Social robotic application to support active and healthy ageing

Cooper, Sara; Fava, Alessandro Di; Villacañas, Oscar; Silva, T.; Fernández-Carbajales, Víctor; Unzueta, Luis; Serras, Manex; Marchionni, Luca; Ferro, Francesco

doi:10.1109/ro-man50785.2021.9515432

Cited by 14 publications

(11 citation statements)

References 19 publications

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“…ADILIB is a built-in software for creating and developing digital voice assistants [ 45 , 46 ]. An ADILIB conversational agent is capable of understanding natural spoken language and generating a response.…”

Section: Resultsmentioning

confidence: 99%

DigiHEALTH: Suite of Digital Solutions for Long-Term Healthy and Active Aging

Martín

Amaya

Torres

et al. 2023

IJERPH

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The population in the world is aging dramatically, and therefore, the economic and social effort required to maintain the quality of life is being increased. Assistive technologies are progressively expanding and present great opportunities; however, given the sensitivity of health issues and the vulnerability of older adults, some considerations need to be considered. This paper presents DigiHEALTH, a suite of digital solutions for long-term healthy and active aging. It is the result of a fruitful trajectory of research in healthy aging where we have understood stakeholders’ needs, defined the main suite properties (that would allow scalability and interoperability with health services), and codesigned a set of digital solutions by applying a continuous reflexive cycle. At the current stage of development, the digital suite presents eight digital solutions to carry out the following: (a) minimize digital barriers for older adults (authentication system based on face recognition and digital voice assistant), (b) facilitate active and healthy living (well-being assessment module, recommendation system, and personalized nutritional system), and (c) mitigate specific impairments (heart failure decompensation, mobility assessment and correction, and orofacial gesture trainer). The suite is available online and it includes specific details in terms of technology readiness level and specific conditions for usage and acquisition. This live website will be continually updated and enriched with more digital solutions and further experiences of collaboration.

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Section: Resultsmentioning

confidence: 99%

DigiHEALTH: Suite of Digital Solutions for Long-Term Healthy and Active Aging

Martín

Amaya

Torres

et al. 2023

IJERPH

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“…56,57 SARs with touchscreens include Casper to provide meal assistance instructions and offer recipe choices, 36 Stevie for voice/video calling, 44 and Pearl to add upcoming appointments to its calendar. 49 Furthermore, Pepper, 37 Kompai, 51 Max, 52 Hobbit, 48 Mini, 47 and ARI 62 all display cognitive games on their touchscreens, which is especially valuable for older adults where comprehension speeds will vary. 31 Display height is typically targeted to accommodate older adults in a seated position, some displays may be tilted to improve accessibility when standing.…”

Section: Design Featuresmentioning

confidence: 99%

“…Mini 47 and Stevie 44 have gaze direction, facial expressions using animated eyes, and head and whole-body movements. Other robots including Brian 2.1, 38 Milo R25, 40 Pepper, 61 Casper, 36 ARI, 43 Bandit, 45 NAO, 46 Tangy, 56 and Baxter 58 use all four types of visual expression for a variety of tasks such as exercise 45 and games 62 to promote user engagement. 21…”

Section: Design Featuresmentioning

confidence: 99%

An analysis of design recommendations for socially assistive robot helpers for effective human-robot interactions in senior care

Robinson

Nejat

2022

Journal of Rehabilitation and Assistive Technologies Engineerin

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As the global population ages, there is an increase in demand for assistive technologies that can alleviate the stresses on healthcare systems. The growing field of socially assistive robotics (SARs) offers unique solutions that are interactive, engaging, and adaptable to different users’ needs. Crucial to having positive human-robot interaction (HRI) experiences in senior care settings is the overall design of the robot, considering the unique challenges and opportunities that come with novice users. This paper presents a novel study that explores the effect of SAR design on HRI in senior care through a results-oriented analysis of the literature. We provide key design recommendations to ensure inclusion for a diverse set of users. Open challenges of considering user preferences during design, creating adaptive behaviors, and developing intelligent autonomy are discussed in detail. SAR features of appearance and interaction mode along with SAR frameworks for perception and intelligence are explored to evaluate individual developments using metrics such as trust, acceptance, and intent to use. Drawing from a diverse set of features, SAR frameworks, and HRI studies, the discussion highlights robot characteristics of greatest influence in promoting wellbeing and aging-in-place of older adults and generates design recommendations that are important for future development.

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“…[4] ARI robot developed by PAL Robotics can recognize the "fall" of the elderly through neural networks trained by the movement vectors. [5] The following survey mainly focuses on the existing action recognition methods applied to robots. Liu et al [6] proposed an action recognition scheme based on probabilistic soft assignment for home service robots, which uses the Gaussian mixture model to improve the recognition accuracy of similar actions.…”

Section: Introductionmentioning

confidence: 99%

“…[ 4 ] ARI robot developed by PAL Robotics can recognize the “fall” of the elderly through neural networks trained by the movement vectors. [ 5 ]…”

Section: Introductionmentioning

confidence: 99%

Skeleton‐Guided Action Recognition with Multistream 3D Convolutional Neural Network for Elderly‐Care Robot

Zhang,

Zhou

2023

Advanced Intelligent Systems

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With the arrival of a global aging society, elderly‐care robots are becoming more and more attractive and can provide better caring services through action recognition. This article presents a skeleton‐guided action recognition framework with multistream 3D convolutional neural network. Two parallel dual‐stream lightweight networks are proposed to enhance the feature extraction ability of human action and meanwhile reduce computation. Two different modes of skeleton input video are constructed to improve the recognition accuracy by decision fusion. The backbone networks adopt Resnet‐18, the feature fusion layer and sliding window mechanism are both designed, and two cross‐entropy losses are used to supervise their training. A dataset (named elder care action recognition (EC‐AR)) with different categories of action is built. The experimental results on HMDB‐51 and EC‐AR datasets both demonstrate that the proposed framework outperforms the existing methods. The developed method is also applied to a prototype of elderly‐care robots, and the test results in home scenarios show that it still has high recognition accuracy and good real‐time performance.

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Social robotic application to support active and healthy ageing

Cited by 14 publications

References 19 publications

DigiHEALTH: Suite of Digital Solutions for Long-Term Healthy and Active Aging

DigiHEALTH: Suite of Digital Solutions for Long-Term Healthy and Active Aging

An analysis of design recommendations for socially assistive robot helpers for effective human-robot interactions in senior care

Skeleton‐Guided Action Recognition with Multistream 3D Convolutional Neural Network for Elderly‐Care Robot

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