Pilot Testing of a New Questionnaire for the Assessment of User Experience During Exoskeleton-Assisted Walking

Pisotta, Iolanda; Tagliamonte, Nevio Luigi; Bigioni, A.; Tamburella, Federica; Lorusso, Matteo; Bentivoglio, F.; Pecoraro, Ilaria; Argentieri, P.; Marri, F.; Zollo, Loredana; Molinari, Marco

doi:10.1007/978-3-030-70316-5_32

Cited by 5 publications

(11 citation statements)

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“…EXPERIENCE and PEPATO protocols were used to compare the effects on human–exoskeleton interaction, as well as user perception, of the different control strategies described in Section 2.3 . The EXPERIENCE protocol [ 36 , 37 ] aims at providing a benchmarking methodology for measuring both the user’s subjective perspective of the use of the exoskeleton by a newly developed multi-factor questionnaire and also to derive psycho-physiological indicators based on physiological data gathered during an exoskeleton-assisted walking test. EXPERIENCE testbed requires measuring ECG, GSR and the BR while walking.…”

Section: Methodsmentioning

confidence: 99%

“…In this work, we are therefore users of EUROBENCH’s project results. As shown in detail in Section 2 , we designed our experimental protocol with the two testbeds most suitable for our objective, which are the EXPERIENCE [ 36 , 37 ] and PEPATO [ 38 ] testbeds: the EXPERIENCE testbed aims at evaluating the user’s physiological response and subjective experience during exoskeleton-assisted walking on a treadmill, while the PEPATO testbed aims at analyzing muscle coordination during exoskeleton-assisted gait. More details are provided in Section 2 .…”

Section: Introductionmentioning

confidence: 99%

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Benchmarking the Effects on Human–Exoskeleton Interaction of Trajectory, Admittance and EMG-Triggered Exoskeleton Movement Control

Rodrigues-Carvalho

Fernández-García

Pinto-Fernández

et al. 2023

Sensors

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Nowadays, robotic technology for gait training is becoming a common tool in rehabilitation hospitals. However, its effectiveness is still controversial. Traditional control strategies do not adequately integrate human intention and interaction and little is known regarding the impact of exoskeleton control strategies on muscle coordination, physical effort, and user acceptance. In this article, we benchmarked three types of exoskeleton control strategies in a sample of seven healthy volunteers: trajectory assistance (TC), compliant assistance (AC), and compliant assistance with EMG-Onset stepping control (OC), which allows the user to decide when to take a step during the walking cycle. This exploratory study was conducted within the EUROBENCH project facility. Experimental procedures and data analysis were conducted following EUROBENCH’s protocols. Specifically, exoskeleton kinematics, muscle activation, heart and breathing rates, skin conductance, as well as user-perceived effort were analyzed. Our results show that the OC controller showed robust performance in detecting stepping intention even using a corrupt EMG acquisition channel. The AC and OC controllers resulted in similar kinematic alterations compared to the TC controller. Muscle synergies remained similar to the synergies found in the literature, although some changes in muscle contribution were found, as well as an overall increase in agonist-antagonist co-contraction. The OC condition led to the decreased mean duration of activation of synergies. These differences were not reflected in the overall physiological impact of walking or subjective perception. We conclude that, although the AC and OC walking conditions allowed the users to modulate their walking pattern, the application of these two controllers did not translate into significant changes in the overall physiological cost of walking nor the perceived experience of use. Nonetheless, results suggest that both AC and OC controllers are potentially interesting approaches that can be explored as gait rehabilitation tools. Furthermore, the INTENTION project is, to our knowledge, the first study to benchmark the effects on human–exoskeleton interaction of three different exoskeleton controllers, including a new EMG-based controller designed by us and never tested in previous studies, which has made it possible to provide valuable third-party feedback on the use of the EUROBENCH facility and testbed, enriching the apprenticeship of the project consortium and contributing to the scientific community.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Benchmarking the Effects on Human–Exoskeleton Interaction of Trajectory, Admittance and EMG-Triggered Exoskeleton Movement Control

Rodrigues-Carvalho

Fernández-García

Pinto-Fernández

et al. 2023

Sensors

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“…The second set of testing protocols entails perturbing users while wearing the device and measuring its recovery from those perturbations. Both settings are complemented with questionnaires aimed at measuring their mental stress and heart acceleration (Pisotta et al, 2021b).…”

Section: Generating Evidence-based Knowledge To Improve Exoskeleton F...mentioning

confidence: 99%

“…These factors measure, among other things, whether users felt safe and in control of their bodies while using the exoskeleton. Each item is assessed based on a 7-point Likert-type scale, where one means "I strongly disagree" and seven means "I strongly agree" (Pisotta et al, 2021a;Tagliamonte et al, 2021). It also includes a consistency scale that assesses the user's reliability when responding to similar questions (Pisotta et al, 2021a;Tagliamonte et al, 2021).…”

Section: E20-6mentioning

confidence: 99%

“…These, in turn, have input the subject’s galvanic skin response, heart, and respiration rate, and heart rate variability (Tagliamonte et al, 2021). The remaining performance indicators—namely, Perceptibility, Acceptability, Functionality, and Usability—are measured based on a multifactor questionnaire piloted within the EUROBENCH consortium (Pisotta et al, 2021b; Tagliamonte et al, 2021). The questionnaire includes four factors—Perceptibility, Acceptability, Functionality, and Usability—and different subfactors within each of them.…”

Section: Generating Evidence-based Knowledge To Improve Exoskeleton F...mentioning

confidence: 99%

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Harnessing robot experimentation to optimize the regulatory framing of emerging robot technologies

2022

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From exoskeletons to lightweight robotic suits, wearable robots are changing dynamically and rapidly, challenging the timeliness of laws and regulatory standards that were not prepared for robots that would help wheelchair users walk again. In this context, equipping regulators with technical knowledge on technologies could solve information asymmetries among developers and policymakers and avoid the problem of regulatory disconnection. This article introduces pushing robot development for lawmaking (PROPELLING), an financial support to third parties from the Horizon 2020 EUROBENCH project that explores how robot testing facilities could generate policy-relevant knowledge and support optimized regulations for robot technologies. With ISO 13482:2014 as a case study, PROPELLING investigates how robot testbeds could be used as data generators to improve the regulation for lower-limb exoskeletons. Specifically, the article discusses how robot testbeds could help regulators tackle hazards like fear of falling, instability in collisions, or define the safe scenarios for avoiding any adverse consequences generated by abrupt protective stops. The article’s central point is that testbeds offer a promising setting to bring policymakers closer to research and development to make policies more attuned to societal needs. In this way, these approximations can be harnessed to unravel an optimal regulatory framework for emerging technologies, such as robots and artificial intelligence, based on science and evidence.

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Multicriteria decision‐making–based framework for implementing DevOps practices: A fuzzy best–worst approach

Kumar,

Nadeem,

Shameem

2023

J Software Evolu Process

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Increasingly, software organizations are implementing DevOps culture to benefit from it in terms of continuous testing, delivery, improvement, and so forth. Implementing DevOps is difficult due to a lack of understanding about the practices and their effective application for its effective implementation. This paper aims to explore different DevOps practices that can be implemented in software organizations. The study involves conducting a systematic literature review (SLR) to identify DevOps implementation practices, followed by the utilization of the fuzzy best–worst method (FBWM) to establish a taxonomy or classification of software practices. We have used an SLR to investigate the practices, and subsequently, the survey method was followed to validate the identified practices. Moreover, the best–worst method (BWM) was considered to evaluate the significance and develop the taxonomy of the practices. The results of this study extracted 19 practices that have been identified in the SLR process. The identified factors are further classified into six core DevOps lifecycle phases. The results of the BWM approach are shown. The outcomes of the study conclude that the proposed taxonomy of the practices could help DevOps practitioners and researchers effectively implement them in software development organizations.

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Pilot Testing of a New Questionnaire for the Assessment of User Experience During Exoskeleton-Assisted Walking

Cited by 5 publications

References 4 publications

Benchmarking the Effects on Human–Exoskeleton Interaction of Trajectory, Admittance and EMG-Triggered Exoskeleton Movement Control

Benchmarking the Effects on Human–Exoskeleton Interaction of Trajectory, Admittance and EMG-Triggered Exoskeleton Movement Control

Harnessing robot experimentation to optimize the regulatory framing of emerging robot technologies

Multicriteria decision‐making–based framework for implementing DevOps practices: A fuzzy best–worst approach

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