Robotic System to Motivate Long Term Infant Kicking for Motor Development Progression
Author(s)
Emeli, Victor
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Abstract
The spontaneous kicking patterns of an infant provide markers that may predict the progression of motor development. Consistent atypical kicking behaviors can forecast irregularities in future development. One main indicator of impaired motor development is the progressive advancement of spasticity in muscle groups. For at-risk infants, physical therapy that encourages kicking motions can help reduce the onset of spasticity, especially if initiated at an early age. Traditionally, physical therapy is conducted by health professionals in a clinical setting, which can be labor intensive and costly. A method that increases physical therapy opportunities by providing an in-home system that motivates kicking motions and operates without immediate clinical supervision would be beneficial. We introduce a system that utilizes 3D computer vision and a robotic infant mobile to detect spontaneous kicking patterns and activate mobile stimuli to encourage prolonged kicking activity. The visual classification of kick or non-kick activity is used to activate the mobile stimuli with the goal of encouraging continued kicking patterns. We also employ statistical techniques to calculate kick amplitude, kick intensity, and kick deviation. These parameters provide insight into kick features and provide measurements to validate the influence of the mobile stimuli on kicking behavior. Additionally, we develop algorithms to identify mobile stimuli preferences that are unique to each infant for encouraging prolonged kicking activity. Finally, we investigate methods for reducing the complexity of the system by employing 2D data estimation for real-world use cases.
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Date
2023-12-12
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Text
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Dissertation