb, enabling variable foot clearance.
Given a desired maximum knee flexion angle (θfinaldes), the swing trajectory is continuously optimized using minimum jerk. As shown, the minimum-jerk planner (also referred to herein as minimum-jerk engine) takes as input the desired maximum knee flexion angle (θfinaldes) and the desired movement duration (Tfinaldes), which is computed in Swing 1 by subtracting the current swing time (tsw1(t)) from the desired Swing 1 duration (Tsw1), as shown by Equation (2):
T
final
des(t)=Tsw1−tsw1(t)
Based on these inputs and on the previously determined desired position, velocity, and acceleration, the minimum jerk planner updates the desired swing trajectory by computing the desired angle, velocity, and acceleration of the knee joint. The desired angle, velocity, and acceleration are then passed to a mixed feedforward/feedback regulator that determines the desired torque at the knee joint level. A new trajectory can branch off from the swing trajectory originally programmed at toe-off if the desired final position or the desired swing duration change. Thus, with continuous minimum-jerk planning, the prosthesis can smoothly change the swing trajectory while it is being performed regardless of the current angle, velocity, and acceleration of the prosthesis joint.
Although the desired maximum knee flexion (θfinaldes) is computed through the integral of the residual limb orientation (θthigh), the actual peak of knee flexion depends on the position of the knee at the transition between Swing 1 and Swing 2. The finite-state machine transitions from Swing 1 to Swing 2 when the thigh angle (θthigh) exceeds a threshold (θthighths). However, this threshold is not fixed, but rather varies as a function of the desired peak knee flexion (θfinaldes) as defined by Equation (3):
θthighths(t)=K4−K5θfinaldes(t)
Where, by way of non-limiting example, K4 equals 17.5 and K5 equals 0.5. These constants may take other values as determined through empirical testing and/or individualized customization of a prosthesis.
Based on Equation (3), the thigh threshold at the transition between Swing 1 and Swing 2 increases proportionally to the desired peak knee flexion (θfinaldes). Thus, the transition between Swing 1 and Swing 2 can happen at different points within Swing. The desired duration of Swing 1 (Tsw1) can be set as a constant (e.g., at 0.4 s) that can be determined empirically, for example.
In Swing 2, the prosthesis uses a minimum jerk controller to ensure timely placement of the foot in preparation for the subsequent heel strike. As shown by the simulation results of
In stance, the controller enforces physiological torque-angle curves extracted from able-bodied individuals walking at different speeds. Thus, the knee and ankle torque profiles are adapted online based on the respective joint positions and an overall estimate of the current walking speed. Different from impedance-based controllers, this stance controller does not necessarily require user-specific or speed-specific tuning, although the body weight of the user is preferably inserted in the controller. Other stance controllers may alternatively be utilized as any initial angle, speed, and acceleration can be handled by the minimum-jerk swing controller.
A longer stride and a larger knee flexion are shown to produce a higher clearance in able-bodied individuals. As a result, the controller continuously modulates the maximum knee flexion in swing depending on how far back the residual limb (i.e., thigh angle) is positioned and how fast the user moves it forward during the flexion part of swing. Moreover, it was designed to adjusts Swing 1 duration, as able-bodied individuals typically wait to start extension at a higher thigh angle whenever a higher clearance is desired. This heuristic adaptation of maximum knee flexion and Swing 1 duration can be combined with minimum jerk programming to obtain a smooth behavior of the leg that qualitatively matches the behavior of the healthy leg.
Previous prostheses using a minimum-jerk approach program the trajectory at toe-off and keep it constant through the whole swing duration. Thus, the swing trajectory cannot be modified as necessary to cross over obstacles. In contrast, the present controller updates the swing trajectory at multiple instances within the swing phase.
The behavior of the controller is demonstrated by the simulations in
In
Varying the transition points between Swing 1 and Swing 2 (circle markers in
However, if the transition between Swing 1 and Swing 2 is due to the timeout conditions (circle marker in
The following discussion now refers to a number of methods and method acts that may be performed in accordance with the present disclosure. Although the method acts are discussed in a certain order and illustrated in a flow chart as occurring in a particular order, no particular ordering is required unless specifically stated, or required because an act is dependent on another act being completed prior to the act being performed. One will appreciate that certain embodiments of the present disclosure may omit one or more of the acts described herein.
Act 702 of flow diagram 700 includes determining that a swing phase has initiated. In some instances, sensor data from a force sensor for measuring ground reaction force (GRF) is used to determine that the swing phase has initiated upon detecting a GRF that is lower than a stance-to-swing threshold. The stance-to-swing threshold may be proportional to a body weight of a user.
Act 704 of flow diagram 700 includes obtaining a thigh angle based on the sensor data obtained by one or more sensors.
Act 706 of flow diagram 700 includes, based on a time elapsed since initiation of the swing phase, and based on the thigh angle, determining a desired maximum knee flexion angle. In some instances, the desired maximum knee flexion angle is determined using an integral of the thigh angle over a time period from the initiation of the swing phase to a present duration of the swing phase. For example, the desired maximum knee flexion angle may be determined according to:
θfinaldes(t)=K1+K2∫0T
where (t) is the time elapsed since initiation of the swing phase, θfinaldes(t) is the desired maximum knee flexion angle, θthigh(t) is the thigh angle at time (t), Tsw1 is a desired duration of a first swing state, and K1 , K2, and K3 are optional constants. In some implementations, K1 is within a range of about 40 to about 70, or within a range of about to about 60, or about 55. In some implementations, K2 is within a range of about 1.1 to about 3, or within a range of about 1.5 to about 2.5, or about 2. In some implementations, K3 is within a range of about 5 to about 35, or within a range of about 10 to about 30, or within a range of about 15 to about 25. In some implementations, Tsw1 is within a range of about 0.25 s to about 0.65 s, or within a range of about 0.35 s to about 0.45 s, or about 0.4 s.
Act 708 of flow diagram 700 includes determining a desired knee joint position, velocity, and acceleration using a minimum jerk engine. The minimum-jerk engine may receive as inputs the desired maximum knee flexion angle, and a desired movement duration. The minimum-jerk engine may output updated desired knee joint position, velocity, and acceleration.
Act 710 of flow diagram 700 includes, during the swing phase, continuously updating the desired maximum knee flexion angle using subsequent measurements of thigh angle and time elapsed since initiation of the swing phase. The minimum jerk engine referred to above in act 708 may accordingly update the desired knee joint position, velocity, and acceleration based on the updated desired maximum knee flexion angle. Therefore, knee flexion of the knee joint during the swing phase may be controlled without explicit classification of an environment.
Act 712 of flow diagram 700 includes outputting a signal configured to cause actuation of the knee joint based on the desired maximum knee flexion angle. For example, the signal may be configured to cause actuation of the knee joint in accordance with the desired knee joint position, velocity, and acceleration (e.g., determined utilizing the minimum-jerk engine).
Act 714 of flow diagram 700 includes determining a first swing state and a second swing state within the swing phase. The first swing state may be associated with control of knee flexion, and the second swing state may be associated with control of knee extension and/or, if necessary, slowing and ending knee flexion. In some instances, the minimum-jerk engine is used to control knee joint movement during the second swing state.
Act 716 of flow diagram 700 includes transitioning from the first swing state to the second swing state upon determining that the thigh angle has passed a thigh angle threshold or upon determining that the time elapsed since initiation of the swing phase has exceeded a time threshold. In some implementations, the thigh angle threshold is variable, such as by varying as a function of the desired maximum knee flexion angle. For example, the thigh angle threshold may be determined according to:
θthighths(t)=K4−K5θfinaldes(t)
where θfinalths(t) is the thigh angle threshold, θfinaldes(t) is the desired maximum knee flexion angle, K4 is a constant, and K5 is an optional constant. In some implementations, K4 is within a range of about 10 to about 25, or about 17.5. In some implementations, K5 is within a range of about 0.25 to about 0.75, or about 0.5.
Act 718 of flow diagram 700 includes determining a transition from the swing phase to a first stance state upon determining a GRF that is higher than a swing-to-stance threshold. In some instances, the swing-to-stance threshold is proportional to a body weight of a user. For example, the swing-to-stance threshold may be within a range of about 3% to about 10% of the body weight of the user, or about 5% of the body weight of the user.
Act 720 of flow diagram 700 includes determining a transition between a first stance state and a second stance state by determining that an ankle joint exceeds a dorsiflexion threshold and has positive plantarflexion velocity. The second stance state may comprise an energy-injection state.
The functionality of the volitional walking controller was measured by observing its performance during a series of tests. In the first test, subjects walked back and forth at their self-selected speed on a 4-m walkway including starting and stopping, while an obstacle was placed in the middle of the walkway. Three different obstacles sizes were used in different trials and are denoted as small (10 cm×80 cm×6 cm), medium (15 cm×80 cm×10 cm), and large (30 cm×80 cm×20 cm). A representative test with one subject with an above-knee amputation crossing over the medium-size obstacle is shown in
As can be seen, the subject performs three consecutive strides with the obstacle being crossed in the second stride with the sound side first. The gait pattern changes considerably when the subject crosses over the obstacle. Specifically, the range of motion of the hip joint increases from 34° and 39° for the first and last stride, respectively, to 51° for the obstacle crossing stride. As a result, a 46% longer stride is taken when crossing the obstacle (x axis,
By analyzing the gait kinematics during the level-ground test with and without obstacles, assess the ability of a subject to voluntarily change foot clearance can be assessed. The analysis of the powered knee kinematics for a representative subject shows that the stride duration is longer in the presence of an obstacle and that it increases with the obstacle size. Similarly, the maximum knee flexion increases with the obstacle size. Moreover, the inversion of the movement between knee flexion and extension (see
The phase analysis (
The performance of the controller under continuous walking is demonstrated by the subjects walking on a treadmill at two different speeds (i.e., 0.6 m/s, 0.8 m/s) while an experimenter manually drops 6-cm tall obstacles on the belt in the path of the powered prosthesis. The analysis of the knee kinematics (
The phase analysis (i.e., knee angle vs. the thigh angle) shows that timing of the knee and thigh movements is altered when an obstacle is crossed (
As shown by
The difference in maximum knee flexion is larger for the treadmill tests, with it reaching 20.8° and 25.7° for the 0.6 m/s and 0.8 m/s speed respectively. By focusing on the level-ground tests with obstacles (B-D,
The timing of the knee flexion is more similar during the treadmill tests, where subjects with an above-knee amputation reach their maximum flexion at an average of 75% of stride and able-bodied subjects reach their maximum flexion at an average of 77% of stride. Moreover, in able-bodied individuals, heel strike happens as soon as the knee is fully extended, whereas subjects with an above-knee amputation tend to delay heel strike. During level-ground walking with no obstacle (A,
The heel strike delay is less pronounced during the treadmill test (E-F,
As shown by
Embodiments of the present disclosure may include, but are not necessarily limited to, features recited in the following clauses:
θfinaldes(t)=K1+K2∫0T
wherein (t) is the time elapsed since initiation of the swing phase, θfinaldes(t) is the desired maximum knee flexion angle, θthigh(t) is the thigh angle at time (t), Tsw1 is a desired duration of a first swing state, and K1 , K2, and K3 are optional constants.
θthighths(t)=K4−K5θfinaldes(t)
wherein θthighths(t) is the thigh threshold, θfinaldes(t) is the desired maximum knee flexion angle, K4 is a constant, and K5 is an optional constant.
While certain embodiments of the present disclosure have been described in detail, with reference to specific configurations, parameters, components, elements, etcetera, the descriptions are illustrative and are not to be construed as limiting the scope of the claimed invention.
Furthermore, it should be understood that for any given element of component of a described embodiment, any of the possible alternatives listed for that element or component may generally be used individually or in combination with one another, unless implicitly or explicitly stated otherwise.
In addition, unless otherwise indicated, numbers expressing quantities, constituents, distances, or other measurements used in the specification and claims are to be understood as optionally being modified by the term “about” or its synonyms. When the terms “about,” “approximately,” “substantially,” or the like are used in conjunction with a stated amount, value, or condition, it may be taken to mean an amount, value or condition that deviates by less than 20%, less than 10%, less than 5%, or less than 1% of the stated amount, value, or condition. At the very least, and not as an attempt to limit the application of the doctrine of equivalents to the scope of the claims, each numerical parameter should be construed in light of the number of reported significant digits and by applying ordinary rounding techniques.
Any headings and subheadings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims.
It will also be noted that, as used in this specification and the appended claims, the singular forms “a,” “an” and “the” do not exclude plural referents unless the context clearly dictates otherwise. Thus, for example, an embodiment referencing a singular referent (e.g., “widget”) may also include two or more such referents.
It will also be appreciated that embodiments described herein may include properties, features (e.g., components, members, elements, parts, and/or portions) described in other embodiments described herein. Accordingly, the various features of a given embodiment can be combined with and/or incorporated into other embodiments of the present disclosure. Thus, disclosure of certain features relative to a specific embodiment of the present disclosure should not be construed as limiting application or inclusion of said features to the specific embodiment. Rather, it will be appreciated that other embodiments can also include such features.
This application claims priority to and the benefit of U.S. Provisional Patent Application Ser. No. 63/104,022, filed Oct. 22, 2020 and titled “Volitional Walking Controller”, the entirety of which is incorporated herein by this reference.
This invention was made with government support under grant nos. HD098154 awarded by the National Institutes of Health and 1925371 awarded by the National Science Foundation. The government has certain rights in this invention.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/US2021/056093 | 10/21/2021 | WO |
| Number | Date | Country | |
|---|---|---|---|
| 63104022 | Oct 2020 | US |
