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      Exoskeletons need to react faster than physiological responses to improve standing balance

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          Abstract

          Maintaining balance throughout daily activities is challenging because of the unstable nature of the human body. For instance, a person’s delayed reaction times limit their ability to restore balance after disturbances. Wearable exoskeletons have the potential to enhance user balance after a disturbance by reacting faster than physiologically possible. However, “artificially fast” balance-correcting exoskeleton torque may interfere with the user’s ensuing physiological responses, consequently hindering the overall reactive balance response. Here, we show that exoskeletons need to react faster than physiological responses to improve standing balance after postural perturbations. Delivering ankle exoskeleton torque before the onset of physiological reactive joint moments improved standing balance by 9%, whereas delaying torque onset to coincide with that of physiological reactive ankle moments did not. In addition, artificially fast exoskeleton torque disrupted the ankle mechanics that generate initial local sensory feedback, but the initial reactive soleus muscle activity was only reduced by 18% versus baseline. More variance of the initial reactive soleus muscle activity was accounted for using delayed and scaled whole-body mechanics [specifically center of mass (CoM) velocity] versus local ankle—or soleus fascicle—mechanics, supporting the notion that reactive muscle activity is commanded to achieve task-level goals, such as maintaining balance. Together, to elicit symbiotic human-exoskeleton balance control, device torque may need to be informed by mechanical estimates of global sensory feedback, such as CoM kinematics, that precede physiological responses.

          Abstract

          Ankle exoskeletons can improve standing balance by reacting to disturbances faster than the user.

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          Most cited references60

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          OpenSim: open-source software to create and analyze dynamic simulations of movement.

          Dynamic simulations of movement allow one to study neuromuscular coordination, analyze athletic performance, and estimate internal loading of the musculoskeletal system. Simulations can also be used to identify the sources of pathological movement and establish a scientific basis for treatment planning. We have developed a freely available, open-source software system (OpenSim) that lets users develop models of musculoskeletal structures and create dynamic simulations of a wide variety of movements. We are using this system to simulate the dynamics of individuals with pathological gait and to explore the biomechanical effects of treatments. OpenSim provides a platform on which the biomechanics community can build a library of simulations that can be exchanged, tested, analyzed, and improved through a multi-institutional collaboration. Developing software that enables a concerted effort from many investigators poses technical and sociological challenges. Meeting those challenges will accelerate the discovery of principles that govern movement control and improve treatments for individuals with movement pathologies.
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            Central programming of postural movements: adaptation to altered support-surface configurations.

            We studied the extent to which automatic postural actions in standing human subjects are organized by a limited repertoire of central motor programs. Subjects stood on support surfaces of various lengths, which forced them to adopt different postural movement strategies to compensate for the same external perturbations. We assessed whether a continuum or a limited set of muscle activation patterns was used to produce different movement patterns and the extent to which movement patterns were influenced by prior experience. Exposing subjects standing on a normal support surface to brief forward and backward horizontal surface perturbations elicited relatively stereotyped patterns of leg and trunk muscle activation with 73- to 110-ms latencies. Activity began in the ankle joint muscles and then radiated in sequence to thigh and then trunk muscles on the same dorsal or ventral aspect of the body. This activation pattern exerted compensatory torques about the ankle joints, which restored equilibrium by moving the body center of mass forward or backward. This pattern has been termed the ankle strategy because it restores equilibrium by moving the body primarily around the ankle joints. To successfully maintain balance while standing on a support surface short in relation to foot length, subjects activated leg and trunk muscles at similar latencies but organized the activity differently. The trunk and thigh muscles antagonistic to those used in the ankle strategy were activated in the opposite proximal-to-distal sequence, whereas the ankle muscles were generally unresponsive. This activation pattern produced a compensatory horizontal shear force against the support surface but little, if any, ankle torque. This pattern has been termed the hip strategy, because the resulting motion is focused primarily about the hip joints. Exposing subjects to horizontal surface perturbations while standing on support surfaces intermediate in length between the shortest and longest elicited more complex postural movements and associated muscle activation patterns that resembled ankle and hip strategies combined in different temporal relations. These complex postural movements were executed with combinations of torque and horizontal shear forces and motions of ankle and hip joints. During the first 5-20 practice trials immediately following changes from one support surface length to another, response latencies were unchanged. The activation patterns, however, were complex and resembled the patterns observed during well-practiced stance on surfaces of intermediate lengths.(ABSTRACT TRUNCATED AT 400 WORDS)
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              Postural orientation and equilibrium: what do we need to know about neural control of balance to prevent falls?

              Postural control is no longer considered simply a summation of static reflexes but, rather, a complex skill based on the interaction of dynamic sensorimotor processes. The two main functional goals of postural behaviour are postural orientation and postural equilibrium. Postural orientation involves the active alignment of the trunk and head with respect to gravity, support surfaces, the visual surround and internal references. Sensory information from somatosensory, vestibular and visual systems is integrated, and the relative weights placed on each of these inputs are dependent on the goals of the movement task and the environmental context. Postural equilibrium involves the coordination of movement strategies to stabilise the centre of body mass during both self-initiated and externally triggered disturbances of stability. The specific response strategy selected depends not only on the characteristics of the external postural displacement but also on the individual's expectations, goals and prior experience. Anticipatory postural adjustments, prior to voluntary limb movement, serve to maintain postural stability by compensating for destabilising forces associated with moving a limb. The amount of cognitive processing required for postural control depends both on the complexity of the postural task and on the capability of the subject's postural control system. The control of posture involves many different underlying physiological systems that can be affected by pathology or sub-clinical constraints. Damage to any of the underlying systems will result in different, context-specific instabilities. The effective rehabilitation of balance to improve mobility and to prevent falls requires a better understanding of the multiple mechanisms underlying postural control.
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                Author and article information

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                Journal
                Science Robotics
                Sci. Robot.
                American Association for the Advancement of Science (AAAS)
                2470-9476
                February 22 2023
                February 22 2023
                : 8
                : 75
                Affiliations
                [1 ]Department of Kinesiology and Health Education, University of Texas at Austin, Austin, TX, USA.
                [2 ]Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA.
                [3 ]Department of Physical Therapy and Rehabilitation Science, Northeastern University, Boston, MA, USA.
                [4 ]Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA.
                [5 ]Department of Rehabilitation Medicine, Division of Physical Therapy, Emory University, Atlanta, GA, USA.
                [6 ]George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
                [7 ]School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA.
                Article
                10.1126/scirobotics.adf1080
                36791215
                0da4fde4-70d9-47f4-83cd-a27bbc302cc8
                © 2023
                History

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