基于足底压力的不规范深蹲姿势识别

Detection of common incorrect squats based on sensor insoles

深蹲被称为力量训练之王,但不正确的姿势会对人体产生不可逆转的伤害。提出了一种利用足底压力来检测常见不正确的蹲姿的方法。使用带8个压力传感器的鞋垫收集了1组正确蹲姿和4组常见错误蹲姿的数据,提出了对这些连续蹲姿数据进行分割的算法,并对压力云图进行了分析。然后设计了3组深度神经网络作为分类器,分别是引入注意力机制的长短期记忆网络(att-LSTM)、长短期记忆网络(LSTM)和卷积神经网络(CNN)。实验结果表明,3组模型的测试准确率分别为90.2%、83.0%和79.8%。结果表明,采用引入注意力机制的LSTM作为分类算法是一种有效的蹲姿检测方法。

Squat is known as the king of strength trainings.However,the incorrect positions may produce irreversible damage to the human body.This study proposes a method utilizing plantar pressure to detect common incorrect squats position.Insoles with eight pressure sensors are utilized to collected 5 sets of database,which are correct squat and 4 common incorrect squats.An algorithm is proposed to segment those continuous pressure data.Then,the pressure nephogram is also analyzed.Three sets of deep neural network are designed as classifiers,which are Att-LSTM,LSTM,and CNN,respectively.Experimental results show that accuracies of these models are 90.2%,83.0%and 79.8%,respectively.The results suggest that the utilization of sensor insoles with LSTM and attention mechanism as the classification algorithm is a valid method to detect squats position.