YominE/Muscle_Fatigue_Cycling
收藏Hugging Face2024-12-13 更新2024-12-14 收录
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https://hf-mirror.com/datasets/YominE/Muscle_Fatigue_Cycling
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资源简介:
该数据集由18至25岁的健康参与者创建,参与者并非经常运动的运动员。数据集包含8个EMG信号,这些信号是在参与者在有条件的自行车上进行高强度冲刺时从主导脚记录的。当参与者无法维持冲刺强度时,这被认为是疲劳的第一个指标,并标记为‘过渡到疲劳’。如果参与者无法继续基础运动,则标记为‘疲劳’。建议使用二分类模型,将‘过渡到疲劳’状态作为正类,因为‘疲劳’类的数据量较少。数据集的特征包括时间和多个肌肉的EMG信号。
This dataset was created with healthy participants aged between 18 and 25 years old. The participants in this dataset were not frequent athletes. The dataset consists of 8 EMG signals recorded from the domineering foot of each participant during a cycling trial. The participants performed exercises on a conditioned cycle, alternating with short periods of high-intensity sprints. When a participant could no longer sustain the sprint intensity, this was considered the first index of fatigue and was labeled as Transition-to-Fatigue. If the participant was unable to continue the base exercise, it was labeled as Fatigue. For this dataset, it is recommended to work with binary classification models, taking the Transition-to-Fatigue state as the positive class, as the data in the Fatigue class is significantly limited.
提供机构:
YominE



