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Mary Ann Liebert, Journal of Neurotrauma, 6(34), p. 1141-1148, 2017

DOI: 10.1089/neu.2016.4583

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Multi-Day Recordings of Wearable Sensors Are Valid and Sensitive Measures of Function and Independence in Human Spinal Cord Injury

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Wearable sensor assessment tools have proven to be reliable in measuring function in normal and impaired movement disorders during well-defined assessment protocols. While such assessments can provide valid and sensitive measures of upper limb activity in spinal cord injury (SCI), no assessment tool has yet been introduced into unsupervised daily recordings to complement clinical assessments during rehabilitation. The objective of this study was to measure the overall amount of upper-limb activity in subjects with acute SCI using wearable sensors and relate this to lesion characteristics, independence, and function. The overall amount of upper extremity activity counts, measures of wheeling (speed and distance), and limb-use laterality were measured in 30 in-patients with an acute cervical or thoracic SCI three months after injury. The findings were related to the international standards for neurological classification of SCI, the spinal cord independence measure, and the upper extremity motor scores of the Graded and Redefined Assessment of Strength, Sensibility, and Prehension. Overall upper extremity activity counts were successfully recorded in all patients and correlated with the neurological level of injury and independence. Clinical measures of proximal muscle strength were related to overall activity count and peak velocity of wheeling. Compared with paraplegics, tetraplegics showed significantly lower activity counts and increased limb-use laterality. This is the first cross-sectional study showing the feasibility and clinical value of sensor recordings during unsupervised daily activities in rehabilitation. The strong relationship between sensor-based measures and clinical outcomes supports the application of such technology to assess and track changes in function during rehabilitation and in clinical trials.