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Sensors (Basel). 2018 Aug 22;18(9). pii: E2767. doi: 10.3390/s18092767.

Using Inertial Measurement Units and Electromyography to Quantify Movement during Action Research Arm Test Execution.

Author information

1
Faculty of Electrical Engineering, University of Ljubljana, Tržaška cesta 25, 1000 Ljubljana, Slovenia. eva.repnik@fe.uni-lj.si.
2
Faculty of Health Sciences, University of Ljubljana, Zdravstvena pot 5, 1000 Ljubljana, Slovenia. urska.puh@zf.uni-lj.si.
3
The University Rehabilitation Institute, Republic of Slovenia, Linhartova 51, 1000 Ljubljana, Slovenia. nika.goljar@ir-rs.si.
4
Faculty of Electrical Engineering, University of Ljubljana, Tržaška cesta 25, 1000 Ljubljana, Slovenia. marko.munih@robo.fe.uni-lj.si.
5
Faculty of Electrical Engineering, University of Ljubljana, Tržaška cesta 25, 1000 Ljubljana, Slovenia. matjaz.mihelj@robo.fe.uni-lj.si.

Abstract

In patients after stroke, ability of the upper limb is commonly assessed with standardised clinical tests that provide a complete upper limb assessment. This paper presents quantification of upper limb movement during the execution of Action research arm test (ARAT) using a wearable system of inertial measurement units (IMU) for kinematic quantification and electromyography (EMG) sensors for muscle activity analysis. The test was executed with each arm by a group of healthy subjects and a group of patients after stroke allocated into subgroups based on their clinical scores. Tasks were segmented into movement and manipulation phases. Each movement phase was quantified with a set of five parameters: movement time, movement smoothness, hand trajectory similarity, trunk stability, and muscle activity for grasping. Parameters vary between subject groups, between tasks, and between task phases. Statistically significant differences were observed between patient groups that obtained different clinical scores, between healthy subjects and patients, and between the unaffected and the affected arm unless the affected arm shows normal performance. Movement quantification enables differentiation between different subject groups within movement phases as well as for the complete task. Spearman's rank correlation coefficient shows strong correlations between patient's ARAT scores and movement time as well as movement smoothness. Weak to moderate correlations were observed for parameters that describe hand trajectory similarity and trunk stability. Muscle activity correlates well with grasping activity and the level of grasping force in all groups.

KEYWORDS:

ARAT; electromyography; inertial measurement unit; quantification; stroke; upper-limb movement

PMID:
30135413
PMCID:
PMC6164634
DOI:
10.3390/s18092767
[Indexed for MEDLINE]
Free PMC Article

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