Original articleEffects of robotic exoskeleton control options on lower limb muscle synergies during overground walking: An exploratory study among able-bodied adults
Introduction
Wearable robotic exoskeletons (WRE) allow people with sensorimotor impairments affecting their lower limb (L/L) to stand and walk and rehabilitation professionals to further adhere to the basic locomotor training principles to promote neuroplasticity. Overground walking with a WRE represents an activity-based rehabilitation intervention that may promote neurological and functional recovery after a central nervous system (CNS) lesion [13], [14]. Most of the first generation of WREs provided total and continuous motorised assistance at the hip and knee joints for the foot to follow a predefined planned trajectory during the swing phase. However, to meet the needs and expectations of neurorehabilitation professionals and end users, a wider range of control options are becoming available on the new generation of WREs. Among those, some recently developed WREs now allow self-selected L/L movement trajectory during the swing phase of the gait cycle (i.e., non-trajectory controlled) that promote active participation of the user and allows stepping variability. This control option can also be combined with assistance or resistance being provided to the L/L. However, whether any of these new control options promote typical muscle activation patterns, or which of those control options could best do it, remains unclear. The limited knowledge about what these new options could bring to the rehabilitation field impedes the development of evidence-based WRE locomotor training strategies during neurorehabilitation.
One way of investigating the effects of different WRE control options on the CNS is through muscle synergy (MSs) analyses. The MSs are a series of motor modules, each containing specific muscular activation patterns to simplify the neuromotor control of locomotion [9], [18], [32]. The CNS needs to control only a small number of these MSs, each containing a specific group of muscles associated with specific biomechanical function during the gait cycle [5], [26]. Simulation studies have shown, for example, that altering body weight and external conditions might lead to changes in MSs characteristics, providing evidence of the link between neuromotor control and specific neurobiomechanical adaptations to a task [22]. Hence, given the configuration of some WREs (i.e., backpack command centre), it is plausible that the motor control when walking without and with a WRE differs.
Although previous studies have explored kinematic outputs and individual muscle activity during walking with robotic devices [15], [33], [35], few studies have explored MSs related to robot-aided walking, and these MSs studies have reported contradictory results. For example, the number of MSs and muscle weighting within each MS were similar when able-bodied individuals walked at different speeds on a treadmill with a WRE, with different amounts of weight support or various levels of robotic guidance [11], [24]. Another study showed that muscle weightings within MSs were modified when using passive guidance during overground walking with a WRE compared to without a WRE [20]. These studies are limited by the most commonly available WRE control options used during walking (i.e., total and continuous motorised assistance according to a predefined planned trajectory), and none of them include in their comparison the most recently developed non-controlled trajectory control options. The recently developed control options offering self-selected L/L trajectories that can be assisted or resisted to different extents by the WRE represent promising interventions for rehabilitation purposes, especially for those individuals that preserve the ability to walk after a CNS lesion. However, it is unknown which of these features are valuable and which ones might result in abnormal patterns of muscle coordination or compensatory strategies required to adapt to these control options. These aspects first need to be investigated in able-bodied individuals to explore how an intact CNS might adapt to these conditions imposed by the WRE, before further exploring muscle patterns adaptations to these control options in individuals with sensory motor impairments.
The present exploratory study aims to gain initial insights regarding the effects of different control options on the number and profile of MSs at the L/L and on their muscle weighting within each MS, during overground walking without and with a WRE set at six different L/L control options (i.e., a subset of trajectory-controlled and non-trajectory controlled options used for neurorehabilitation). It is hypothesised that:
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all WRE control options will preserve MS characteristics extracted during overground walking without a WRE, as the intended L/L kinematics remain similar;
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walking with the WRE set to non-trajectory controlled options will lead to variable changes in MS characteristics depending on the control option used, since these options allow increased voluntary participation and step variability by imposing different constraints on the L/L motion.
Stronger evidence is needed to provide new insights into the effects of various control options on biomechanical and neural locomotor control [10], and to inform how different control options may be applied during locomotor training of individuals with sensorimotor impairments and limited walking ability following a neurological event.
Section snippets
Participants
A non-probabilistic convenience sample of 20 able-bodied adults (11 men, 9 women; mean age = 31.0 ± 12.5 years; height = 1.70 ± 0.10 m; weight = 73.4 ± 13.9 kg; body mass index = 24.9 ± 3.5 kg/m2) was recruited. To be included in the study, participants had to be at least 18 years of age and present no neuromusculoskeletal impairments affecting their L/L or lower back, or any other conditions that could restrict their capacity to walk, follow simple verbal commands, or perceive auditory cues. The study was
Walking speeds
Walking speeds across all overground and WRE conditions are presented in Table 2. Walking speeds were similar (P > 0.05) between REF-EXO and most non-trajectory controlled options except for HASSIST (P = 0.01). By contrast, walking speeds were significantly different (P ˂ 0.05) between REF-NAT and all WRE control options, with speed reductions between −84.4 ± 20.4% and −138 ± 8.9%. Overall, the slowest speed was TOT, being 76.9 ± 19.7% slower than REF-EXO and −138 ± 8.9% slower than REF-NAT.
Number and muscle weightings of muscle synergies
Overall, three to
Discussion
The present study investigated the effects of different WRE control options on MSs in terms of number, activation profiles, muscle weightings, and EMG profiles of individual muscles composing each MS. Although previous research investigating MS characteristics using robotic devices was limited to trajectory-controlled WRE passive and active control options [11], [20], to our knowledge, this is the first study investigating MSs during WRE walking with a range of WRE control options, including
Conclusion
The number of MSs and their muscle weightings observed during typical overground walking is maintained when walking with various WRE control options, although their temporal profiles vary to different extents. Non-trajectory-controlled options best duplicated the typical MSs found during overground walking, whereas the most commonly used controlled options (i.e., passive and active trajectory controlled options) presented the most differences in terms of muscle weightings and temporal profiles.
Disclosure of interest
The authors declare that they have no competing interest.
Acknowledgements
The authors would like to acknowledge Philippe Gourdou for his assistance with data processing. MJ Escalona was supported by a doctoral scholarship from the Fonds de Recherche du Québec-Santé (FRQ-S) and the Initiative for the Development of New Technologies and Practices in Rehabilitation (INSPIRE). D. Le Flem was supported by a research internship grant from INSPIRE. DH Gagnon is supported by a senior research scientist salary support grant from the FRQ-S and co-leads INSPIRE. The equipment
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