In the last two decades, numerous powered ankle-foot orthoses have been developed. Despite similar designs and control strategies being shared by some of these devices, their performance in terms of achieving a comparable goal varies. It has been shown that the effect of powered ankle-foot orthoses on healthy users is altered by some factors of the testing protocol. This paper provides an overview of the effect of powered walking on healthy and weakened users. It identifies a set of key factors influencing the performance of powered ankle-foot orthoses, and it presents the effects of these factors on healthy subjects, highlighting the similarities and differences of the results obtained in different works. Furthermore, the outcomes of studies performed on elderly and impaired subjects walking with powered ankle-foot orthoses are compared, to outline the effects of powered walking on these users. This article shows that several factors mutually influence the performance of powered ankle-foot orthoses on their users and, for this reason, the determination of their effects on the user is not straightforward. One of the key factors is the adaptation of users to provided assistance. This factor is very important for the assessment of the effects of powered ankle-foot orthoses on users, however, it is not always reported by studies. Moreover, future works should report, together with the results, the list of influencing factors used in the protocol, to facilitate the comparison of the obtained results. This article also underlines the need for a standardized method to benchmark the actuators of powered ankle-foot orthoses, which would ease the comparison of results between the performed studies. In this paper, the lack of studies on elderly and impaired subjects is highlighted. The insufficiency of these studies makes it difficult to assess the effects of powered ankle-foot orthoses on these users. To summarize, this article provides a detailed overview of the work performed on powered ankle-foot orthoses, presenting and analyzing the results obtained, but also emphasizing topics on which more research is still required.

Exoskeletons have shown their ability to assist locomotion and augment human performances. However, the benefits of wearing these devices depend on how effectively power can be transmitted from the device to the user's biological structures. Recent studies have shown evidence of inefficient power transmission, with losses of up to 50%. The problem of power transmission can be mitigated by designing interfaces that increase contact stiffness and reduce relative motion between the limb and the robot. In this contribution, the design and development of physical interfaces for rigid lower limb exoskeletons is presented. The relative motion between the human and the developed interface is evaluated using a motion capture system and compared to the performances of a commercially available interface. Results indicate a clear reduction in relative motion between the user and the exoskeleton when the customized interface is worn.

Forecasting performances of feed-forward and recurrent neural networks (NN) trained with different learning algorithms are analyzed and compared using the Mackey-Glass nonlinear chaotic time series. This system is a known benchmark test whose elements are hard to predict. Multi-layer Perceptron NN was chosen as a feed-forward neural network because it is still the most commonly used network in financial forecasting models. It is compared with the modified version of the so-called Dynamic Multi-layer Perceptron NN characterized with a dynamic neuron model, i.e., Auto Regressive Moving Average filter built into the hidden layer neurons. Thus, every hidden layer neuron has the ability to process previous values of its own activity together with new input signals. The obtained results indicate satisfactory forecasting characteristics of both networks. However, recurrent NN was more accurate in practically all tests using less number of hidden layer neurons than the feed-forward NN. This study once again confirmed a great effectiveness and potential of dynamic neural networks in modeling and predicting highly nonlinear processes. Their application in the design of financial forecasting models is therefore most recommended.

The ankle joint is the main contributor in providing support to the body, ensuring forward progression and initiating the swing of the leg during the push-off phase of walking. However, its capability can be negatively altered by neuromuscular disorders. In these cases, an active ankle-foot orthosis (AAFO) can greatly enhance the rehabilitation of the affected patients. This paper presents the mechanical design of a lightweight and compliant AAFO, which can be used for rehabilitation purposes. The actuator is bidirectional, thus it can assist the ankle during both dorsiflexion and plantarflexion. With respect to most of the existing AAFOs, the presented one is adaptable to different subjects. The connections between the ankle actuator and the user's shank and foot are designed to fit the AAFO to different users and to align the human and the robot ankle joints, without the need of building customized versions of it. The implemented ankle actuator is a MACCEPA (Mechanically Adjustable Compliance and Controllable Equilibrium Position Actuator) and it can provide a peak torque of 25Nm. Due to a careful design of the actuator components, the total weight of the AAFO is only 1.7kg.