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Above-knee amputation severely reduces the mobility and quality of life of millions of individuals. Walking with available leg prostheses is highly inefficient, and poor walking economy is a major problem limiting mobility. Here we show that an autonomous powered hip exoskeleton assisting the residual limb significantly improves metabolic walking economy by 15.6 [plus or minus] 2.9% (mean [plus or minus] s.e.m.; two-tailed paired t-test, P = 0.002) in six individuals with above-knee amputation walking on a treadmill. The observed metabolic cost improvement is equivalent to removing a 12-kg backpack from a nonamputee individual. All participants were able to walk overground with the exoskeleton, including starting and stopping, without notable changes in gait balance or stability. This study shows that assistance of the user's residual limb with a powered hip exoskeleton is a viable solution for improving amputee walking economy. By significantly reducing the metabolic cost of walking, the proposed hip exoskeleton may have a considerable positive impact on mobility, improving the quality of life of individuals with above-knee amputations. In individuals with above-knee amputation, a powered hip exoskeleton, which reduces the metabolic cost of walking by adding energy at the hip joint, greatly improves walking economy and has the potential to improve mobility., Author(s): Marshall K. Ishmael [sup.1] , Dante Archangeli [sup.1] , Tommaso Lenzi [sup.1] Author Affiliations: (1) Department of Mechanical Engineering and Robotics Center, University of Utah, Salt Lake City, USA [...]

Across different fields within robotics, there is a great need for lightweight, efficient actuators with human-like performance. Linkage-based passive variable transmissions and torque-sensitive transmissions have emerged as promising solutions to meet this need by significantly increasing actuator efficiency and power density, but their modeling and analysis remain an open research topic. In this paper, we introduce the sensitivity between input displacement and output torque as a key metric to analyze the performance of these complex mechanisms in dynamic tasks. We present the analytical model of sensitivity in the context of two different torque-sensitive transmission designs, and used this sensitivity metric to analyze the differences in their performance. Experiments with these designs implemented within a powered knee prosthesis were conducted, and results validated the sensitivity model as well as its role in predicting actuators' dynamic performance. Together with other design methods, sensitivity analysis is a valuable tool for designers to systematically analyze and create transmission systems capable of human-like physical behavior. [ABSTRACT FROM AUTHOR]

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 exoskeletons need actuators that are lightweight, compact, and efficient while allowing for accurate torque control. To satisfy these requirements, researchers have proposed using series elastic actuators (SEAs). SEAs use a spring in series with rotary or linear actuators. The spring compliance, in conjunction with an appropriate control scheme, improves torque control, efficiency, output impedance, and disturbance rejection. However, springs add weight to the actuator and complexity to the control, which may have negative effects on the performance of the powered exoskeleton. Therefore, there is an unmet need for new SEA designs that are lighter and more efficient than available systems, as well as for control strategies that push the performance of SEA-based exoskeletons without requiring complex modeling and tuning. This article presents the design, development, and testing of a novel SEA with high force density for powered exoskeletons, as well as the use of a two degree-of-freedom (2DOF) PID system to improve output impedance and disturbance rejection. Benchtop testing results show reduced output impedance and damping values when using a 2DOF PID controller as compared to a 1DOF PID controller. Human experiments with three able-bodied subjects (N = 3) show improved torque tracking with reduced root-mean-square error by 45.2% and reduced peak error by 49.8% when using a 2DOF PID controller. Furthermore, EMG data shows a reduction in peak EMG value when using the exoskeleton in assistive mode compared to the exoskeleton operating in transparent mode. [ABSTRACT FROM AUTHOR]

Many people struggle with mobility impairments due to lower limb amputations. To participate in society, they need to be able to walk on a wide variety of terrains, such as stairs, ramps, and level ground. Current lower limb powered prostheses require different control strategies for varying ambulation modes, and use data from mechanical sensors within the prosthesis to determine which ambulation mode the user is in. However, it can be challenging to distinguish between ambulation modes. Efforts have been made to improve classification accuracy by adding electromyography information, but this requires a large number of sensors, has a low signal-to-noise ratio, and cannot distinguish between superficial and deep muscle activations. An alternative sensing modality, A-mode ultrasound, can detect and distinguish between changes in superficial and deep muscles. It has also shown promising results in upper limb gesture classification. Despite these advantages, A-mode ultrasound has yet to be employed for lower limb activity classification. Here we show that A- mode ultrasound can classify ambulation mode with comparable, and in some cases, superior accuracy to mechanical sensing. In this study, seven transfemoral amputee subjects walked on an ambulation circuit while wearing A-mode ultrasound transducers, IMU sensors, and their passive prosthesis. The circuit consisted of sitting, standing, level-ground walking, ramp ascent, ramp descent, stair ascent, and stair descent, and a spatial–temporal convolutional network was trained to continuously classify these seven activities. Offline continuous classification with A-mode ultrasound alone was able to achieve an accuracy of 91.8 ± 3.4 % , compared with 93.8 ± 3.0 % , when using kinematic data alone. Combined kinematic and ultrasound produced 95.8 ± 2.3 % accuracy. This suggests that A-mode ultrasound provides additional useful information about the user's gait beyond what is provided by mechanical sensors, and that it may be able to improve ambulation mode classification. By incorporating these sensors into powered prostheses, users may enjoy higher reliability for their prostheses, and more seamless transitions between ambulation modes. [ABSTRACT FROM AUTHOR]

Robotic leg prostheses promise to improve the mobility and quality of life of millions of individuals with lower-limb amputations by imitating the biomechanics of the missing biological leg. Unfortunately, existing powered prostheses are much heavier and bigger and have shorter battery life than conventional passive prostheses, severely limiting their clinical viability and utility in the daily life of amputees. Here, we present a robotic leg prosthesis that replicates the key biomechanical functions of the biological knee, ankle, and toe in the sagittal plane while matching the weight, size, and battery life of conventional microprocessor-controlled prostheses. The powered knee joint uses a unique torque-sensitive mechanism combining the benefits of elastic actuators with that of variable transmissions. A single actuator powers the ankle and toe joints through a compliant, underactuated mechanism. Because the biological toe dissipates energy while the biological ankle injects energy into the gait cycle, this underactuated system regenerates substantial mechanical energy and replicates the key biomechanical functions of the ankle/foot complex during walking. A compact prosthesis frame encloses all mechanical and electrical components for increased robustness and efficiency. Preclinical tests with three individuals with above-knee amputation show that the proposed robotic leg prosthesis allows for common ambulation activities with close to normative kinematics and kinetics. Using an optional passive mode, users can walk on level ground indefinitely without charging the battery, which has not been shown with any other powered or microprocessor-controlled prostheses. A prosthesis with these characteristics has the potential to improve real-world mobility in individuals with above-knee amputation. [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]

Robotic exoskeletons can assist humans with walking by providing supplemental torque in proportion to the user's joint torque. Electromyographic (EMG) control algorithms can estimate a user's joint torque directly using real-time EMG recordings from the muscles that generate the torque. However, EMG signals change as a result of supplemental torque from an exoskeleton, resulting in unreliable estimates of the user's joint torque during active exoskeleton assistance. Here, we present an EMG control framework for robotic exoskeletons that provides consistent joint torque predictions across varying levels of assistance. Experiments with three healthy human participants showed that using diverse training data (from different levels of assistance) enables robust torque predictions, and that a convolutional neural network (CNN), but not a Kalman filter (KF), can capture the non-linear transformations in EMG due to exoskeleton assistance. With diverse training, the CNN could reliably predict joint torque from EMG during zero, low, medium, and high levels of exoskeleton assistance [root mean squared error (RMSE) below 0.096 N-m/kg]. In contrast, without diverse training, RMSE of the CNN ranged from 0.106 to 0.144 N-m/kg. RMSE of the KF ranged from 0.137 to 0.182 N-m/kg without diverse training, and did not improve with diverse training. When participant time is limited, training data should emphasize the highest levels of assistance first and utilize at least 35 full gait cycles for the CNN. The results presented here constitute an important step toward adaptive and robust human augmentation via robotic exoskeletons. This work also highlights the non-linear reorganization of locomotor output when using assistive exoskeletons; significant reductions in EMG activity were observed for the soleus and gastrocnemius, and a significant increase in EMG activity was observed for the erector spinae. Control algorithms that can accommodate spatiotemporal changes in muscle activity have broad implications for exoskeleton-based assistance and rehabilitation following neuromuscular injury. [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]

Powered prostheses aim to mimic the missing biological limb with controllers that are finely tuned to replicate the nominal gait pattern of non-amputee individuals. Unfortunately, this control approach poses a problem with real-world ambulation, which includes tasks such as crossing over obstacles, where the prosthesis trajectory must be modified to provide adequate foot clearance and ensure timely foot placement. Here, we show an indirect volitional control approach that enables prosthesis users to walk at different speeds while smoothly and continuously crossing over obstacles of different sizes without explicit classification of the environment. At the high level, the proposed controller relies on a heuristic algorithm to continuously change the maximum knee flexion angle and the swing duration in harmony with the user's residual limb. At the low level, minimum-jerk planning is used to continuously adapt the swing trajectory while maximizing smoothness. Experiments with three individuals with above-knee amputation show that the proposed control approach allows for volitional control of foot clearance, which is necessary to negotiate environmental barriers. Our study suggests that a powered prosthesis controller with intrinsic, volitional adaptability may provide prosthesis users with functionality that is not currently available, facilitating real-world ambulation. [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]

Modern lean burn aero-engine combustors make use of relevant swirl degrees for flame stabilization. Moreover, important temperature distortions are generated, in tangential and radial directions, due to discrete fuel injection and liner cooling flows respectively. At the same time, more efficient devices are employed for liner cooling and a less intense mixing with the mainstream occurs. As a result, aggressive swirl fields, high turbulence intensities, and strong hot streaks are achieved at the turbine inlet. In order to understand combustor-turbine flow field interactions, it is mandatory to collect reliable experimental data at representative flow conditions. While the separated effects of temperature, swirl, and turbulence on the first turbine stage have been widely investigated, reduced experimental data is available when it comes to consider all these factors together. In this perspective, an annular three-sector combustor simulator with fully cooled high pressure vanes has been designed and installed at the THT Lab of University of Florence. The test rig is equipped with three axial swirlers, effusion cooled liners, and six film cooled high pressure vanes passages, for a vortex-to-vane count ratio of 1:2. The relative clocking position between swirlers and vanes has been chosen in order to have the leading edge of the central NGV aligned with the central swirler. In order to generate representative conditions, a heated mainstream passes though the axial swirlers of the combustor simulator, while the effusion cooled liners are fed by air at ambient temperature. The resulting flow field exiting from the combustor simulator and approaching the cooled vane can be considered representative of a modern Lean Burn aero engine combustor with swirl angles above ±50deg, turbulence intensities up to about 28% and maximum-to-minimum temperature ratio of about 1.25. With the final aim of investigating the hot streaks evolution through the cooled high pressure vane, the mean aerothermal field (temperature, pressure, and velocity fields) has been evaluated by means of a five-hole probe equipped with a thermocouple and traversed upstream and downstream of the NGV cascade. [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]

We present a lightweight robotic knee prosthesis with a novel hybrid actuation system that enables passive and active operation modes. The proposed hybrid knee uses a spring-damper system in combination with an electric motor and transmission system, which can be engaged to provide a stair ambulation capability. In comparison to fully powered prostheses that power all ambulation activities, a hybrid knee prosthesis can achieve significant weight reduction by focusing the design of the actuator on a subset of activities without losing the ability to produce equivalent torque and mechanical power in the active mode. The hybrid knee prototype weighs 1.7 kg, including battery and control, and can provide up to 125 Nm of repetitive torque. Experiments with two transfemoral amputee subjects show that the proposed hybrid knee prosthesis can support walking on level ground in the passive mode, as well as stair ambulation with a reciprocal gait pattern in the active mode. [ABSTRACT FROM AUTHOR]

Aim: The aim of this study was to compare early and late injections of intravitreal dexamethasone implant in patients affected by central retinal vein occlusion (CRVO) or branch retinal vein occlusion (BRVO) with a six-months follow-up. We assessed whether an earlier treatment start (within seven days from diagnosis) could be more beneficial than a delayed (or late) treatment start (after seven days). Materials and methods: The study included 81 patients (81 eyes) affected by retinal vein occlusion. Best corrected visual acuity was assessed through Early Treatment Diabetic Retinopathy Study (ETDRS) while central macular thickness (CMT) was measured by spectral-domain optical coherence tomography. Results: Both types of patients had a positive therapeutic response to dexamethasone, with an increase in visual acuity (ETDRS) and CMT reduction. CRVO patients were characterized by lower ETDRS values at baseline and at the end of the follow-up as compared to BRVO. CRVO patients showed higher CMT values at baseline, after three and six months from injection. No significant differences in therapeutic response to dexamethasone were observed between patients treated early or late, regardless of RVO type. Conclusions: This study demonstrates that the therapeutic properties of dexamethasone implant are not significantly influenced by an early or late treatment start in patients affected by BRVO and CRVO, although its therapeutic efficacy seems greater in the former type. [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]

Background: Acanthamoeba keratitis (AK) is ever more frequently reported in industrialized countries. The loss of the corneal surface integrity consequent to secondary microtrauma produced by the use of contact lens (CL) favors the penetration of the parasite into the corneal tissue. Objectives: A scientific review was performed to investigate the association of CL wear as an Acanthamoeba keratitis (AK) risk factor. Methods: A computerized screening of 7834 Medline articles (4623 from PubMed; 3211 from Scopus) used a strict selection criteria of case-control studies involving CL wear and/or trauma. Results: The search yielded five case-control studies published from 1995 to 2012. All studies included showed a statistically significant positive association between AK and CL use, with a combined odds ratio (OR) of 10.21 (95%, confidence intervals [CI]; 3.57-27.64). Statistical analysis: All studies included showed a statistically significant positive association between AK and CL use, though with differing OR values. Conclusion: Though rare, AK should be held in higher consideration when ophthalmologists are faced with CL users exhibiting simplex-like lesions associated with circular stromal infiltrates and disproportionate ocular pain in respect to the objective clinical picture. [ABSTRACT FROM AUTHOR]

Background: This randomized double-blind study examined the use of a new anesthetic agent, levobupivacaine 0.5%, which is the S(-)-enantiomer of a racemic mixture of bupivacaine, for peribulbar anesthesia and compared it with racemic bupivacaine 0.5% alone or in combination with hyaluronidase 10 IU/mL. Methods: A total of 160 patients undergoing ophthalmic surgery were randomized into four groups (n = 40 each) to receive inferotemporal peribulbar injection of levobupivacaine 0.5% (group L), racemic bupivacaine 0.5% (group B), levobupivacaine + hyaluronidase 10 IU/mL (group LH), or racemic bupivacaine + hyaluronidase 10 IU/mL (group BH) by two anesthetists and two ophthalmologists in a ratio of 25% each. Ocular akinesia and orbicularis oculi function were evaluated using a three-point scale; a value < 5 points was considered as requiring surgery, and movements were re-evaluated the day following surgery to confirm regression of the block. Results: The time to onset (12 ± 2.6 minutes versus 13 ± 2.8 minutes) and duration of anesthesia (185 ± 33.2 minutes versus 188 ± 35.7 minutes) were similar between groups L and B. Complete akinesia (score 0) was obtained more frequently when hyaluronidase was used in addition to the anesthetic, with occurrences of 72.5% versus 57.5% in group LH versus L, respectively, and 67.5% versus 45% in group BH versus B. Moderate hypotension (,30% of baseline) was observed in four patients (10%) in group L, two (5.0%) in group B, one (2.5%) in group LH, and three (7.5%) in group BH. The time to onset was significantly different between groups L and BH, B and BH, and LH and BH, and the duration of anesthesia differed significantly between groups B and LH, B and BH, and L and LH. The akinesia score differed significantly between groups L and LH and between groups B and LH (P = 0.043 and P = 0.018, respectively), and the number of patients with a score of 0 differed significantly between groups B and LH and between groups B and BH (P = 0.004 and P = 0.017, respectively). Conclusion: Levobupivacaine is a long-lasting local anesthetic with limited cardiotoxicity and neurotoxicity, and may be considered the landmark for vitreoretinal surgery in elderly patients. [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]

We present a sensor technology for the measure of the physical human-robot interaction pressure developed in the last years at Scuola Superiore Sant'Anna. The system is composed of flexible matrices of opto-electronic sensors covered by a soft silicone cover. This sensory system is completely modular and scalable, allowing one to cover areas of any sizes and shapes, and to measure different pressure ranges. In this work we present the main application areas for this technology. A first generation of the system was used to monitor human-robot interaction in upper- (NEUROExos; Scuola Superiore Sant'Anna) and lower-limb (LOPES; University of Twente) exoskeletons for rehabilitation. A second generation, with increased resolution and wireless connection, was used to develop a pressure-sensitive foot insole and an improved human-robot interaction measurement systems. The experimental characterization of the latter system along with its validation on three healthy subjects is presented here for the first time. A perspective on future uses and development of the technology is finally drafted. [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]

A sensory apparatus to monitor pressure distribution on the physical human-robot interface of lower-limb exoskeletons is presented. We propose a distributed measure of the interaction pressure over the whole contact area between the user and the machine as an alternative measurement method of human-robot interaction. To obtain this measure, an array of newly-developed soft silicone pressure sensors is inserted between the limb and the mechanical interface that connects the robot to the user, in direct contact with the wearer's skin. Compared to state-of-the-art measures, the advantage of this approach is that it allows for a distributed measure of the interaction pressure, which could be useful for the assessment of safety and comfort of human-robot interaction. This paper presents the new sensor and its characterization, and the development of an interaction measurement apparatus, which is applied to a lower-limb rehabilitation robot. The system is calibrated, and an example its use during a prototypical gait training task is presented. [ABSTRACT FROM AUTHOR]

Abstract: Antagonistic Driven Compliant Joints (ADCJs) are object of great interest in current robotics research, representing one of the most widely applied solutions to develop human-like and safe joints for human-robot interaction. Providing the joint with “actively” adjustable hardware compliance, ADCJs have two distinctive features: (1) the joint is powered by two independent “actuation units” and (2) each actuation unit works as a non-linear elastic element with an adjustable resting position. This paper proposes a sensorless torque control strategy suitable for ADCJs actuated robots. This method is based on two steps: (1) off-line characterization of the elasticity of the actuation units, defined by the force–elongation curve and (2) online estimation of the force exerted by each actuation unit, through a direct measure of the joint angle, and of the “resting position” of each actuation unit. The proposed force estimation method can be used to develop two independent force controllers, which can be then combined to regulate the resulting joint torque, with no need of additional torque sensors. The performance of the proposed torque control was evaluated over the shoulder and the elbow ADCJs of the 2-link 2-DOFs planar robotic arm NEURARM. The method proved to work effectively, achieving good performances on the test platform, and represents a suitable alternative to state-of-the-art sensor-based torque controls. [Copyright &y& Elsevier]

The presence of injectors with strongly swirled flows, used to promote flame stability in the combustion chambers of gas turbines, influences the behaviour of the effusion cooling jets and consequently of the liner's cooling capabilities. For this reason, unsteady behaviour of the jets in the presence of swirling flow requires a characterization by means of experimental flow field analyses. The experimental setup of this work consists of a non-reactive single-sector linear combustor test rig, scaled up with respect to the real engine geometry to increase spatial resolution and to reduce the frequencies of the unsteadiness. It is equipped with a radial swirler and multi-perforated effusion plates to simulate the liner cooling system. Two effusion plates were tested and compared: with cylindrical and with laid-back fan-shaped 7-7-7 holes in staggered arrangement. Time resolved Particle Image Velocimetry has been carried out: the unsteady characteristics of the jets, promoted by the intermittent interactions with the turbulent mainstream, have been investigated as their vortex structures and turbulent decay. The results demonstrate how an unsteady analysis is necessary to provide a complete characterization of the coolant behaviour and of its turbulent mixing with mainflow, which affect, in turn, the film cooling capability and liner's lifetime. [ABSTRACT FROM AUTHOR]

Objective: Volitional control systems for powered prostheses require the detection of user intent to operate in real life scenarios. Ambulation mode classification has been proposed to address this issue. However, these approaches introduce discrete labels to the otherwise continuous task that is ambulation. An alternative approach is to provide users with direct, voluntary control of the powered prosthesis motion. Surface electromyography (EMG) sensors have been proposed for this task, but poor signal-to-noise ratios and crosstalk from neighboring muscles limit performance. B-mode ultrasound can address some of these issues at the cost of reduced clinical viability due to the substantial increase in size, weight, and cost. Thus, there is an unmet need for a lightweight, portable neural system that can effectively detect the movement intention of individuals with lower-limb amputation., Methods: In this study, we show that a small and lightweight A-mode ultrasound system can continuously predict prosthesis joint kinematics in seven individuals with transfemoral amputation across different ambulation tasks. Features from the A-mode ultrasound signals were mapped to the user's prosthesis kinematics via an artificial neural network., Results: Predictions on testing ambulation circuit trials resulted in a mean normalized RMSE across different ambulation modes of 8.7 ± 3.1%, 4.6 ± 2.5%, 7.2 ± 1.8%, and 4.6 ± 2.4% for knee position, knee velocity, ankle position, and ankle velocity, respectively., Conclusion and Significance: This study lays the foundation for future applications of A-mode ultrasound for volitional control of powered prostheses during a variety of daily ambulation tasks.

Powered lower-limb prostheses have the potential to improve amputee mobility by closely imitating the biomechanical function of the missing biological leg. To accomplish this goal, powered prostheses need controllers that can seamlessly adapt to the ambulation activity intended by the user. Most powered prosthesis control architectures address this issue by switching between specific controllers for each activity. This approach requires online classification of the intended ambulation activity. Unfortunately, any misclassification can cause the prosthesis to perform a different movement than the user expects, increasing the likelihood of falls and injuries. Therefore, classification approaches require near-perfect accuracy to be used safely in real life. In this paper, we propose a unified controller for powered knee prostheses which allows for walking, stair ascent, and stair descent without the need for explicit activity classification. Experiments with one individual with an above-knee amputation show that the proposed controller enables seamless transitions between activities. Moreover, transition between activities is possible while leading with either the sound-side or the prosthesis. A controller with these characteristics has the potential to improve amputee mobility.

Ambulation in everyday life requires walking at variable speeds, variable inclines, and variable terrains. Powered prostheses aim to provide this adaptability through control of the actuated joints. Some powered prosthesis controllers can adapt to discrete changes in speed and incline but require manual tuning to determine the control parameters, leading to poor clinical viability. Other data-driven controllers can continuously adapt to changes in speed and incline but do so by imposing the same non-amputee gait patterns for all amputee subjects, which does not consider subjective preferences and differing clinical needs of users. Here, we present a controller for powered knee and ankle prostheses that can continuously adapt to different walking speeds, inclines, and uneven terrains without enforcing a specific prosthesis position, impedance, or torque. A virtual biarticular muscle connection determines the knee flexion torque, which changes with both speed and slope. Adaptation to inclines and uneven terrains is based solely on the global shank orientation. Continuously variable damping allows for speed adaptation. Minimum-jerk programming defines the prosthesis swing trajectory at variable cadences. Experiments with one individual with an above-knee amputation suggest that the proposed controller can effectively adapt to different walking speeds, inclines, and rough terrains.