Causality Analysis of Inertial Body Sensors for Multiple Sclerosis Diagnostic Enhancement

被引:14
|
作者
Gong, Jiaqi [1 ]
Qi, Yanjun [2 ]
Goldman, Myla D. [3 ]
Lach, John [1 ]
机构
[1] Univ Virginia, Dept Elect & Comp Engn, UVA Ctr Wireless Hlth, Charlottesville, VA 22904 USA
[2] Univ Virginia, Dept Comp Sci, UVA Ctr Wireless Hlth, Charlottesville, VA 22904 USA
[3] Univ Virginia, Dept Neurol, UVA Ctr Wireless Hlth, Charlottesville, VA 22904 USA
关键词
Body sensor networks; causality; information representation; GAIT ANALYSIS; BALANCE; MOTION; MODEL;
D O I
10.1109/JBHI.2016.2589902
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Inertial body sensors have emerged in recent years as an effective tool for evaluating mobility impairment resulting from various diseases, disorders, and injuries. For example, body sensors have been used in 6-min walk (6 MW) tests for multiple sclerosis (MS) patients to identify gait features useful in the study, diagnosis, and tracking of the disease. However, most studies to date have focused on features localized to the lower or upper extremities and do not provide a holistic assessment of mobility. This paper presents a causality analysis method focused on the coordination between extremities to identify subtle whole-body mobility impairment that may aid disease diagnosis. This method was developed for and utilized in an MS pilot study with 41 subjects (28 persons with MS (PwMS) and 13 healthy controls) performing 6 MW tests. Compared with existing methods, the causality analysis provided better discrimination between healthy controls and PwMS and a deeper understanding of MS disease impact on mobility.
引用
收藏
页码:1273 / 1280
页数:8
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