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Background: Few portable exoskeletons following the assist-as-needed concept have been developed for patients with neurological disorders. Thus, the main objectives of this proof-of-concept study were 1) to explore the safety and feasibility of an exoskeleton for gait rehabilitation in stroke and multiple sclerosis patients, 2) to test different algorithms for gait assistance and measure the resulting gait changes and 3) to evaluate the user's perception of the device. Methods: A cross-sectional study was conducted. Five patients were recruited (4 patients with stroke and 1 with multiple sclerosis). A robotic, one-degree-of-freedom, portable lower limb exoskeleton known as the Marsi Active Knee (MAK) was designed. Three control modes (the Zero Force Control mode, Mode 1 and Mode 3) were implemented. Spatiotemporal gait parameters were measured by the 10-m walking test (10MWT), the Gait Assessment and Intervention Tool (G.A.I.T.) and Tinetti Performance Oriented Mobility Assessment (gait subscale) before and after the trials. A modified QUEST 2.0 questionnaire was administered to determine each participant's opinion about the exoskeleton. The data acquired by the MAK sensors were normalized to a gait cycle, and adverse effects were recorded. Results: The MAK exoskeleton was used successfully without any adverse effects. Better outcomes were obtained in the 10MWT and G.A.I.T. when Mode 3 was applied compared with not wearing the device at all. In 2 participants, Mode 3 worsened the results. Additionally, Mode 3 seemed to improve the 10MWT and G.A.I.T. outcomes to a greater extent than Mode 1. The overall score for the user perception of the device was 2.8 ± 0.4 95% CI. Conclusions: The MAK exoskeleton seems to afford positive preliminary results regarding safety, feasibility, and user acceptance. The efficacy of the MAK should be studied in future studies, and more advanced improvements in safety must be implemented.

Purpose -Reducing energy consumption in walking robots is an issue of great importance in field applications such as humanitarian demining so as to increase mission time for a given power supply. The purpose of this paper is to address the problem of improving energy efficiency in statically stable walking machines by comparing two leg, insect and mammal, configurations on the hexapod robotic platform SIL06. Design/methodology/approach -Dynamic simulation of this hexapod is used to develop a set of rules that optimize energy expenditure in both configurations. Later, through a theoretical analysis of energy consumption and experimental measurements in the real platform SIL06, a configuration is chosen. Findings -It is widely accepted that the mammal configuration in statically stable walking machines is better for supporting high loads, while the insect configuration is considered to be better for improving mobility. However, taking into account the leg dynamics and not only the body weight, different results are obtained. In a mammal configuration, supporting body weight accounts for 5 per cent of power consumption while leg dynamics accounts for 31 per cent. Originality/value -As this paper demonstrates, the energy expended when the robot walks along a straight and horizontal line is the same for both insect and mammal configurations, while power consumption during crab walking in an insect configuration exceeds power consumption in the mammal configuration.

By analysing the dynamic principles of the human gait, an economic gait‐control analysis is performed, and passive elements are included to increase the energy efficiency in the motion control of active orthoses. Traditional orthoses use position patterns from the clinical gait analyses (CGAs) of healthy people, which are then de‐normalized and adjusted to each user. These orthoses maintain a very rigid gait, and their energy cost is very high, reducing the autonomy of the user. First, to take advantage of the inherent dynamics of the legs, a state machine pattern with different gains in each state is applied to reduce the actuator energy consumption. Next, different passive elements, such as springs and brakes in the joints, are analysed to further reduce energy consumption. After an off‐line parameter optimization and a heuristic improvement with genetic algorithms, a reduction in energy consumption of 16.8% is obtained by applying a state machine control pattern, and a reduction of 18.9% is obtained by using passive elements. Finally, by combining both strategies, a more natural gait is obtained, and energy consumption is reduced by 24.6% compared with a pure CGA pattern