Movement sonification has emerged as a promising approach for rehabilitation and motion control. Despite significant advancements in sensor technologies, challenges remain in developing cost-effective, user-friendly, and reliable systems for gait detection and sonification. This study introduces a novel wearable personalised sonification and biofeedback device to enhance movement awareness for individuals with irregular gait and posture.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
June 2024
The brain continually reorganizes its functional network to adapt to post-stroke functional impairments. Previous studies using static modularity analysis have presented global-level behavior patterns of this network reorganization. However, it is far from understood how the brain reconfigures its functional network dynamically following a stroke.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2023
The brain's functional network can be analyzed as a set of distributed functional modules. Previous studies using the static method suggested the modularity of the brain function network decreased due to stroke; however, how the modular network changes after stroke, particularly over time, is far from understood. This study collected resting-state functional MRI data from 15 stroke patients and 15 age-matched healthy controls.
View Article and Find Full Text PDFBackground: Motor impairment is a common consequence of stroke causing difficulty in independent movement. The first month of post-stroke rehabilitation is the most effective period for recovery. Movement imagination, known as motor imagery, in combination with virtual reality may provide a way for stroke patients with severe motor disabilities to begin rehabilitation.
View Article and Find Full Text PDFIntroduction: Functional magnetic resonance imaging (fMRI) has shown that aging disturbs healthy brain organization and functional connectivity. However, how this age-induced alteration impacts dynamic brain function interaction has not yet been fully investigated. Dynamic function network connectivity (DFNC) analysis can produce a brain representation based on the time-varying network connectivity changes, which can be further used to study the brain aging mechanism for people at different age stages.
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