Smart Computer-Assisted Cognitive Rehabilitation for the Ageing Population

Oliver, Miguel; González, Pascual; Montero, Francisco; Molina, José Pascual; Fernández-Caballero, Antonio

doi:10.1007/978-3-319-40114-0_22

Cited by 10 publications

(13 citation statements)

References 8 publications

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“…Thus, after analyzing different proposals in the rehabilitation domain and what kind of patients our system is focused on, we present our system and the main differences with our previous work (Oliver, M. et al, 2016) that is the base of this paper. We present the system architecture and describe all the components, detailing the new features that allow bringing in all the social aspects.…”

Section: Discussionmentioning

confidence: 99%

“…One of them is a quiz activity, which not only makes the person perform the physical exercise, but also focuses on cognitive aspect to answer some basic set of general knowledge questions. Finally, we can find the proposal presented by us which is the base of this work (Oliver et al, 2016) that. In that paper a tool for designing cognitive therapies is presented.…”

Section: Assistive Technologies In Physical and Cognitive Rehabilitationmentioning

confidence: 94%

See 1 more Smart Citation

Collaborative Computer-Assisted Cognitive Rehabilitation System

Oliver¹,

Molina²,

Fernández-Caballero³

et al. 2017

ADCAIJ

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Section: Discussionmentioning

confidence: 99%

Section: Assistive Technologies In Physical and Cognitive Rehabilitationmentioning

confidence: 94%

Collaborative Computer-Assisted Cognitive Rehabilitation System

Oliver¹,

Molina²,

Fernández-Caballero³

et al. 2017

ADCAIJ

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“…Lastly, Oliver et al [38] developed a system tailored on cognitive and motor rehabilitation targeting aging individuals. It presents a strategic and extensible Rule Authoring component, that, considering the broad variety of cognitive injuries, offers a considerable number of possible exercises to treat them.…”

Section: Video-based Systemsmentioning

confidence: 99%

Real-time multi-agent systems for telerehabilitation scenarios

Calvaresi

Marinoni

Dragoni

et al. 2019

Artificial Intelligence in Medicine

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Telerehabilitation in older adults is most needed in the patient environments, rather than in formal ambulatories or hospitals. Supporting such practices brings significant advantages to patients, their family, formal and informal caregivers, clinicians, and researchers. This paper presents a focus group with experts in physiotherapy and telerehabilitation, debating on the requirements, current techniques and technologies developed to facilitate and enhance the effectiveness of telerehabilitation, and the still open challenges. Particular emphasis is given to (i) the body-parts requiring the most rehabilitation, (ii) the typical environments, initial causes, and general conditions, (iii) the values and parameters to be observed, (iv) common errors and limitations of current practices and technological solutions, and (v) the envisioned and desired technological support. Consequently, it has been performed a systematic review of the state of the art, investigating what types of systems and support currently cope with telerehabilitation practices and possible matches with the outcomes of the focus group. Technological solutions based on video analysis, wearable devices, robotic support, distributed sensing, and gamified telerehabilitation are examined. Particular emphasis is given to solutions implementing agent-based approaches, analyzing and discussing strength, limitations, and future challenges. By doing so, it has been possible to relate functional requirements expressed by professional physiotherapists and researchers, with the need for extending multi-agent systems (MAS) peculiarities at the sensing level in wearable solutions establishing new research challenges. In particular, to be employed in safety-critical cyber-physical scenarios with user-sensor and sensor-sensor interactions, MAS are requested to handle timing constraints, scarcity of resources and new communication means, crucial to providing real-time feedback and coaching. Therefore, MAS pillars such as the negotiation protocol and the agent's internal scheduler have been investigated, proposing solutions to achieve the aforementioned real-time compliance.

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“…"Living Labs" show use of sensors to monitor human behaviour in real life environment. [20] shows some solution based on AmI using assistive technology to help elderly people. These techniques deal with physical and cognitive rehabilitation.…”

Section: Availability Of Rehabilitationmentioning

confidence: 99%

Ambient Intelligence for Rehabilitation: A Survey

Gorave¹

2019

IJCA

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Rehabilitation is defined as a set of measures that assist individuals who experience, or are likely to experience, disability to achieve and maintain optimal functioning in interaction with their environments. Ambient Intelligence (AmI) refers to a digital environment that proactively, but sensibly, supports people in their daily lives. AmI is useful in order to rehabilitate patients. In this paper, a survey of AmI for rehabilitation is presented.

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Smart Computer-Assisted Cognitive Rehabilitation for the Ageing Population

Cited by 10 publications

References 8 publications

Collaborative Computer-Assisted Cognitive Rehabilitation System

Collaborative Computer-Assisted Cognitive Rehabilitation System

Real-time multi-agent systems for telerehabilitation scenarios

Ambient Intelligence for Rehabilitation: A Survey

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