IEEE Trans Neural Syst Rehabil Eng. 2021;29:2550-2558. doi: 10.1109/TNSRE.2021.3132644. Epub 2021 Dec 15.
Pushrim-activated power-assisted wheels (PAPAWs) are assistive technologies that provide on-demand propulsion assistance to wheelchair users. In this study, we aimed to develop an adaptive PAPAW controller that responds effectively to changes in environmental conditions (e.g., type of surface or terrain). Experiments were conducted to collect kinematics of wheelchair motion using a frame-mounted inertial measurement unit (IMU) while performing a variety of wheelchair activities on different indoor/outdoor terrains. Statistical characteristics of velocity and acceleration measurements were extracted and used to develop a terrain classification framework to identify certain indoor and outdoor terrains. The terrain classification framework, based on random forest classification algorithms and kinematic features, was implemented and tested in our laboratory-developed PAPAW. This computationally efficient terrain classification framework was successfully implemented and tested in real-time. The power-assist ratio of each wheel was adjusted based on the type of terrain (e.g., more assistance was provided on outdoor terrains). Our findings revealed that propulsion effort (e.g., peak input torque) on asphalt was significantly reduced when using adaptive controllers compared to conventional PAPAW controllers. In addition, subjective views of participants regarding the workload of wheelchair propulsion (e.g., physical/cognitive effort) supported the positive effects of adaptive PAPAW controllers. We believe that the adoption of terrain-specific adaptive controllers has the potential to improve the accessibility of outdoor terrains and to prevent or delay upper extremity joint degeneration or pain.
推把式动力辅助轮(PAPAW)是一种辅助技术,可为轮椅使用者提供按需推进辅助。在这项研究中,我们旨在开发一种自适应 PAPAW 控制器,以有效响应环境条件的变化(例如,表面类型或地形)。实验中使用安装在框架上的惯性测量单元(IMU)收集轮椅运动的运动学数据,同时在不同的室内/室外地形上进行各种轮椅活动。提取速度和加速度测量的统计特征,并使用它们来开发地形分类框架,以识别某些室内和室外地形。基于随机森林分类算法和运动学特征的地形分类框架在我们实验室开发的 PAPAW 中进行了实施和测试。这种计算效率高的地形分类框架已成功在实时环境中实施和测试。根据地形类型(例如,室外地形提供更多辅助)调整每个轮子的动力辅助比。我们的研究结果表明,与传统的 PAPAW 控制器相比,自适应控制器可显著降低在沥青路面上的推进力(例如,峰值输入扭矩)。此外,参与者对轮椅推进工作负荷(例如,体力/认知力)的主观看法支持了自适应 PAPAW 控制器的积极效果。我们相信,采用特定地形的自适应控制器有可能改善户外地形的可达性,并预防或延迟上肢关节退化或疼痛。