Anticipatory detection of turning in humans for intuitive control of robotic mobility assistance

EMG-based prediction of step direction for a better control of lower limb wearable devices

BACKGROUND AND OBJECTIVES

Lower-limb wearable devices can significantly improve the quality of life of subjects suffering from debilitating conditions, such as amputations, neurodegenerative disorders, and stroke-related impairments. Current control approaches, limited to forward walking, fall short of replicating the complexity of human locomotion in complex environments, such as uneven terrains or crowded places. Here we propose a high-level controller based on two Support Vector Machines exploiting four surface electromyography (EMG) signals of the thigh muscles to detect the onset (Toe-off intention decoder) and the direction (Directional EMG decoder) of the upcoming step.

METHODS AND MATERIALS

We validated a preliminary version of the approach by acquiring EMG signals from ten healthy subjects, performing steps in four directions (forward, backward, right, and left), in three different settings (ground-level walking, stairs, and ramps), and in both steady-state and static conditions. Both the Toe-off intention and Directional EMG decoders have been tested with a 5-fold cross-validation repeated five times, using linear and radial-basis-function kernels, and by changing the classification output timing, from 200 ms before to 50 ms after the toe-off.

RESULTS

The Toe-off intention decoder reached a median accuracy of 83.34 % (interquartile range (IQR): 6.48) and specificity of 92.72 % (IQR: 3.62) in its radial-basis-function version, while the Directional EMG decoder's median accuracy ranged between 73.92 % (IQR: 5.8), 200 ms before the toe-off, to 92.91 % (IQR: 4.11), 50 ms after the toe-off, with the radial-basis-function kernel implementation. For both the Toe-off intention and Directional EMG decoders the radial-basis-function version achieved better performances than the linear one (Wilcoxon signed rank test, p < 0.05).

CONCLUSIONS AND SIGNIFICANCE

The combination of the two decoders proved to be a promising solution to detect the step initiation and classify its direction, paving the way for wearable devices with a broader range of movements and more degrees of freedom, ultimately promoting usability in uncontrolled settings and better reactions to external perturbations. Additionally, the encumbrance of the setup is limited to the thigh of the leg of interest, which simplifies the implementation in compact devices, concurrently limiting the sensors worn by the subject.

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

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-021-00906-3.

Gravito-inertial ambiguity resolved through head stabilization

It has been frequently observed that humans and animals spontaneously stabilize their heads with respect to the gravitational vertical during body movements even in the absence of vision. The interpretations of this intriguing behaviour have so far not included the need, for survival, to robustly estimate verticality. Here we use a mechanistic model of the head/otolith organ to analyse the possibility for this system to render verticality 'observable', a fundamental prerequisite to the determination of the angular position and acceleration of the head from idiothetic, inertial measurements. The intrinsically nonlinear head-vestibular dynamics is shown to generally lack observability unless the head is stabilized in orientation by feedback. Thus, our study supports the hypothesis that a central function of the physiologically costly head stabilization strategy is to enable an organism to estimate the gravitational vertical and head acceleration during locomotion. Moreover, our result exhibits a rare peculiarity of certain nonlinear systems to fortuitously alter their observability properties when feedback is applied.