Research Centre in Digitalization and Intelligent Robotics (CeDRI), Polytechnic Institute of Bragança, 5300-253 Bragança, Portugal.
ALGORITMI Centre, University of Minho, 4800-058 Braga, Portugal.
Sensors (Basel). 2022 Oct 7;22(19):7605. doi: 10.3390/s22197605.
The progressive loss of functional capacity due to aging is a serious problem that can compromise human locomotion capacity, requiring the help of an assistant and reducing independence. The NanoStim project aims to develop a system capable of performing treatment with electrostimulation at the patient's home, reducing the number of consultations. The knee angle is one of the essential attributes in this context, helping understand the patient's movement during the treatment session. This article presents a wearable system that recognizes the knee angle through IMU sensors. The hardware chosen for the wearables are low cost, including an ESP32 microcontroller and an MPU-6050 sensor. However, this hardware impairs signal accuracy in the multitasking environment expected in rehabilitation treatment. Three optimization filters with algorithmic complexity O(1) were tested to improve the signal's noise. The complementary filter obtained the best result, presenting an average error of 0.6 degrees and an improvement of 77% in MSE. Furthermore, an interface in the mobile app was developed to respond immediately to the recognized movement. The systems were tested with volunteers in a real environment and could successfully measure the movement performed. In the future, it is planned to use the recognized angle with the electromyography sensor.
由于衰老导致的功能能力逐渐丧失是一个严重的问题,可能会影响人类的行动能力,需要辅助人员的帮助,并降低其独立性。NanoStim 项目旨在开发一种能够在患者家中进行电刺激治疗的系统,减少就诊次数。在这种情况下,膝关节角度是一个重要的属性,可以帮助了解患者在治疗过程中的运动情况。本文提出了一种通过 IMU 传感器识别膝关节角度的可穿戴系统。所选的可穿戴硬件成本低,包括 ESP32 微控制器和 MPU-6050 传感器。然而,这种硬件在康复治疗中预期的多任务环境中会影响信号的准确性。测试了三种具有算法复杂度 O(1)的优化滤波器来改善信号的噪声。互补滤波器获得了最佳结果,平均误差为 0.6 度,MSE 提高了 77%。此外,还在移动应用程序中开发了一个界面,以便对识别到的运动做出即时响应。该系统在真实环境中对志愿者进行了测试,能够成功测量所进行的运动。未来,计划使用识别出的角度和肌电图传感器。