Who's Leading This Dance?: Theorizing Automatic and Strategic Synchrony in Human-Exoskeleton Interactions

Evaluating the Performance of Joint Angle Estimation Algorithms on an Exoskeleton Mock-Up via a Modular Testing Approach

A common challenge for exoskeleton control is discerning operator intent to provide seamless actuation of the device with the operator. One way to accomplish this is with joint angle estimation algorithms and multiple sensors on the human-machine system. However, the question remains of what can be accomplished with just one sensor. The objective of this study was to deploy a modular testing approach to test the performance of two joint angle estimation models-a kinematic extrapolation algorithm and a Random Forest machine learning algorithm-when each was informed solely with kinematic gait data from a single potentiometer on an ankle exoskeleton mock-up. This study demonstrates (i) the feasibility of implementing a modular approach to exoskeleton mock-up evaluation to promote continuity between testing configurations and (ii) that a Random Forest algorithm yielded lower realized errors of estimated joint angles and a decreased actuation time than the kinematic model when deployed on the physical device.

Sensemaking, adaptation and agency in human-exoskeleton synchrony

Introduction: Wearable I robots such as exoskeletons combine the strength and precision of intelligent machines with the adaptability and creativity of human beings. Exoskeletons are unique in that humans interact with the technologies on both a physical and cognitive level, and as such, involve a complex, interdependent relationship between humans and robots. The aim of this paper was to explore the concepts of agency and adaptation as they relate to human-machine synchrony, as human users learned to operate a complex whole-body powered exoskeleton. Methods: Qualitative interviews were conducted with participants over multiple sessions in which they performed a range of basic functional tasks and simulated industrial tasks using a powered exoskeleton prototype, to understand their expectations of the human-technology partnership, any challenges that arose in their interaction with the device, and what strategies they used to resolve such challenges. Results: Analysis of the data revealed two overarching themes: 1) Participants faced physical, cognitive, and affective challenges to synchronizing with the exoskeleton; and 2) they engaged in sensemaking strategies such as drawing analogies with known prior experiences and anthropomorphized the exoskeleton as a partner entity in order to adapt and address challenges. Discussion: This research is an important first step to understanding how humans make sense of and adapt to a powerful and complex wearable robot with which they must synchronize in order to perform tasks. Implications for our understanding of human and machine agency as well as bidirectional coadaptation principles are discussed.

Passive Exoskeleton with Gait-Based Knee Joint Support for Individuals with Cerebral Palsy

Cerebral palsy is a neurological disorder with a variety of symptoms that can affect muscle coordination and movement. Crouch gait is one such symptom that is defined as excessive knee flexion accompanied by a crouched posture. This paper introduces a passive exoskeleton to support the knee joint during stance of individuals with cerebral palsy that are affected by crouch gait. The exoskeleton utilizes a hydraulic disc brake mechanism that is actuated only by the body weight and gait of the wearer to provide a braking torque at the knee joint. This passive, gait-based control method aims to offer a compact, lightweight, and simple alternative to existing exoskeletons. Preliminary experiments were conducted to verify the mechanics, safety, and braking capabilities of the device with healthy participants. A pilot study with an individual with cerebral palsy was then conducted. The individual with cerebral palsy showed a reduction in hip joint angle when using the device (18.8∘ and 21.7∘ for left and right sides, respectively). The muscle co-activation index was also reduced from 0.48 to 0.24 on the right side and from 0.17 to 0.017 on the left side. However, changes such as activation timing and device training need to be improved to better support the user.

Resonance as a Design Strategy for AI and Social Robots

Resonance, a powerful and pervasive phenomenon, appears to play a major role in human interactions. This article investigates the relationship between the physical mechanism of resonance and the human experience of resonance, and considers possibilities for enhancing the experience of resonance within human-robot interactions. We first introduce resonance as a widespread cultural and scientific metaphor. Then, we review the nature of "sympathetic resonance" as a physical mechanism. Following this introduction, the remainder of the article is organized in two parts. In part one, we review the role of resonance (including synchronization and rhythmic entrainment) in human cognition and social interactions. Then, in part two, we review resonance-related phenomena in robotics and artificial intelligence (AI). These two reviews serve as ground for the introduction of a design strategy and combinatorial design space for shaping resonant interactions with robots and AI. We conclude by posing hypotheses and research questions for future empirical studies and discuss a range of ethical and aesthetic issues associated with resonance in human-robot interactions.