FriWalk robotic walker: usability, acceptance and UX evaluation after a pilot study in a real environment

Pérez‐Rodríguez, Rodrigo; Moreno-Sánchez, Pedro A.; Valdés-Aragonés, Myriam; Oviedo-Briones, Myriam; Divan, Stefano; Garcia-Grossocordon, Nuria; Rodríguez‐Mañas, Leocadio

doi:10.1080/17483107.2019.1617795

Cited by 7 publications

(16 citation statements)

References 18 publications

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“…As shown in Figure 3 , the majority of articles focusing on the most used questionnaires for evaluating the usability of robots and smart wearables were published in 2020 ( n = 11), 22 – 29 , 52 – 54 2021 ( n = 9), 1,0– 34 , 55 – 57 and 2022 ( n = 10), 35 – 41 , 58 – 60 respectively (More details in Table 2 ).…”

Section: Resultsmentioning

confidence: 99%

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The most used questionnaires for evaluating the usability of robots and smart wearables: A scoping review

Moulaei,

Bahaadinbeigy

2024

DIGITAL HEALTH

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Background As the field of robotics and smart wearables continues to advance rapidly, the evaluation of their usability becomes paramount. Researchers may encounter difficulty in finding a suitable questionnaire for evaluating the usability of robotics and smart wearables. Therefore, the aim of this study is to identify the most commonly utilized questionnaires for assessing the usability of robots and smart wearables. Methods A comprehensive search of databases, including PubMed, Web of Science, and Scopus, was conducted for this scoping review. Two authors performed the selection of articles and data extraction using a 10-field data extraction form. In cases of disagreements, a third author was consulted to reach a consensus. The inclusions were English-language original research articles that utilized validated questionnaires to assess the usability of healthcare robots and smart wearables. The exclusions comprised review articles, non-English publications, studies not focused on usability, those assessing clinical outcomes, articles lacking questionnaire details, and those using non-validated or researcher-made questionnaires. Descriptive statistics methods (frequency and percentage), were employed to analyze the data. Results A total of 314 articles were obtained, and after eliminating irrelevant and duplicate articles, a final selection of 50 articles was included in this review. A total of 17 questionnaires were identified to evaluate the usability of robots and smart wearables, with 10 questionnaires specifically for wearables and 7 questionnaires for robots. The System Usability Scale (50%) and Post-Study System Usability Questionnaire (19.44%) were the predominant questionnaires utilized to assess the usability of smart wearables. Moreover, the most commonly used questionnaires for evaluating the usability of robots were the System Usability Scale (56.66%), User Experience Questionnaire (16.66%), and Quebec User Evaluation of Satisfaction with Assistive Technology (10%). Conclusion Commonly employed questionnaires serve as valuable tools in assessing the usability of robots and smart wearables, aiding in the refinement and optimization of these technologies for enhanced user experiences. By incorporating user feedback and insights, designers can strive towards creating more intuitive and effective robotic and wearable solutions.

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Section: Resultsmentioning

confidence: 99%

“…The minimum and maximum intervention time for evaluating the usability of wearables was 5 minutes 19 and 2 years, 30 respectively. In addition, the minimum and maximum intervention time for evaluating the usability of robots was 5 minutes 61 and 6 months, 52 respectively.…”

Section: Resultsmentioning

confidence: 99%

The most used questionnaires for evaluating the usability of robots and smart wearables: A scoping review

Moulaei,

Bahaadinbeigy

2024

DIGITAL HEALTH

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“…Subsequently, the full texts of the remaining 43 papers underwent meticulous review. In the final analysis, 17 papers were considered suitable for data extraction [34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50] (Figure 1). original or customized questionnaire employed, and the digital health technology under assessment.…”

Section: Resultsmentioning

confidence: 99%

User Experience of Older People While Using Digital Health Technologies: A Systematic Review

Takano,

Maruyama,

Takahashi

et al. 2023

Applied Sciences

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Digital technologies ranging from biosensors to virtual reality have revolutionized the healthcare landscape by offering innovations that hold great promise in addressing the challenges posed by rapidly aging populations. To optimize healthcare experiences for older people, it is crucial to understand their user experience (UX) with digital health technologies. This systematic review, covering articles published from 2013 to 2023, aimed to explore frequently used questionnaires for assessing digital healthcare UX among older people. The inclusion criteria were original studies assessing UX in digital health for individuals aged ≥65 years. Of 184 articles identified, 17 were selected after rigorous screening. The questionnaires used included the System Usability Scale (SUS), the User Experience Questionnaire (UEQ), and the Post-Study System Usability Questionnaire. Customized questionnaires based on models such as the Technology Acceptance Model and the Almere model were developed in some studies. Owing to its simplicity and effectiveness in assessing digital health UX among older people, the SUS emerged as the go-to tool (52.9%). Combining the SUS with the UEQ provided comprehensive insights into UX. Specialized questionnaires were also used, but further research is needed to validate and adapt these tools for diverse cultural contexts and evolving technologies.

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“…Not many RCTs exist in the field of ICTs applied to frailty management, which prevents the availability of a wider number of works focused on assessing the usability of technologies for treating frail population [41]. Works analyzing usability-related aspects of technology during real interventions also report satisfactory results [67,68], however, since the design procedure followed is scarcely described, the sample size is significantly smaller than the one presented in this paper, and data related to adherence are not optimal (i.e., far from 100% adherence as reported in this paper), those results should be interpreted with caution. On the other hand, the majority of the research addressing how older persons interact with technology is done in controlled environments and under the supervision of domain experts [69][70][71][72][73].…”

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confidence: 99%

“…On the other hand, the majority of the research addressing how older persons interact with technology is done in controlled environments and under the supervision of domain experts [69][70][71][72][73]. Most of the published related research use standardized tools such as those used in this work, which is aligned with the methods followed in the current approach; moreover, despite the heterogeneous approaches in terms of the target application, ranging from rehabilitation [67][68][69] to exergames [70], monitoring cognitive impairment [71], fall risk [72], or evaluating available health apps [73], the used interaction instruments, including mobile devices [67,69,72,73], personal computers [68,71], or custom prototypes [70], and the diverse characteristics of the target population, that in some cases have a previous experience with the technology to be used [68] and in some others cannot use it without help [71], the UCD approach is a commonality backing almost all approaches from a methodological perspective.…”

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confidence: 99%

Usability, User Experience, and Acceptance Evaluation of CAPACITY: A Technological Ecosystem for Remote Follow-Up of Frailty

Pérez‐Rodríguez

Villalba-Mora

Valdés-Aragonés

et al. 2021

Sensors

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Frailty predisposes older persons to adverse events, and information and communication technologies can play a crucial role to prevent them. CAPACITY provides a means to remotely monitor variables with high predictive power for adverse events, enabling preventative personalized early interventions. This study aims at evaluating the usability, user experience, and acceptance of a novel mobile system to prevent disability. Usability was assessed using the system usability scale (SUS); user experience using the user experience questionnaire (UEQ); and acceptance with the technology acceptance model (TAM) and a customized quantitative questionnaire. Data were collected at baseline (recruitment), and after three and six months of use. Forty-six participants used CAPACITY for six months; nine dropped out, leaving a final sample of 37 subjects. SUS reached a maximum averaged value of 83.68 after six months of use; no statistically significant values have been found to demonstrate that usability improves with use, probably because of a ceiling effect. UEQ, obtained averages scores higher or very close to 2 in all categories. TAM reached a maximum of 51.54 points, showing an improvement trend. Results indicate the success of the participatory methodology, and support user centered design as a key methodology to design technologies for frail older persons. Involving potential end users and giving them voice during the design stage maximizes usability and acceptance.

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FriWalk robotic walker: usability, acceptance and UX evaluation after a pilot study in a real environment

Cited by 7 publications

References 18 publications

The most used questionnaires for evaluating the usability of robots and smart wearables: A scoping review

The most used questionnaires for evaluating the usability of robots and smart wearables: A scoping review

User Experience of Older People While Using Digital Health Technologies: A Systematic Review

Usability, User Experience, and Acceptance Evaluation of CAPACITY: A Technological Ecosystem for Remote Follow-Up of Frailty

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