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Chapitre D'ouvrage Année : 2017

Multimodal Analysis of Synchronization Data from Patients with Dementia


Little is known about the abilities of people with dementia to synchronize bodily movements to music. The lack of non-intrusive tools that do not hinder patients, and the absence of appropriate analysis methods may explain why such investigations remain challenging. This paper discusses the development of an analysis framework for processing sensorimotor synchronization data obtained from multiple measuring devices. The data was collected during an explorative study, carried out at the University Hospital of Reims (F), involving 16 individuals with dementia. The study aimed at testing new methods and measurement tools developed to investigate sensorimotor synchronization capacities in people with dementia. An analysis framework was established for the extraction of quantity of motion and synchronization parameters from the multimodal dataset composed of sensor, audio, and video data. A user-friendly monitoring tool and analysis framework has been established and tested that holds potential to respond to the needs of complex movement data handling. The study enabled improving of the hardware and software robustness. It provides a strong framework for future experiments involving people with dementia interacting with music.

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Dates et versions

hal-04082197 , version 1 (26-04-2023)


  • HAL Id : hal-04082197 , version 1


Frank Desmet, Micheline Lesaffre, Joren Six, Nathalie Ehrlé, Severine Samson. Multimodal Analysis of Synchronization Data from Patients with Dementia. van Dyck, E. Proceedings of the 25th Anniversary Conference of the European Society for the Cognitive Sciences of Music (ESCOM 2017), Ghent University, p. 53-58, 2017. ⟨hal-04082197⟩


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