Intelligent prompting system to assist stroke survivors

Jean-Baptiste, Emilie M. D.; Russell, Martin J.; Howe, J. L.; Rotshtein, Pia

doi:10.3233/ais-170461

Cited by 5 publications

(3 citation statements)

References 46 publications

(42 reference statements)

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“…This evaluation allows to show the evolution of the problem of the person to determine when he/she is not any more able to live independently. The second kind of application is to help people performing these activities taking into account the specificity of their disease/impairment [46]. It can improve their conditions of living at home and their experiences.…”

Section: Ambient Assisted Livingmentioning

confidence: 99%

Internet of Things for enabling smart environments: A technology-centric perspective

Gómez

Chessa

Fleury

et al. 2019

AIS

115

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The Internet of Things (IoT) is a computing paradigm whereby everyday life objects are augmented with computational and wireless communication capabilities, typically through the incorporation of resource-constrained devices including sensors and actuators, which enable their connection to the Internet. The IoT is seen as the key ingredient for the development of smart environments. Nevertheless, the current IoT ecosystem offers many alternative communication solutions with diverse performance characteristics. This situation presents a major challenge to identifying the most suitable IoT communication solution(s) for a particular smart environment. In this paper we consider the distinct requirements of key smart environments, namely the smart home, smart health, smart cities and smart factories, and relate them to current IoT communication solutions. Specifically, we describe the core characteristics of these smart environments and then proceed to provide a comprehensive survey of relevant IoT communication technologies and architectures. We conclude with our reflections on the crucial features of IoT solutions in this setting and a discussion of challenges that remain open for research.

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Section: Ambient Assisted Livingmentioning

confidence: 99%

Internet of Things for enabling smart environments: A technology-centric perspective

Gómez

Chessa

Fleury

et al. 2019

AIS

115

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“…The task model was represented as an MDP with a set of states and transition probabilities (allowing alternative paths through the sequence of steps) that were obtained from observations of control participants [ 19 ]. The task model was implemented as a subset of a computer-based system [ 25 ] developed in a project, CogWatch ( https://more.bham.ac.uk/cogwatch/ ) to provide home-based rehabilitation of ADL tasks. When this subsystem was previously tested with twelve stroke survivors with AADS, the success rate in making a cup of tea improved to 96% compared to 68% without the subsystem [ 25 ].…”

Section: Introductionmentioning

confidence: 99%

“…The task model was implemented as a subset of a computer-based system [ 25 ] developed in a project, CogWatch ( https://more.bham.ac.uk/cogwatch/ ) to provide home-based rehabilitation of ADL tasks. When this subsystem was previously tested with twelve stroke survivors with AADS, the success rate in making a cup of tea improved to 96% compared to 68% without the subsystem [ 25 ]. The present study seeks to extend this finding with training over a number of sessions, in a randomized controlled design, and including follow-up assessment.…”

Section: Introductionmentioning

confidence: 99%

The efficacy of a task model approach to ADL rehabilitation in stroke apraxia and action disorganisation syndrome: A randomised controlled trial

et al. 2022

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Background Apraxia and action disorganization syndrome (AADS) after stroke can disrupt activities of daily living (ADL). Occupational therapy has been effective in improving ADL performance, however, inclusion of multiple tasks means it is unclear which therapy elements contribute to improvement. We evaluated the efficacy of a task model approach to ADL rehabilitation, comparing training in making a cup of tea with a stepping training control condition. Methods Of the 29 stroke survivors with AADS who participated in this cross-over randomized controlled feasibility trial, 25 were included in analysis [44% females; mean(SD) age = 71.1(7.8) years; years post-stroke = 4.6(3.3)]. Participants attended five 1-hour weekly tea making training sessions in which progress was monitored and feedback given using a computer-based system which implemented a Markov Decision Process (MDP) task model. In a control condition, participants received five 1-hour weekly stepping sessions. Results Compared to stepping training, tea making training reduced errors across 4 different tea types. The time taken to make a cup of tea was reduced so the improvement in accuracy was not due to a speed-accuracy trade-off. No improvement linked to tea making training was evident in a complex tea preparation task (making two different cups of tea simultaneously), indicating a lack of generalisation in the training. Conclusions The clearly specified but flexible training protocol, together with information on the distribution of errors, provide pointers for further refinement of task model approaches to ADL rehabilitation. It is recommended that the approach be tested under errorless learning conditions with more impaired patients in future research. Trial registration Retrospectively registered at ClinicalTrials.gov on 5th August 2019 [NCT04044911] https://clinicaltrials.gov/ct2/show/NCT04044911?term=Cogwatch&rank=1

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