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After above-knee amputation, the missing biological knee and ankle are commonly replaced with a passive prosthesis, which cannot provide net-positive energy to assist the user. During activities such as sit-to-stand, above-knee amputees must compensate for this lack of power using their upper body, intact limb, and residual limb, resulting in slower, less symmetric, and higher effort movements. Previous studies have shown that powered prostheses can improve symmetry and speed by providing positive assistive power. However, we still lack a systematic investigation of the effect of powered prosthesis assistance. Without this knowledge, researchers and clinicians have no framework for tuning powered prostheses to optimally assist users. Here we show that varying the assistive knee torque significantly affected weight-bearing symmetry, effort, and speed during the stand-up movement in eight above-knee amputees. Specifically, we observed improvements in the index of asymmetry of the vertical ground reaction force at the point approximating maximum vertical center of mass acceleration, the integral of the intact vastus medialis activation measured using electromyography, and the stand-up duration compared to the passive prosthesis. We saw significant improvements in all three metrics when subjects used the powered prosthesis compared to the passive prosthesis. We saw improvements in all three metrics with increasing assistive torque levels commanded by the powered prosthesis. We also observed increased weight-bearing asymmetry at the end of movement, and increased kinematic asymmetry with increasing assistance from the powered prosthesis. These results show that powered prostheses can improve functional mobility, potentially increasing quality of life for millions of people living with above-knee amputations. [ABSTRACT FROM AUTHOR]

Powered prostheses can enable individuals with above-knee amputations to ascend stairs step-over-step. To accomplish this task, available stair ascent controllers impose a predefined joint impedance behavior or follow a preprogramed position trajectory. These control approaches have proved successful in the laboratory. However, they are not robust to changes in stair height or cadence, which is essential for real-world ambulation. Here, we present an adaptive stair ascent controller that enables individuals with above-knee amputations to climb stairs of varying stair heights at their preferred cadence and with their preferred gait patterns. We found that modulating the prosthesis knee and ankle position as a function of the user's thigh in swing provides toe clearance for varying stair heights. In stance, modulating the torque–angle relationship as a function of the prosthesis knee position at foot contact provides sufficient torque assistance for climbing stairs of different heights. Furthermore, the proposed controller enables individuals to climb stairs at their preferred cadence and gait patterns, such as step-by-step, step-over-step, and two-step. The proposed adaptive stair controller may improve the robustness of powered prostheses to environmental and human variance, enabling powered prostheses to more easily move from the lab to the real world. [ABSTRACT FROM AUTHOR]

Advances in powered assistive device technology, including the ability to provide net mechanical power to multiple joints within a single device, have the potential to dramatically improve the mobility and restore independence to their users. However, these devices rely on the ability of their users to continuously control multiple powered lower-limb joints simultaneously. Success of such approaches rely on robust sensing of user intent and accurate mapping to device control parameters. Here, we compare two non-invasive sensing modalities: surface electromyography and sonomyography, (i.e., ultrasound imaging of skeletal muscle), as inputs to Gaussian process regression models trained to estimate hip, knee and ankle joint moments during varying forms of ambulation. Experiments were performed with ten non-disabled individuals instrumented with surface electromyography and sonomyography sensors while completing trials of level, incline (10°) and decline (10°) walking. Results suggest sonomyography of muscles on the anterior and posterior thigh can be used to estimate hip, knee and ankle joint moments more accurately than surface electromyography. Furthermore, these results can be achieved by training Gaussian process regression models in a task-independent manner; i.e., incorporating features of level and ramp walking within the same predictive framework. These findings support the integration of sonomyographic and electromyographic sensing within powered assistive devices to continuously control joint torque. [ABSTRACT FROM AUTHOR]

Misalignments between powered exoskeleton joints and the user’s anatomical joints are inevitable due to difficulty locating the anatomical joint axis, non-constant location of the anatomical joint axis, and soft-tissue deformations. Self-aligning mechanisms have been proposed to prevent spurious forces and torques on the user’s limb due to misalignments. Several exoskeletons have been developed with self-aligning mechanisms based on theoretical models. However, there is no experimental evidence demonstrating the efficacy of self-aligning mechanisms in lower-limb exoskeletons. Here we show that a lightweight and compact self-aligning mechanism improves the user’s comfort and performance while using a powered knee exoskeleton. Experiments were conducted with 14 able-bodied subjects with the self-aligning mechanism locked and unlocked. Our results demonstrate up to 15.3% increased comfort and 38% improved performance when the self-aligning mechanism was unlocked. Not surprisingly, the spurious forces and torques were reduced by up to 97% when the self-aligning mechanism was unlocked. This study demonstrates the efficacy of self-aligning mechanisms in improving comfort and performance for sit-to-stand and position tracking tasks with a powered knee exoskeleton. [ABSTRACT FROM AUTHOR]

Robotic ankle-foot prostheses aim to improve the mobility of individuals with belowknee amputations by closely imitating the biomechanical function of the missing biological limb. To accomplish this goal, they must provide biomechanically accurate torque during ambulation. In addition, they must satisfy further requirements such as build height, range of motion (ROM), and weight. These requirements are critical for determining the potential number of users, range of activities that can be performed, and clinical outcomes. Previous studies have proposed addressing this challenge through the use of advanced actuation systems with series and parallel elastic actuators, clutchable leverages, and pneumatic artificial muscles. These ad vanced actuation systems have shown improved mechanical and electrical efficiency compared to conventional servo motors, making powered ankle prostheses possible. However, the improved efficiency comes at the expense of a tall build height, reduced ROM, and significant increase in weight, thus limiting the clinical viability of currently available powered prostheses. [ABSTRACT FROM AUTHOR]

Novel advanced prostheses aim to improve the ambulation ability of lower-limb amputees by adapting the prosthesis mechanical behavior online during ambulation. Accurate force/torque sensing is necessary to measure the physical interaction between the user, the prosthesis, and the environment. Most available solutions consist of retrofitting an off-the-shelf load cell, which leads to suboptimal designs regarding weight and size, ultimately reducing the prosthesis usability. To address this limitation, we propose to instrument an existing prosthesis component, namely, a pyramid adapter, with force/torque sensing and an inertial measurement unit. Magnetic sensing of large structural deformations is used to improve system reliability and reduce costs. Testing shows that the proposed sensor prototype can sense up to 120 Nm and 2500 N of torque and force and has 2.1% and 8.3% nonlinearity, respectively, during walking. The total weight is 150 g—only 66 g more than a standard pyramid adapter without force/torque instrumentation. Amputee testing with robotic leg prosthesis is conducted to validate the instrumented pyramid in a case scenario. [ABSTRACT FROM AUTHOR]

Robotic ankle prostheses can imitate the biomechanical function of intact legs at the cost of a larger weight and size compared to conventional passive prostheses. Unfortunately, increased weight and size negatively affect comfort and socket stability, ultimately limiting their clinical viability. Alternatively, a nonbackdrivable transmission system can be used to actively regulate the ankle position during nonweight bearing activities only. This semiactive design can be made smaller and lighter as a result of the lower actuation power requirements. However, the transmission system must withstand high loads during stance and standing. Thus, available semiactive prostheses are still significantly heavier and have a larger build height than passive ankle prostheses. In this paper, we present the design, development, and validation of a semiactive ankle prosthesis with a nonbackdrivable cam-follower mechanism designed to lower the load on moving components and align with the foot longitudinally as necessary to reduce the prosthesis weight and size. The proposed ankle mechanism is ∼50% shorter, has ∼40% wider range of motion (ROM), and is estimated to be ∼27% lighter than available semiactive prostheses. Experiments with a transtibial subject show that the semiactive prosthesis can increase foot clearance up to 142% and reduce the load on the residual limb as low as 32% compared to passive prostheses. [ABSTRACT FROM AUTHOR]

Recent advances in motor and gear designs have accelerated the development of multi-degree of freedom prosthetic limbs controlled by novel electromyographic signal processing techniques. Most of these new devices have focused on improved performance at the expense of other critical factors for clinical use, such as weight and bulk, which significantly affect cosmesis and comfort. This paper presents the mechatronic design of an anthropomorphic transhumeral prosthetic arm—the Rehabilitation Institute of Chicago (RIC) arm—that is small enough for a 25th percentile female and weighs only 1518 g. Specifically, we describe the design of the RIC arm, including the integration of custom external rotor motors, cycloid transmissions, nonbackdrivable clutches, and custom pattern recognition control. Mechanics and control performance of the RIC arm were evaluated within the laboratory, and clinical viability was preliminary evaluated during a take-home field trial by an individual with a transhumeral amputation. [ABSTRACT FROM PUBLISHER]

Powered lower limb prostheses have potential to improve the quality of life of individuals with amputations by enabling all daily activities. However, seamless ambulation mode recognition is necessary to achieve this goal and is not yet a clinical reality. Current intent recognition systems use mechanical and EMG sensors to estimate prosthesis and user status. We propose to complement these systems by integrating information about the environment obtained through the depth sensing. This paper presents the design, characterization, and the early validation of a novel stair segmentation system based on Microsoft Kinect. Static and dynamic tests were performed. A first experiment showed how the resolution of the depth camera affects the speed and the accuracy of segmentation. A second test proved the robustness of the algorithm to different staircases. Finally, we performed an online walking test with the stair segmentation and related measures recorded online at >5 frames/s. Experimental results show that the proposed algorithm allows for an accurate estimate of distance, angle of intersection, number of steps, stair height, and stair depth for a set of stairs in the environment. The online test produced an estimate of whether the individual was approaching stairs in real time with approximately 98.8% accuracy. [ABSTRACT FROM AUTHOR]

Recent powered (or robotic) prosthetic legs independently control different joints and time periods of the gait cycle, resulting in control parameters and switching rules that can be difficult to tune by clinicians. This challenge might be addressed by a unifying control model used by recent bipedal robots, in which virtual constraints define joint patterns as functions of a monotonic variable that continuously represents the gait cycle phase. In the first application of virtual constraints to amputee locomotion, this paper derives exact and approximate control laws for a partial feedback linearization to enforce virtual constraints on a prosthetic leg. We then encode a human-inspired invariance property called effective shape into virtual constraints for the stance period. After simulating the robustness of the partial feedback linearization to clinically meaningful conditions, we experimentally implement this control strategy on a powered transfemoral leg. We report the results of three amputee subjects walking overground and at variable cadences on a treadmill, demonstrating the clinical viability of this novel control approach. [ABSTRACT FROM PUBLISHER]

By 2050, an estimated 1.5 million people in the United States will be living with a major lower-limb amputation [1], a condition that causes severe disability, particularly for persons with transfemoral (above-knee) amputations. These individuals expend up to twice the metabolic effort to walk at half the speed [2] of able-bodied persons, and they experience a higher risk of falls and secondary pathological conditions, such as osteoarthritis, back pain, and depression [3]. [ABSTRACT FROM AUTHOR]

In this paper, we study the human locomotor adaptation to the action of a powered exoskeleton providing assistive torque at the user's hip during walking. To this end, we propose a controller that provides the user's hip with a fraction of the nominal torque profile, adapted to the specific gait features of the user from Winter's reference data refid="ref34"/. The assistive controller has been implemented on the ALEX II exoskeleton and tested on ten healthy subjects. Experimental results show that when assisted by the exoskeleton, users can reduce the muscle effort compared to free walking. Despite providing assistance only to the hip joint, both hip and ankle muscles significantly reduced their activation, indicating a clear tradeoff between hip and ankle strategy to propel walking. [ABSTRACT FROM AUTHOR]

Estimation of the temporal derivatives of a noisy position signal is a ubiquitous problem in industrial and robotics engineering. Here, we propose a new approach to get velocity and acceleration estimates of cyclical/periodic signals near to steady-state regime, by using adaptive oscillators. Our method combines the advantages of introducing no delay, and filtering out the high-frequency noise. We expect this method to be useful in control applications requiring undelayed but smooth estimates of velocity and acceleration (e.g., velocity control and inverse dynamics) of quasi-periodic tasks (e.g., active vibration compensation, robot locomotion, and lower-limb movement assistance). [ABSTRACT FROM AUTHOR]

This paper presents the design and experimental testing of the robotic elbow exoskeleton NEUROBOTICS Elbow Exoskeleton (NEUROExos). The design of NEUROExos focused on three solutions that enable its use for poststroke physical rehabilitation. First, double-shelled links allow an ergonomic physical human–robot interface and, consequently, a comfortable interaction. Second, a four-degree-of-freedom passive mechanism, embedded in the link, allows the user's elbow and robot axes to be constantly aligned during movement. The robot axis can passively rotate on the frontal and horizontal planes 30° and 40°, respectively, and translate on the horizontal plane 30 mm. Finally, a variable impedance antagonistic actuation system allows NEUROExos to be controlled with two alternative strategies: independent control of the joint position and stiffness, for robot-in-charge rehabilitation mode, and near-zero impedance torque control, for patient-in-charge rehabilitation mode. In robot-in-charge mode, the passive joint stiffness can be changed in the range of 24–56 N·m/rad. In patient-in-charge mode, NEUROExos output impedance ranges from 1 N·m/rad, for 0.3 Hz motion, to 10 N·m/rad, for 3.2 Hz motion. [ABSTRACT FROM AUTHOR]

The field of wearable robotics is gaining momentum thanks to its potential application in rehabilitation engineering, assistive robotics, and power augmentation. These devices are designed to be used in direct contact with the user to aid with movement or increase the power of specific skeletal joints. The design of the so-called physical human–robot interface is critical, since it determines not only the efficacy of the robot but the kinematic compatibility of the device with the human skeleton and the degree of adaptation to different anthropometries as well. Failing to deal with these problems causes misalignments between the robot and the user joint. Axes misalignment leads to the impossibility of controlling the torque effectively transmitted to the user joint and causes undesired loading forces on articulations and soft tissues. In this paper, we propose a general analytical method for the design of exoskeletons able to assist human joints without being subjected to misalignment effects. This method is based on a kinetostatic analysis of a coupled mechanism (robot–human skeleton) and can be applied in the design of self-aligning mechanisms. The method is exemplified in the design of an assistive robotic chain for a two-degree-of-freedom (DOF) human articulation. [ABSTRACT FROM AUTHOR]

Electromyographical (EMG) signals have been frequently used to estimate human muscular torques. In the field of human-assistive robotics, these methods provide valuable information to provide effectively support to the user. However, their usability is strongly limited by the necessity of complex user-dependent and session-dependent calibration procedures, which confine their use to the laboratory environment. Nonetheless, an accurate estimate of muscle torque could be unnecessary to provide effective movement assistance to users. The natural ability of human central nervous system of adapting to external disturbances could compensate for a lower accuracy of the torque provided by the robot and maintain the movement accuracy unaltered, while the effort is reduced. In order to explore this possibility, in this paper we study the reaction of ten healthy subjects to the assistance provided through a proportional EMG control applied by an elbow powered exoskeleton. This system gives only a rough estimate of the user muscular torque but does not require any specific calibration. Experimental results clearly show that subjects adapt almost instantaneously to the assistance provided by the robot and can reduce their effort while keeping full control of the movement under different dynamic conditions (i.e., no alterations of movement accuracy are observed). [ABSTRACT FROM PUBLISHER]

We propose a novel method for movement assistance that is based on adaptive oscillators, i.e., mathematical tools that are capable of extracting the high-level features (amplitude, frequency, and offset) of a periodic signal. Such an oscillator acts like a filter on these features, but keeps its output in phase with respect to the input signal. Using a simple inverse model, we predicted the torque produced by human participants during rhythmic flexion–extension of the elbow. Feeding back a fraction of this estimated torque to the participant through an elbow exoskeleton, we were able to prove the assistance efficiency through a marked decrease of the biceps and triceps electromyography. Importantly, since the oscillator adapted to the movement imposed by the user, the method flexibly allowed us to change the movement pattern and was still efficient during the nonstationary epochs. This method holds promise for the development of new robot-assisted rehabilitation protocols because it does not require prespecifying a reference trajectory and does not require complex signal sensing or single-user calibration: the only signal that is measured is the position of the augmented joint. In this paper, we further demonstrate that this assistance was very intuitive for the participants who adapted almost instantaneously. [ABSTRACT FROM AUTHOR]

Lower-limb powered prostheses can provide users with volitional control of ambulation. To accomplish this goal, they require a sensing modality that reliably interprets user intention to move. Surface electromyography (EMG) has been previously proposed to measure muscle excitation and provide volitional control to upper- and lower-limb powered prosthesis users. Unfortunately, EMG suffers from a low signal to noise ratio and crosstalk between neighboring muscles, often limiting the performance of EMG-based controllers. Ultrasound has been shown to have better resolution and specificity than surface EMG. However, this technology has yet to be integrated into lower-limb prostheses. Here we show that A-mode ultrasound sensing can reliably predict the prosthesis walking kinematics of individuals with a transfemoral amputation. Ultrasound features from the residual limb of 9 transfemoral amputee subjects were recorded with A-mode ultrasound during walking with their passive prosthesis. The ultrasound features were mapped to joint kinematics through a regression neural network. Testing of the trained model against untrained kinematics from an altered walking speed show accurate predictions of knee position, knee velocity, ankle position, and ankle velocity, with a normalized RMSE of 9.0 ± 3.1%, 7.3 ± 1.6%, 8.3 ± 2.3%, and 10.0 ± 2.5% respectively. This ultrasound-based prediction suggests that A-mode ultrasound is a viable sensing technology for recognizing user intent. This study is the first necessary step towards implementation of volitional prosthesis controller based on A-mode ultrasound for individuals with transfemoral amputation.

Emerging robotic knee and ankle prostheses present an opportunity to restore the biomechanical function of missing biological legs, which is not possible with conventional passive prostheses. However, challenges in coordinating the robotic prosthesis movements with the user's neuromuscular system and transitioning between activities limit the real-world viability of these devices. Here we show that a shared neural control approach combining neural signals from the user's residual limb with robot control improves functional mobility in individuals with above-knee amputation. The proposed shared neural controller enables subjects to stand up and sit down under a variety of conditions, squat, lunge, walk, and seamlessly transition between activities without explicit classification of the intended movement. No other available technology can enable individuals with above-knee amputations to achieve this level of mobility. Further, we show that compared to using a conventional passive prosthesis, the proposed shared neural controller significantly reduced muscle effort in both the intact limb (21-51% decrease) and the residual limb (38-48% decrease). We also found that the body weight lifted by the prosthesis side increased significantly while standing up with the robotic leg prosthesis (49%-68% increase), leading to better loading symmetry (43-46% of body weight on the prosthesis side). By decreasing muscle effort and improving symmetry, the proposed shared neural controller has the potential to improve amputee mobility and decrease the risk of falls compared to using conventional passive prostheses.