Rhythmic auditory stimuli, or cueing, are known to be effective to modulate the rhythm or cadence of people performing different activities. By providing an adequate rhythm, coordination and rhythmicity of movements, as well as the amplitude of movements, can be improved.
Rhythmic auditory cueing are known to be effective to regulate and overcome typical gait problems that occur in patients with Parkinson’s disease and other neurodegenerative diseases. Auditory cueing can also act as a rehabilitation strategy, for example, after doing some orthopaedic corrective treatments. Cueing can also be used during training sessions to improve the athletic performance of a competitor. Sounds can therefore be applied in several different situations, including therapeutic sessions, gait guidance and training.
Several types of sounds can be used as a cueing strategy, including metronomes, music or both types joined together. Sounds can be manipulated in order to change their rhythm in real time, using appropriate time stretching techniques.
The purpose of this research is to explore the use of the smartphone and its sensors to detect several movement measures in real time, including gait measures, like cadence and velocity. Particularly, the study is focused on the detection of gait problems that typically occurs in people with Parkinson’s disease, including bradykinesia, small steps, reduced speed, variability and freezing of gait episodes, which must be detected in real time based on smartphone sensors’ information.
The project also explores the use and manipulation of music to act as cueing during different activities. Sounds can be triggered manually (for rehabilitation or training purposes) or automatically, based on walking pattern of the person (for gait guidance). Characteristics of sounds (including their rhythm) are adapted to the specific needs of the user, considering their walking patterns and their response to the sounds delivered.
The purpose of this research is to explore the use of the smartphone and its sensors to detect movement measures and motor symptoms in patients with Parkinson’s disease. Additionally, the project explores the use and manipulation of music to act as cueing, adjusting the characteristics of sounds to the patients’ needs, taking into account the information sensed by the smartphone.
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