Objective
Aphasia causes severe impairments in verbal communication, coupled with cognitive and motor deficits and depression, making it the most debilitating and socioeconomically burdening consequence of stroke. As our population ages and prevalence of stroke and associated care costs increase, persons with aphasia (PWA) often do not receive sufficient rehabilitation in public health care. Effective remote rehabilitation applications are urgently needed to ensure comprehensive and cost-effective aphasia care. PWA often retain the ability to produce words through singing, and rehabilitation methods using music and singing are promising tools for enhancing communication and psychosocial wellbeing in aphasia. However, there are currently no music-based remote rehabilitation applications available for PWA, which greatly limits the inclusion of music in aphasia care.
In OPTIMUS, I will lead the development of a novel and innovative multicomponent music-based remote rehabilitation (MMRR) programme for aphasia and determine its usability, applicability, and effects, first through pilot experiments and engagement with stakeholders (PWA, patient associations, rehabilitation staff) and then in a 3-month feasibility randomized controlled trial in 30 PWA. Compared to existing aphasia rehabilitation methods, MMRR has the added value of being more (i) versatile, targeting verbal, cognitive, motor, and emotional functions through multiple musical training modules (singing, rhythm & movement, music listening); (ii) enjoyable and motivating, enabling better adherence to treatment protocol and larger training volumes; and (iii) widely scalable and easy to implement in stroke rehabilitation.
OPTIMUS will have major scientific, clinical, and societal value and can lead to a breakthrough social innovation in aphasia treatment by providing a comprehensive music-based remote rehabilitation tool that can be made publicly available and integrated to the clinical stroke rehabilitation continuum.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- medical and health sciencesclinical medicinephysiotherapy
- medical and health sciencesbasic medicineneurologystroke
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Keywords
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Funding Scheme
HORIZON-ERC-POC - HORIZON ERC Proof of Concept GrantsHost institution
00014 HELSINGIN YLIOPISTO
Finland