Review of control strategies for lower-limb exoskeletons to assist gait

Abstract

Background: Many lower-limb exoskeletons have been developed to assist gait, exhibiting a large range of control methods. The goal of this paper is to review and classify these control strategies, that determine how these devices interact with the user.

Methods: In addition to covering the recent publications on the control of lower-limb exoskeletons for gait assistance, an effort has been made to review the controllers independently of the hardware and implementation aspects. The common 3-level structure (high, middle, and low levels) is first used to separate the continuous behavior (mid-level) from the implementation of position/torque control (low-level) and the detection of the terrain or user's intention (high-level). Within these levels, different approaches (functional units) have been identified and combined to describe each considered controller.

Results: 291 references have been considered and sorted by the proposed classification. The methods identified in the high-level are manual user input, brain interfaces, or automatic mode detection based on the terrain or user's movements. In the mid-level, the synchronization is most often based on manual triggers by the user, discrete events (followed by state machines or time-based progression), or continuous estimations using state variables. The desired action is determined based on position/torque profiles, model-based calculations, or other custom functions of the sensory signals. In the low-level, position or torque controllers are used to carry out the desired actions. In addition to a more detailed description of these methods, the variants of implementation within each one are also compared and discussed in the paper.

Conclusions: By listing and comparing the features of the reviewed controllers, this work can help in understanding the numerous techniques found in the literature. The main identified trends are the use of pre-defined trajectories for full-mobilization and event-triggered (or adaptive-frequency-oscillator-synchronized) torque profiles for partial assistance. More recently, advanced methods to adapt the position/torque profiles online and automatically detect terrains or locomotion modes have become more common, but these are largely still limited to laboratory settings. An analysis of the possible underlying reasons of the identified trends is also carried out and opportunities for further studies are discussed.

Keywords: Control; Exoskeleton; Lower-limb; Review.

Fig. 1

Flowchart of the methodology used for the search and screening process

Fig. 2

Simplified diagram of the proposed classification

Fig. 3

Block diagram of the proposed classification of the control strategies subparts. The idea of this classification is that any controller in the literature can be represented by a path that joins the used control blocks. The path does not have to start from the high-level layer, and may start directly in the mid-level. A controller can have several parallel paths if the controller combines several strategies at the same time, or successively during the gait. Connecting lines show the common paths identified in the literature. However, it should be noted that the lack of a line between two blocks does not mean they cannot be related. For instance, the outcome of the high-level layer, the “operation mode”, could affect any of the blocks of the middle-level, but it is not connected to them for the sake of readability

Fig. 4

Example of angle-speed phase diagram. The data plotted is the hip angle during a few gait cycles of a test session with the exoskeleton SPRIINT (see [325])

Fig. 5

Distribution of actuator types in the reviewed articles. Studies in which the controller was not actually implemented in a real device or the actuator type was not mentioned were excluded for this analysis

Fig. 6

Number of references for each functional block (top: high-level, middle: mid-level, bottom: low-level)

Fig. 7

Percentage of the considered publications that addressed high/mid/low level, per year of publication

Fig. 8

Number of reference considered, per year of publication