Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland.
PLoS One. 2012;7(2):e32239. doi: 10.1371/journal.pone.0032239. Epub 2012 Feb 23.
Modern theories define chronic pain as a multidimensional experience - the result of complex interplay between physiological and psychological factors with significant impact on patients' physical, emotional and social functioning. The development of reliable assessment tools capable of capturing the multidimensional impact of chronic pain has challenged the medical community for decades. A number of validated tools are currently used in clinical practice however they all rely on self-reporting and are therefore inherently subjective. In this study we show that a comprehensive analysis of physical activity (PA) under real life conditions may capture behavioral aspects that may reflect physical and emotional functioning.
PA was monitored during five consecutive days in 60 chronic pain patients and 15 pain-free healthy subjects. To analyze the various aspects of pain-related activity behaviors we defined the concept of PA 'barcoding'. The main idea was to combine different features of PA (type, intensity, duration) to define various PA states. The temporal sequence of different states was visualized as a 'barcode' which indicated that significant information about daily activity can be contained in the amount and variety of PA states, and in the temporal structure of sequence. This information was quantified using complementary measures such as structural complexity metrics (information and sample entropy, Lempel-Ziv complexity), time spent in PA states, and two composite scores, which integrate all measures. The reliability of these measures to characterize chronic pain conditions was assessed by comparing groups of subjects with clinically different pain intensity.
The defined measures of PA showed good discriminative features. The results suggest that significant information about pain-related functional limitations is captured by the structural complexity of PA barcodes, which decreases when the intensity of pain increases. We conclude that a comprehensive analysis of daily-life PA can provide an objective appraisal of the intensity of pain.
现代理论将慢性疼痛定义为一种多维体验——是生理和心理因素复杂相互作用的结果，对患者的身体、情感和社会功能有重大影响。几十年来，医学界一直在努力开发能够捕捉慢性疼痛多维影响的可靠评估工具。目前，有许多经过验证的工具在临床实践中使用，但它们都依赖于自我报告，因此本质上是主观的。在这项研究中，我们表明，在真实生活条件下对身体活动（PA）进行全面分析，可以捕捉到可能反映身体和情绪功能的行为方面。
在连续 5 天内，对 60 名慢性疼痛患者和 15 名无疼痛健康受试者进行 PA 监测。为了分析与疼痛相关的活动行为的各个方面，我们定义了 PA“条形码”的概念。主要思想是将 PA 的不同特征（类型、强度、持续时间）结合起来，定义各种 PA 状态。不同状态的时间序列以“条形码”的形式可视化，这表明关于日常活动的大量信息可以包含在 PA 状态的数量和种类以及序列的时间结构中。使用补充措施（如信息和样本熵、莱姆普-齐夫复杂性等结构复杂性度量）来量化此信息，以及 PA 状态下的时间、以及整合所有措施的两个综合得分。通过比较具有临床不同疼痛强度的受试者组来评估这些措施来描述慢性疼痛状况的可靠性。
PA 的定义措施具有良好的区分特征。结果表明，PA 条形码的结构复杂性捕捉到了与疼痛相关的功能限制的重要信息，而当疼痛强度增加时，这些信息会减少。我们得出结论，对日常生活中的 PA 进行全面分析可以客观评估疼痛的强度。
