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      Human-Human Hand Interactions Aid Balance During Walking by Haptic Communication

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          Abstract

          Principles from human-human physical interaction may be necessary to design more intuitive and seamless robotic devices to aid human movement. Previous studies have shown that light touch can aid balance and that haptic communication can improve performance of physical tasks, but the effects of touch between two humans on walking balance has not been previously characterized. This study examines physical interaction between two persons when one person aids another in performing a beam-walking task. 12 pairs of healthy young adults held a force sensor with one hand while one person walked on a narrow balance beam (2 cm wide x 3.7 m long) and the other person walked overground by their side. We compare balance performance during partnered vs. solo beam-walking to examine the effects of haptic interaction, and we compare hand interaction mechanics during partnered beam-walking vs. overground walking to examine how the interaction aided balance. While holding the hand of a partner, participants were able to walk further on the beam without falling, reduce lateral sway, and decrease angular momentum in the frontal plane. We measured small hand force magnitudes (mean of 2.2 N laterally and 3.4 N vertically) that created opposing torque components about the beam axis and calculated the interaction torque, the overlapping opposing torque that does not contribute to motion of the beam-walker’s body. We found higher interaction torque magnitudes during partnered beam-walking vs. partnered overground walking, and correlation between interaction torque magnitude and reductions in lateral sway. To gain insight into feasible controller designs to emulate human-human physical interactions for aiding walking balance, we modeled the relationship between each torque component and motion of the beam-walker’s body as a mass-spring-damper system. Our model results show opposite types of mechanical elements (active vs. passive) for the two torque components. Our results demonstrate that hand interactions aid balance during partnered beam-walking by creating opposing torques that primarily serve haptic communication, and our model of the torques suggest control parameters for implementing human-human balance aid in human-robot interactions.

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          Most cited references56

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          Loss of balance during balance beam walking elicits a multifocal theta band electrocortical response.

          Determining the neural correlates of loss of balance during walking could lead to improved clinical assessment and treatment for individuals predisposed to falls. We used high-density electroencephalography (EEG) combined with independent component analysis (ICA) to study loss of balance during human walking. We examined 26 healthy young subjects performing heel-to-toe walking on a treadmill-mounted balance beam as well as walking on the treadmill belt (both at 0.22 m/s). ICA identified clusters of electrocortical EEG sources located in or near anterior cingulate, anterior parietal, superior dorsolateral-prefrontal, and medial sensorimotor cortex that exhibited significantly larger mean spectral power in the theta band (4-7 Hz) during walking on the balance beam compared with treadmill walking. Left and right sensorimotor cortex clusters produced significantly less power in the beta band (12-30 Hz) during walking on the balance beam compared with treadmill walking. For each source cluster, we also computed a normalized mean time/frequency spectrogram time locked to the gait cycle during loss of balance (i.e., when subjects stepped off the balance beam). All clusters except the medial sensorimotor cluster exhibited a transient increase in theta band power during loss of balance. Cluster spectrograms demonstrated that the first electrocortical indication of impending loss of balance occurred in the left sensorimotor cortex at the transition from single support to double support prior to stepping off the beam. These findings provide new insight into the neural correlates of walking balance control and could aid future studies on elderly individuals and others with balance impairments.
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            Two is better than one: Physical interactions improve motor performance in humans

            How do physical interactions with others change our own motor behavior? Utilizing a novel motor learning paradigm in which the hands of two - individuals are physically connected without their conscious awareness, we investigated how the interaction forces from a partner adapt the motor behavior in physically interacting humans. We observed the motor adaptations during physical interactions to be mutually beneficial such that both the worse and better of the interacting partners improve motor performance during and after interactive practice. We show that these benefits cannot be explained by multi-sensory integration by an individual, but require physical interaction with a reactive partner. Furthermore, the benefits are determined by both the interacting partner's performance and similarity of the partner's behavior to one's own. Our results demonstrate the fundamental neural processes underlying human physical interactions and suggest advantages of interactive paradigms for sport-training and physical rehabilitation.
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              Fingertip contact influences human postural control

              Touch and pressure stimulation of the body surface can strongly influence apparent body orientation, as well as the maintenance of upright posture during quiet stance. In the present study, we investigated the relationship between postural sway and contact forces at the fingertip while subjects touched a rigid metal bar. Subjects were tested in the tandem Romberg stance with eyes open or closed under three conditions of fingertip contact: no contact, touch contact (< 0.98 N of force), and force contact (as much force as desired). Touch contact was as effective as force contact or sight of the surroundings in reducing postural sway when compared to the no contact, eyes closed condition. Body sway and fingertip forces were essentially in phase with force contact, suggesting that fingertip contact forces are physically counteracting body sway. Time delays between body sway and fingertip forces were much larger with light touch contact, suggesting that the fingertip is providing information that allows anticipatory innervation of musculature to reduce body sway. The results are related to observations on precision grip as well as the somatosensory, proprioceptive, and motor mechanisms involved in the reduction of body sway.
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                Author and article information

                Contributors
                Journal
                Front Robot AI
                Front Robot AI
                Front. Robot. AI
                Frontiers in Robotics and AI
                Frontiers Media S.A.
                2296-9144
                04 November 2021
                2021
                : 8
                : 735575
                Affiliations
                [ 1 ]The Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States
                [ 2 ]School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
                [ 3 ]Mechanical and Aerospace Engineering, Missouri University of Science and Technology, Rolla, MO, United States
                [ 4 ]Department of Rehabilitation Medicine, Division of Physical Therapy, Emory University School of Medicine, Atlanta, GA, United States
                Author notes

                Edited by: Tapomayukh Bhattacharjee, Cornell University, United States

                Reviewed by: Marc Daniel Killpack, Brigham Young University, United States

                Cara Welker, University of Michigan, United States

                *Correspondence: Mengnan Wu, mengnan.wu@ 123456emory.edu

                This article was submitted to Human-Robot Interaction, a section of the journal Frontiers in Robotics and AI

                Article
                735575
                10.3389/frobt.2021.735575
                8599825
                34805289
                9afd9287-201e-4c7e-8dd5-05efaf058c8e
                Copyright © 2021 Wu, Drnach, Bong, Song and Ting.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 02 July 2021
                : 20 October 2021
                Categories
                Robotics and AI
                Original Research

                haptic communication,walking balance,beam-walking,walking aid,balance assistance,human-human interaction,human-robot interaction,physical interaction

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