Hou Yujie, Wang Zhaohui, Liu Huanhuan, Xia Mengxuan, Fan Xinyi, Ye Qinwen
College of Fashion and Design, Donghua University, Shanghai 200051, China.
Key Laboratory of Clothing Design and Technology, Donghua University, Ministry of Education, Shanghai 200051, China.
Sensors (Basel). 2025 May 27;25(11):3359. doi: 10.3390/s25113359.
Currently, the sedentary nature of office work has led to a steady increase in the prevalence of spinal disorders, including lower back pain, back pain, and neck pain. Medical research has shown that monitoring and improving sitting posture is an important measure to prevent spinal discomfort. The emergence and development of wearable technology have enabled more people to effectively monitor their health. In this study, we propose and design a textile sensor-based sitting posture correction smart garment to realize dynamic sitting reminders aimed at meeting the needs of sedentary office workers. The garment achieves real-time sitting posture recognition through integrated machine learning algorithms, with a recognition accuracy exceeding 95% using a random forest classifier. Additionally, we developed haptic vibration feedback and visual GUI feedback modes to provide sitting posture intervention and dynamic sitting reminders. To evaluate the system's effectiveness and usability, we conducted comparative experiments analyzing sitting posture behavior before and after wearing the smart garment, along with a user satisfaction survey. The results demonstrate that the smart garment effectively helps office workers adjust their sitting posture and reduces the risk of spinal discomfort associated with prolonged sedentary work.
目前，办公室工作久坐不动的特性导致脊柱疾病的患病率稳步上升，包括下背痛、背痛和颈部疼痛。医学研究表明，监测和改善坐姿是预防脊柱不适的一项重要措施。可穿戴技术的出现和发展使更多人能够有效地监测自身健康。在本研究中，我们提出并设计了一种基于纺织传感器的坐姿矫正智能服装，以实现动态坐姿提醒，旨在满足久坐办公室工作人员的需求。该服装通过集成机器学习算法实现实时坐姿识别，使用随机森林分类器时识别准确率超过95%。此外，我们开发了触觉振动反馈和视觉GUI反馈模式，以提供坐姿干预和动态坐姿提醒。为了评估该系统的有效性和可用性，我们进行了对比实验，分析了穿着智能服装前后的坐姿行为，并开展了用户满意度调查。结果表明，该智能服装有效地帮助办公室工作人员调整坐姿，并降低了与长时间久坐工作相关的脊柱不适风险。
