The Robot ALIAS as a Database for Health Monitoring for Elderly People

Rehrl, Tobias; Geiger, Jürgen T.; Golcar, Maja; Gentsch, Stefan; Knobloch, Jan; Rigoll, Gerhard; Scheibl, Katharina; Schneider, Wolfram; Ihsen, Susanne; Wallhoff, Frank

doi:10.1007/978-3-642-37988-8_15

Cited by 9 publications

(5 citation statements)

References 7 publications

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“…Anna-Constantia [49], Zora [50], MOBISERV [51], PAMM [52][53], ALIAS [54], Robo Coach Xuan and Taizo [55], Robo MD [56], Florence [57], Flo [58], GiraffPlus [59], Cybi [60], Pearl [61].…”

Section: Companion and Service Combo Robotmentioning

confidence: 99%

A Review on Usability and User Experience of Assistive Social Robots for Older Persons

Isa¹,

Saptari²,

Perumal³

et al. 2022

IJIE

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In the advancement of human-robot interaction technology, assistive social robots have been recognized as one of potential technologies that can provide physical and cognitive supports in older person’s care. However, a major challenge faced by the designers is to develop an assistive social robot with prodigious usability and user experience for older persons who were known to have physical and cognitive limitations. A considerable number of published literatures was reporting on the technological design process of assistive social robots. However, only a small amount of attention has been paid to review the usability and user experience of the robots. The objective of this paper is to provide an overview of established researches in the literatures concerning usability and user experience issues faced by the older persons when interacting with assistive social robots. The authors searched relevant articles from the academic databases such as Google Scholar, Scopus and Web of Science as well as Google search engine for the publication period 2000 to 2021. Several search keywords were typed such as ‘older persons’ ‘elderly’, ‘senior citizens’, ‘assistive social robots’, ‘companion robots’, ‘personal robots’, ‘usability’ and ‘user experience’. This online search found a total of 215 articles which are related to assistive social robots in elderly care. Out of which, 54 articles identified as significant references, and they were examined thoroughly to prepare the main content of this paper. This paper reveals usability issues of 28 assistive social robots, and user experience feedback based on 41 units of assistive social robots. Based on the research articles scrutinized, the authors concluded that the key elements in the design and development of assistive social robots to improve acceptance of older persons were determined by three factors: functionality, usability and users’ experience. Functionality refers to ability of robots to serve the older persons. Usability is ease of use of the robots. It is an indicator on how successful of interaction between the robots and the users. To improve usability, robot designers should consider the limitations of older persons such as vision, hearing, and cognition capabilities when interactingwith the robots. User experience reflects to perceptions, preferences and behaviors of users that occur before, during and after use the robots. Combination of superior functionality and usability lead to a good user experiencein using the robots which in the end achieves satisfaction of older persons.

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“…Anna-Constantia [49], Zora [50], MOBISERV [51], PAMM [52][53], ALIAS [54], Robo Coach Xuan and Taizo [55], Robo MD [56], Florence [57], Flo [58], GiraffPlus [59], Cybi [60], Pearl [61].…”

Section: Companion and Service Combo Robotmentioning

confidence: 99%

A Review on Usability and User Experience of Assistive Social Robots for Older Persons

Isa¹,

Saptari²,

Perumal³

et al. 2022

IJIE

View full text Add to dashboard Cite

show abstract

“…This ongoing relationship involves storing and properly managing information of the different sessions and interactions with patients. Recent projects have also addressed very important aspects in human-machine interaction, such as their social acceptance [23] or the possibility of including additional capabilities such as memory, cognition, emotion recognition or lifelong learning [24,25,26,27,28,29].…”

Section: Conversational Agents and Robotsmentioning

confidence: 99%

Conversational Agents for Mental Health and Wellbeing

Callejas

Griol

2021

Logic, Argumentation &Amp; Reasoning

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Recent advances in spoken language technology, artificial intelligence, and conversational interface design, coupled with the emergence of smart devices, have increased the possibilities of using conversational interfaces for a growing range of application domains. These interfaces are currently applied in the healthcare domain in a range of innovative tasks that allow to provide a more natural an user-friendly human-machine communication, promote patient participation in their own care, and help and support medical professionals. This chapter provides a detailed description of the great potential for the use of conversational interfaces for the specific area of mental health by means of the description of their most valuable applications in this domain and the open challenges for future research.

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“…This continuity forces dialogs to manage extensive and persistent information about the different sessions of the patient. In addition, recent projects have also addressed very important aspects in multimodal human–machine interaction like the social acceptability of verbally assistive systems (Payr, ) or the possibility of including additional capabilities such as memory, cognition, emotion recognition, or learning (Cavazza, De La Cámara, & Turunen, ; Leite et al, ; Young, ), Soprano (Sixsmith et al, ), Humaine (Andre et al, ; Rehrl et al, )).…”

Section: Related Workmentioning

confidence: 99%

A multimodal conversational coach for active ageing based on sentient computing and m‐health

2019

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As life expectancy increases, it has become more necessary to find ways to support healthy ageing. A number of active ageing initiatives are being developed nowadays to foster healthy habits in the population. This paper presents our contribution to these initiatives in the form of a multimodal conversational coach that acts as a coach for physical activities. The agent can be developed as an Android app running on smartphones and coupled with cheap widely available sport sensors in order to provide meaningful coaching. It can be employed to prepare exercise sessions, provide feedback during the sessions, and discuss the results after the exercise. It incorporates an affective component that informs dynamic user models to produce adaptive interaction strategies.

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The Robot ALIAS as a Database for Health Monitoring for Elderly People

Cited by 9 publications

References 7 publications

A Review on Usability and User Experience of Assistive Social Robots for Older Persons

A Review on Usability and User Experience of Assistive Social Robots for Older Persons

Conversational Agents for Mental Health and Wellbeing

A multimodal conversational coach for active ageing based on sentient computing and m‐health

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