Ali Raza, Atallah Louis, Lo Benny, Yang Guang-Zhong
Hamlyn Center, Imperial College, London, UK.
IEEE Trans Inf Technol Biomed. 2012 Jan;16(1):119-28. doi: 10.1109/TITB.2011.2165320. Epub 2011 Aug 18.
Activity monitoring is important for assessing daily living conditions for elderly patients and those with chronic diseases. Transitions between activities can present characteristic patterns that may be indicative of quality of movement. To detect and analyze transitional activities, a manifold-based approach is proposed in this paper. The proposed method uses a recursive spectral graph-partitioning algorithm to segment transitions in activity. These segments are subsequently mapped to a reference manifold space. Categorization of transitions is performed with the corresponding features in the manifold space. The practical value of the work is demonstrated through data collected under laboratory conditions, as well as patients recovering from total knee replacement operations, demonstrating specific transitions and motion impairment compared to normal subjects.
活动监测对于评估老年患者和慢性病患者的日常生活状况非常重要。活动之间的转换可能呈现出特征模式，这些模式可能表明运动质量。为了检测和分析过渡活动，本文提出了一种基于流形的方法。所提出的方法使用递归谱图划分算法来分割活动中的转换。这些片段随后被映射到参考流形空间。在流形空间中利用相应特征对转换进行分类。通过在实验室条件下收集的数据以及从全膝关节置换手术中恢复的患者的数据，证明了这项工作的实际价值，与正常受试者相比，展示了特定的转换和运动损伤。
