Skill Level Classification in Basketball Free-Throws Using a Single Inertial Sensor
نویسندگان
چکیده
Wearable sensors are an emerging technology, with growing evidence supporting their application in sport performance enhancement. This study utilized data collected from a tri-axial inertial sensor on the wrist of ten recreational and eight professional basketball players while they performed free-throws, to classify skill levels. We employed fully connected convolutional neural network (CNN) for classification task, using 64% training, 16% validation, remaining 20% testing model’s performance. In case considering single parameter sensor, most accurate individual components were upward acceleration (AX), accuracy 82% (sensitivity = 0.79; specificity 0.84), forward (AZ), 80% 0.78; 0.83), angular velocity sagittal plane (GY), 77% 0.73; 0.79). The highest was achieved when these CNN inputs stack-up matrix three axes, resulting 88% 0.87, 0.90). Applying wearable successfully classified as or up 88%. represents step towards development biofeedback device improve free-throw shooting technique.
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2023
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app13095401