Guevara Nelson E, Rengifo Carlos F, Bolaños Yamir H, Fernández Daniel A, Sierra Wilson A, Rodríguez Luis E
Research Group of Automation, Universidad del Cauca, Colombia.
Department of Electronic, Instrumentation and Control, Universidad del Cauca, Colombia.
HardwareX. 2024 Sep 27;20:e00589. doi: 10.1016/j.ohx.2024.e00589. eCollection 2024 Dec.
This paper proposes a low-cost electronic system for estimating ground reaction forces (GRF) during human gait. The device consists of one master node and two slave nodes. The master node sends instructions to slave nodes that sample and store data from two force insoles located at the participant's feet. These insoles are equipped with 14 piezo-resistive FlexiForce A301 sensors (FSR). The slave nodes are attached to the ankles and feet of each participant. Subsequently, the start command is transmitted through the master node, which is connected to the USB port of a personal computer (PC). Once the walking session is completed, the information obtained by the slave nodes can be downloaded by accessing the access point generated by these devices through Wi-Fi communication. The GRF estimation system was validated with force platforms (), giving on average a measure equal to in dynamic situations. Future versions of this device are expected to increase this by using machine learning models.
本文提出了一种用于估计人体步态期间地面反作用力(GRF)的低成本电子系统。该设备由一个主节点和两个从节点组成。主节点向从节点发送指令,从节点对位于参与者脚部的两个测力鞋垫的数据进行采样和存储。这些鞋垫配备了14个压阻式FlexiForce A301传感器(FSR)。从节点连接到每个参与者的脚踝和脚部。随后,启动命令通过与个人计算机(PC)的USB端口相连的主节点进行传输。一旦步行过程完成,通过Wi-Fi通信访问这些设备生成的接入点,就可以下载从节点获得的信息。GRF估计系统通过力平台进行了验证(),在动态情况下平均给出的测量值等于 。预计该设备的未来版本将通过使用机器学习模型来提高这个 值。