Predictive Biomechanics for Modelling Gait Stability and Falls Prediction

用于步态稳定性和跌倒预测建模的预测生物力学

• 批准号: DP240101449
• 负责人: Prof Rezaul Begg
• 金额: $ 46.17万
• 依托单位: Victoria University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2024
• 资助国家: 澳大利亚
• 起止时间: 2024-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP240101449
• 关键词: Predictive; Biomechanics; Modelling; Gait; Stability

Efficient, adaptive locomotion is critical to our independence, but it is adversely affected by neuromuscular disorders due to trauma, ageing and other impairments that increase the risk of balance loss and falling. This project investigates the extraordinary possibilities of advancing from the traditional laboratory-based, retrospective, gait research paradigm, to real-world gait monitoring using predictive biomechanics. By employing artificial intelligence, wearable sensors' data will predict balance loss and alert the user. The outcome will be fundamental knowledge for developing wearable systems to reduce the catastrophic impact of falls, with public health cost savings and improved quality of life for people with restricted mobility.

有效的、适应性的运动对我们的独立性至关重要，但它会受到创伤、衰老和其他损伤引起的神经肌肉疾病的不利影响，这些损伤会增加失去平衡和跌倒的风险。该项目探讨了从传统的基于实验室的回顾性步态研究范式发展到使用预测生物力学进行现实世界步态监测的非凡可能性。通过采用人工智能，可穿戴传感器的数据将预测平衡损失并提醒用户。其结果将是开发可穿戴系统的基础知识，以减少福尔斯的灾难性影响，节省公共卫生成本，提高行动不便者的生活质量。