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Daniel P. Ferris and Bryan R. Schlink

Robotic exoskeletons and bionic prostheses have moved from science fiction to science reality in the last decade. These robotic devices for assisting human movement are now technically feasible given recent advancements in robotic actuators, sensors, and computer processors. However, despite the ability to build robotic hardware that is wearable by humans, we still do not have optimal controllers to allow humans to move with coordination and grace in synergy with the robotic devices. We consider the history of robotic exoskeletons and bionic limb prostheses to provide a better assessment of the roadblocks that have been overcome and to gauge the roadblocks that still remain. There is a strong need for kinesiologists to work with engineers to better assess the performance of robotic movement assistance devices. In addition, the identification of new performance metrics that can objectively assess multiple dimensions of human performance with robotic exoskeletons and bionic prostheses would aid in moving the field forward. We discuss potential control approaches for these robotic devices, with a preference for incorporating feedforward neural signals from human users to provide a wider repertoire of discrete and adaptive rhythmic movements.

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Mhairi K. MacLean and Daniel P. Ferris

One goal for developing robotic lower limb exoskeletons is human performance augmentation. Robotic exoskeletons that can enhance the performance of able-bodied humans serving as firefighters, military personnel, and/or construction workers could reduce injuries and improve worker efficiency. To be

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Stephen R. Bested, Gerome A. Manson, and Luc Tremblay

.g., a putt). Physical guidance has been defined as, the act of “moving or being moved into a new position or location” ( Hodges & Campagnaro, 2012 , p. 179). More recently, physical guidance has been administered with the use of robotic devices. These robotic devices allow participants to be guided through

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Richard E. Debski, Shon P. Darcy, and Savio L-Y. Woo

Quantitative data on the mechanics of diarthrodial joints and the function of ligaments are needed to better understand injury mechanisms, improve surgical procedures, and develop improved rehabilitation protocols. Therefore, experimental and computational approaches have been developed to determine joint kinematics and the in-situ forces in ligaments and their replacement grafts using human cadaveric knee and shoulder joints. A robotic/universal force-moment sensor testing system is used in our research center for the evaluation of a wide variety of external loading conditions to study the function of ligaments and their replacements; it has the potential to reproduce in-vivo joint motions in a cadaver knee. Two types of computational models have also been developed: a rigid body spring model and a displacement controlled spring model. These computational models are designed to complement and enhance experimental studies so that more complex loading conditions can be examined and the stresses and strains in the soft tissues can be calculated. In the future, this combined approach will improve our understanding of these joints and soft tissues during in-vivo activities and serve as a tool to aid surgical planning and development of rehabilitation protocols.

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Margaret A. Finley, Laura Dipietro, Jill Ohlhoff, Jill Whitall, Hermano I. Krebs, and Christopher T. Bever

We are expanding the use of the MIT-MANUS robotics to persons with impairments due exclusively to orthopedic disorders, with no neurological deficits. To understand the reliability of repeated measurements of the robotic tasks and the potential for registering changes due to learning is critical. Purposes of this study were to assess the learning effect of repeated exposure to robotic evaluations and to demonstrate the ability to detect a change in protocol in outcome measurements. Ten healthy, unimpaired subjects (mean age = 54.1 ± 6.4 years) performed six repeated evaluations consisting of unconstrained reaching movements to targets and circle drawing (with and without a visual template) on the MIT-MANUS. Reaching outcomes were aiming error, mean and peak speed, movement smoothness and duration. Outcomes for circle drawing were axis ratio metric and shoulder–elbow joint angles correlation metric (was based on a two-link model of the human arm and calculated hand path during the motions). Repeated-measures ANOVA (p ≤ .05) determined if difference existed between the sessions. Intraclass correlations (R) were calculated. All variables were reliable, without learning across testing sessions. Intraclass correlation values were good to high (reaching, R ≥ .80; circle drawing, R ≥ .90). Robotic measurement ability to differentiate between similar but distinct tasks was demonstrated as measured by axis ratio metric (p < .001) and joint correlation metric (p = .001). Outcome measures of the MIT-MANUS proved to be reliable yet sensitive to change in healthy adults without motor learning over the course of repeated measurements.

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Maninderjit Kaur, Timothy Gifford, Kerry L. Marsh, and Anjana Bhat


Coordination develops gradually over development with younger children showing more unstable coordination patterns compared to older children and adults. In addition, children with Autism Spectrum Disorders (ASDs) display significant coordination impairments. In the current study, we examined whether robot–child interactions could improve bilateral coordination skills of typically developing (TD) children and one child with ASD.


Fourteen TD children between four and seven years of age and an 11-year-old child with ASD performed dual-limb and multilimb actions within a solo and social context during a pre- and posttest. Between the pre- and posttests, eight training sessions were offered across four weeks during a robot imitation context involving karate and dance actions.


Younger TD children and the child with ASD improved their solo coordination whereas the older TD children increased their social coordination.


This preliminary study lacked a control group.


Robot–child interactions may facilitate bilateral coordination and could be a promising intervention tool for children with ASDs.

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Jonathan K. Holm, Jonas Contakos, Sang-Wook Lee, and John Jang

This study investigated the energetics of the human ankle during the stance phase of downhill walking with the goal of modeling ankle behavior with a passive spring and damper mechanism. Kinematic and kinetic data were collected on eight male participants while walking down a ramp with inclination varying from 0° to 8°. The ankle joint moment in the sagittal plane was calculated using inverse dynamics. Mechanical energy injected or dissipated at the ankle joint was computed by integrating the power across the duration of the stance phase. The net mechanical energy of the ankle was approximately zero for level walking and monotonically decreased (i.e., became increasingly negative) during downhill walking as the slope decreased. The indication is that the behavior of the ankle is energetically passive during downhill walking, playing a key role in dissipating energy from one step to the next. A passive mechanical model consisting of a pin joint coupled with a revolute spring and damper was fit to the ankle torque and its parameters were estimated for each downhill slope using linear regression. The passive model demonstrated good agreement with actual ankle dynamics as indicated by low root-mean-square error values. These results indicate the stance phase behavior of the human ankle during downhill walking may be effectively duplicated by a passive mechanism with appropriately selected spring and damping characteristics.

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David I. Anderson

these accomplishments, many aspects of motor development remain a mystery. Moreover, despite forging collaborations with researchers and clinicians in neuroscience, cognitive science, embryology, pediatrics, robotics, the learning sciences, and public health, motor development researchers are only

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Theresa C. Hauge, Garrett E. Katz, Gregory P. Davis, Kyle J. Jaquess, Matthew J. Reinhard, Michelle E. Costanzo, James A. Reggia, and Rodolphe J. Gentili

evaluating Veterans who suffer from an array of cognitive impairments ( McAndrew et al., 2016 ; Smith et al., 2009 ). Another potential application is the development of cognitive-motor robotic controllers able to execute action sequences to complete complex tasks such as the Tower of Hanoi and possibly