Ultralight wheelchair part failures are associated with sensor-monitored road shocks: A pilot study

Wheelchair part failures and repairs have significantly increased over the last decade, leading to severe consequences for wheelchair users. Servicing these devices by wheelchair repair technicians has reduced part failures. However, no tools or technologies have been developed to support servicing in practice. To inform servicing events, risk factors affecting wheelchair quality and reliability need to be identified. This pilot study tracks wheelchair usage for a week in the community for eight ultralight manual wheelchair users and assesses the relationship between usage variables and user-reported part failures over 20 months. The participants’ preferences for using smart technology for wheelchair servicing were evaluated. At least 73 wheelchair part failures and two adverse consequences were reported. Data analysis indicated associations between part failure frequency, usage variable of road shocks, wheelchair maintenance frequency, and the user’s demographic characteristics of training status and transportation. Six participants favored using smart technology for wheelchair servicing. This study’s findings encourage the development of usage monitoring technology and failure prediction models to support technician-led servicing and prevent wheelchair failures and user consequences.

过去十年间，轮椅部件故障与维修需求显著增加，给轮椅使用者带来了严重后果。轮椅维修技师对设备的维护虽已减少部件故障，但目前尚无实际可用的工具或技术支持此类维护工作。为指导维护工作，需明确影响轮椅质量与可靠性的风险因素。本试点研究对8名超轻型手动轮椅使用者在社区中的一周使用情况进行追踪，并评估20个月内使用变量与用户报告的部件故障之间的关系，同时评估了参与者对将智能技术应用于轮椅维护的偏好。研究报告了至少73起轮椅部件故障及2起不良后果。数据分析显示，部件故障频率与路面冲击这一使用变量、轮椅维护频率，以及用户的训练状态和出行方式等人口统计学特征之间存在关联。6名参与者倾向于使用智能技术进行轮椅维护。本研究结果为开发使用监测技术与故障预测模型提供了依据，以支持技师主导的维护工作，预防轮椅故障及对使用者造成的后果。