At moderate to fast walking speeds, the human ankle provides net positive work at high-mechanical-power output to propel the body upward and forward during the stance period. On the contrary, conventional ankle–foot prostheses exhibit a passiveelastic response during stance, and consequently, cannot provide net work. Clinical studies indicate that transtibial ampu-tees using conventional prostheses have higher gait metabolic rates than normal. Researchers believe that the main cause for these higher rates is due to the inability of conventional prostheses to provide suf-ficient positive power at terminal stance in the trailing leg to limit heel strike losses of the adjacent leading leg. In this investigation, we evaluate the hypothesis that a powered ankle–foot prosthesis, ca-pable of providing human-like ankle work and power during stance, can decrease the metabolic cost of trans-port (COT) compared to a conventional passive-elastic prosthesis. To test the hypothesis, a powered pros- thesis is built that comprises a unidirectional spring, configured in parallel with a force-controllable actuator with series elasticity. The prosthesis is shown to deliver the high mechanical power and net po-sitive work observed in normal human walking. The rate of oxygen consumption and carbon dioxide production is measured as a determinant of metabolic rate on three unilateral transtibial amputees walking at self- selected speeds. We find that the powered prosthesis decreases the amputee’s metabolic COT on average by 14% compared to the conventional passive-elastic prostheses evaluated (Flex-Foot Ceterus R
and Freedom In-novations Sierra), even though the powered system is over twofold heavier than the conventional devices. These results highlight the clinical importance of prosthetic interventions that closely mimic the mass di-stribution, kinetics, and kinematics of the missing limb.

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This paper presents a novel design for a 4 degree of freedom pneumatically-actuated upper-limb rehabilitation device. BONES is based on a parallel mechanism that actuates the upper arm by means of two passive, sliding rods pivoting with respect to a fixed structural frame. Four, mechanically-grounded pneumatic actuators are placed behind the main structural frame to control shoulder motion via the sliding rods, and a fifth cylinder is located on the structure to control elbow flexion/extension. The device accommodates a wide range of motion of the human arm, while also achieving low inertia and direct-drive force generation capability at the shoulder. A key accomplishment of this design is the ability to generate arm internal/external rotation without any circular bearing element such as a ring, a design feature inspired by the biomechanics of the human forearm. The paper describes the rationale for this device and its main design aspects including its kinematics, range of motion, and force generation capability.

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Gait training of stroke survivors can help in retraining their muscles and improving their gait pattern. Robot assisted gait training (RAGT) was developed for stroke survivors using ALEX and force-field controller, which use assist-as-needed paradigm for rehabilitation. In this paradigm undesirable gait motion is resisted and assistance is provided towards the desirable motion. The force-field controller achieves this paradigm by applying forces at the foot of the subject. Two stroke survivors participated in a 15-day gait training study each with ALEX. The results show that by the end of the training the gait pattern of the patients was improved towards healthy subjects gait pattern. Improvement is seen as increase in the size of the patientspsila gait pattern, increase in knee and ankle joint excursions and increase in their walking speed on the treadmill.

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This paper presents multi-criteria design optimization of parallel mechanism based force feedback exoskeletons for human forearm and wrist. The optimized devices are aimed to be employed as a high fidelity haptic interfaces. Multiple design objectives are discussed and classified for the devices and the optimization problem to study the trade-offs between these criteria is formulated. Dimensional syntheses are performed for optimal global kinematic and dynamic performance, utilizing a Pareto front based framework, for two spherical parallel mechanisms that satisfy the ergonomic necessities of a human forearm and wrist. Two optimized mechanisms are compared and discussed in the light of multiple design criteria. Finally, kinematic structure and dimensions of an optimal exoskeleton are decided.

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Background: In virtual reality (VR) systems, the user’s finger and hand positions are sensed and used to control the virtual envi-ronments. Direct biocontrol of VR environments using surface electromyography (SEMG) signals may be more synergistic and uncons-training to the user. The purpose of the present investigation was to develop a technique to predict the finger joint angle from the surface EMG measurements of the extensor muscle using neural network models.
Methodology: SEMG together with the actual joint angle measurements were obtained while the subject was performing flexion-exten-sion rotation of the index finger at three speeds. Several neural networks were trained to predict the joint angle from the para-meters extracted from the SEMG signals. The best networks were selected to form six committees. The neural network committees were evaluated using data from new subjects.
Results: There was hysteresis in the measured SMEG signals during the flexion-extension cycle. However, neural network committees were able to predict the joint angle with reasonable accuracy. RMS errors ranged from 0.085 ± 0.036 for fast speed finger-extension to 0.147 ± 0.026 for slow speed finger extension, and from 0.098 ± 0.023 for the fast speed finger flexion to 0.163 ± 0.054 for slow speed finger flexion.
Conclusion: Although hysteresis was observed in the measured SEMG signals, the committees of neural networks were able to predict the finger joint angle from SEMG signals.

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