scholarly journals Wearable Biofeedback Improves Human-Robot Compliance during Ankle-Foot Exoskeleton-Assisted Gait Training: A Pre-Post Controlled Study in Healthy Participants

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5876
Author(s):  
Cristiana Pinheiro ◽  
Joana Figueiredo ◽  
Nuno Magalhães ◽  
Cristina P. Santos
Keyword(s):  
Group Performance ◽  
Gait Training ◽  
User Participation ◽  
Human Robot Interaction ◽  
Controlled Study ◽  
P Value ◽  
Joint Motion ◽  
Robot Interaction ◽  
Post Stroke ◽  
Healthy Participants

The adjunctive use of biofeedback systems with exoskeletons may accelerate post-stroke gait rehabilitation. Wearable patient-oriented human-robot interaction-based biofeedback is proposed to improve patient-exoskeleton compliance regarding the interaction torque’s direction (joint motion strategy) and magnitude (user participation strategy) through auditory and vibrotactile cues during assisted gait training, respectively. Parallel physiotherapist-oriented strategies are also proposed such that physiotherapists can follow in real-time a patient’s motor performance towards effective involvement during training. A preliminary pre-post controlled study was conducted with eight healthy participants to conclude about the biofeedback’s efficacy during gait training driven by an ankle-foot exoskeleton and guided by a technical person. For the study group, performance related to the interaction torque’s direction increased during (p-value = 0.07) and after (p-value = 0.07) joint motion training. Further, the performance regarding the interaction torque’s magnitude significantly increased during (p-value = 0.03) and after (p-value = 68.59 × 10−3) user participation training. The experimental group and a technical person reported promising usability of the biofeedback and highlighted the importance of the timely cues from physiotherapist-oriented strategies. Less significant improvements in patient–exoskeleton compliance were observed in the control group. The overall findings suggest that the proposed biofeedback was able to improve the participant-exoskeleton compliance by enhancing human-robot interaction; thus, it may be a powerful tool to accelerate post-stroke ankle-foot deformity recovery.

Mechanical Design and Evaluation of a Novel Knee-Ankle-Foot Robot for Rehabilitation

2015 ◽  
Author(s):  
Gong Chen ◽  
Zhao Guo ◽  
Haoyong Yu
Keyword(s):  
Mechanical Design ◽  
Gait Training ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Gait Patterns ◽  
Gait Biomechanics ◽  
Leg Muscles ◽  
In Series ◽  
Translational Spring ◽  
Selection Of

This paper presents the mechanical design and evaluation of a knee-ankle-foot robot, which is compact, modular, and portable for stroke patients to carry out overground gait training at outpatient and home settings. The robot is driven by a novel series elastic actuator (SEA) for safe human-robot interaction. The SEA employs one soft translational spring in series with a stiff torsion spring to achieve high intrinsic compliance and the capacity of providing peak force. The robotic joint mechanism and the selection of the actuator springs are optimized based on gait biomechanics to achieve portability and capability. The robot demonstrated stable and accuracy force control in experiments conducted on healthy subjects with overground walking. Major leg muscles of the subjects showed reduced level of activations (Electromyography, EMG) while maintaining normal gait patterns with robotic assistances, indicating the robot’s capability of providing effective gait assistance.

scholarly journals Design of a pressure sensitive matrix for analyzing direct haptic patient-therapist interaction in motor rehabilitation after stroke

2017 ◽  
Vol 3 (1) ◽  
pp. 57-61
Author(s):  
Michael Pust ◽  
Ekaterina Ivanova ◽  
Henning Schmidt ◽  
Jörg Krüger
Keyword(s):  
Human Robot Interaction ◽  
Hand Position ◽  
Motor Rehabilitation ◽  
Therapeutic Approaches ◽  
Haptic Interaction ◽  
Robot Interaction ◽  
Pressure Sensitive ◽  
The Matrix ◽  
Textile Sensor ◽  
Healthy Participants

Abstract:Robot based therapy is one of the prevalent therapeutic approaches in motor stroke rehabilitation. It is often used in hospitals in combination with conventional therapy. In order to optimize human-robot interaction, we aim to investigate how a therapist physically supports patients during motor training of the upper extremities. This paper presents the design of a flexible textile sensor matrix, which measures the pressure exerted between therapist and patient during direct haptic interaction as well as the hand position and orientation in space. The matrix contains 144 sensors which enables measuring pressure intensity and localization of areas where the pressure is applied. The measurement matrix was evaluated with four healthy participants.

scholarly journals Design and Control of a Lower Limb Exoskeleton for Robot-Assisted Gait Training

2009 ◽  
Vol 6 (2) ◽  
pp. 229-243 ◽  
Author(s):  
Pieter Beyl ◽  
Michaël Van Damme ◽  
Ronald Van Ham ◽  
Bram Vanderborght ◽  
Dirk Lefeber
Keyword(s):  
Sliding Mode ◽  
Gait Training ◽  
Human Robot Interaction ◽  
Normal Operation ◽  
Artificial Muscles ◽  
Robot Assisted ◽  
Robot Interaction ◽  
Position Errors ◽  
Pneumatic Artificial Muscles ◽  
And Control

Robot-assisted rehabilitation of gait still faces many challenges, one of which is improving physical human-robot interaction. The use of pleated pneumatic artificial muscles to power a step rehabilitation robot has the potential to meet this challenge. This paper reports on the development of a gait rehabilitation exoskeleton with a knee joint powered by pleated pneumatic artificial muscles. It is intended as a platform for the evaluation of design and control concepts in view of improved physical human-robot interaction. The design was focused on the optimal dimensioning of the actuator configuration. Safety being the most important prerequisite, a proxy-based sliding mode controller (PSMC) was implemented as it combines accurate tracking during normal operation with a smooth, slow and safe recovery from large position errors. Treadmill walking experiments of a healthy subject wearing the powered exoskeleton show the potential of PSMC as a safe robot-in-charge control strategy for robot-assisted gait training.

Workload in Human-Robot Interaction: A Review of Manipulations and Outcomes

2009 ◽  
Author(s):  
Matthew S. Prewett ◽  
Kristin N. Saboe ◽  
Ryan C. Johnson ◽  
Michael D. Coovert ◽  
Linda R. Elliott
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction

Biomimetic, sociable robots for human-robot interaction

2010 ◽  
Author(s):  
Eleanore Edson ◽  
Judith Lytle ◽  
Thomas McKenna
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction

The role and relationship of mindreading and social attunement in HRI – position statements of interdisciplinary researchers. Workshop HRI'20

2020 ◽  
Author(s):  
Agnieszka Wykowska ◽  
Jairo Pérez-Osorio ◽  
Stefan Kopp
Keyword(s):  
Mental States ◽  
Human Robot Interaction ◽  
Human Interaction ◽  
Artificial Agents ◽  
The Novel ◽  
Robot Interaction ◽  
Novel Coronavirus ◽  
Relationship Of ◽  
The Relationship

This booklet is a collection of the position statements accepted for the HRI’20 conference workshop “Social Cognition for HRI: Exploring the relationship between mindreading and social attunement in human-robot interaction” (Wykowska, Perez-Osorio & Kopp, 2020). Unfortunately, due to the rapid unfolding of the novel coronavirus at the beginning of the present year, the conference and consequently our workshop, were canceled. On the light of these events, we decided to put together the positions statements accepted for the workshop. The contributions collected in these pages highlight the role of attribution of mental states to artificial agents in human-robot interaction, and precisely the quality and presence of social attunement mechanisms that are known to make human interaction smooth, efficient, and robust. These papers also accentuate the importance of the multidisciplinary approach to advance the understanding of the factors and the consequences of social interactions with artificial agents.

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