Stroke causes neurological pathologies, including gait pathologies, which are diagnosed by gait analysis. However, existing gait analysis devices are difficult to use in situ or are disrupted by external conditions. To overcome these drawbacks, a flexible capacitance sensor was developed in this study. To date, a performance comparison of flexible sensors with different dimensions has not been carried out. The aim of this study was to provide optimized sensor dimension information for gait analysis. To accomplish this, sensors with seven different dimensions were fabricated. The dimensions of the sensors were based on the average body size and movement range of 20- to 59-year-old adults. The sensors were characterized by 100 oscillations. The minimum hysteresis error was 8%. After that, four subjects were equipped with the sensor and walked on a treadmill at a speed of 3.6 km/h. All walking processes were filmed at 50 fps and analyzed in Kinovea. The RMS error was calculated using the same frame rate of the video and the sampling rate of the signal from the sensor. The smallest RMS error between the sensor data and the ankle angle was 3.13° using the 49 × 8 mm sensor. In this study, we confirm the dimensions of the sensor with the highest gait analysis accuracy; therefore, the results can be used to make decisions regarding sensor dimensions.

中文翻译：

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不同尺寸柔性电容传感器的分析精度差异

中风导致神经病理学，包括步态病理学，其通过步态分析来诊断。然而，现有的步态分析设备难以原位使用或受到外部条件的干扰。为了克服这些缺点，本研究开发了一种灵活的电容传感器。迄今为止，尚未对不同尺寸的柔性传感器进行性能比较。本研究的目的是为步态分析提供优化的传感器尺寸信息。为了实现这一点，制造了七种不同尺寸的传感器。传感器的尺寸基于 20 至 59 岁成年人的平均体型和运动范围。传感器的特点是 100 次振荡。最小滞后误差为 8%。在那之后，四名受试者配备了传感器并以 3.6 公里/小时的速度在跑步机上行走。所有步行过程均以 50 fps 的速度拍摄，并在 Kinovea 中进行分析。RMS 误差是使用相同的视频帧率和来自传感器的信号采样率计算的。使用 49 × 8 mm 传感器时，传感器数据和脚踝角度之间的最小 RMS 误差为 3.13°。在这项研究中，我们确认了具有最高步态分析精度的传感器的尺寸；因此，结果可用于做出有关传感器尺寸的决策。使用 49 × 8 mm 传感器时，传感器数据和脚踝角度之间的最小 RMS 误差为 3.13°。在这项研究中，我们确认了具有最高步态分析精度的传感器的尺寸；因此，结果可用于做出有关传感器尺寸的决策。使用 49 × 8 mm 传感器时，传感器数据和脚踝角度之间的最小 RMS 误差为 3.13°。在这项研究中，我们确认了具有最高步态分析精度的传感器的尺寸；因此，结果可用于做出有关传感器尺寸的决策。