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. 2023 Jan 19;23(3):1158.
doi: 10.3390/s23031158.

Comparison of Various Smoothness Metrics for Upper Limb Movements in Middle-Aged Healthy Subjects

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Comparison of Various Smoothness Metrics for Upper Limb Movements in Middle-Aged Healthy Subjects

Nicolas Bayle et al. Sensors (Basel). .

Abstract

Backgound: Metrics for movement smoothness include the number of zero-crossings on the acceleration profile (N0C), the log dimensionless jerk (LDLJ), the normalized averaged rectified jerk (NARJ) and the spectral arc length (SPARC). Sensitivity to the handedness and movement type of these four metrics was compared and correlations with other kinematic parameters were explored in healthy subjects.

Methods: Thirty-two healthy participants underwent 3D upper limb motion analysis during two sets of pointing movements on each side. They performed forward- and backward-pointing movements at a self-selected speed to a target located ahead at shoulder height and at 90% arm length, with and without a three-second pause between forward and backward movements. Kinematics were collected, and smoothness metrics were computed.

Results: LDLJ, NARJ and N0C found backward movements to be smoother, while SPARC found the opposite. Inter- and intra-subject coefficients of variation were lowest for SPARC. LDLJ, NARJ and N0C were correlated with each other and with movement time, unlike SPARC.

Conclusion: There are major differences between smoothness metrics measured in the temporal domain (N0C, LDLJ, NARJ), which depend on movement time, and those measured in the frequency domain, the SPARC, which gave results opposite to the other metrics when comparing backward and forward movements.

Keywords: LDLJ; SPARC; kinematics; motion analysis; pointing task; smoothness metrics.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Experimental set up: starting position and target (left). Representation of reflective markers in Vicon software (right).
Figure 2
Figure 2
Mean value and standard deviation of trajectories (first line) and velocity profiles (second line) for set (A) (with pause) and set (B) (without pause) forward- and backward-pointing movements in the vertical plane (Z) as a function of movement completion (%).
Figure 2
Figure 2
Mean value and standard deviation of trajectories (first line) and velocity profiles (second line) for set (A) (with pause) and set (B) (without pause) forward- and backward-pointing movements in the vertical plane (Z) as a function of movement completion (%).
Figure 3
Figure 3
(A) Differences in smoothness measured with the NARJ across sides, sets (with pause vs. without pause) and movement type (forward vs. backward). (B) Differences in smoothness measured with the Number of Zero Crossings across sides, sets and movement type. (C) Differences in smoothness measured with the LDLJ across sides, sets and movement type. (D) Differences in smoothness measured with the SPARC across sides, sets and movement type; (Mann–Whitney tests). FPM: forward-pointing movement; BPM: backward-pointing movement; D: dominant, ND: non-dominant; * p < 0.05; *** p < 0.01.
Figure 4
Figure 4
First column: Spearman correlations between temporal domain smoothness metrics. Second column: Spearman correlations between SPARC and temporal domain metrics. Third column: Spearman correlations between smoothness metrics and movement duration.

References

    1. Alt Murphy M., Resteghini C., Feys P., Lamers I. An Overview of Systematic Reviews on Upper Extremity Outcome Measures after Stroke. BMC Neurol. 2015;15:29. doi: 10.1186/s12883-015-0292-6. - DOI - PMC - PubMed
    1. Proud E.L., Miller K.J., Bilney B., Balachandran S., McGinley J.L., Morris M.E. Evaluation of Measures of Upper Limb Functioning and Disability in People With Parkinson Disease: A Systematic Review. Arch. Phys. Med. Rehabil. 2015;96:540–551.e1. doi: 10.1016/j.apmr.2014.09.016. - DOI - PubMed
    1. Lamers I., Kelchtermans S., Baert I., Feys P. Upper Limb Assessment in Multiple Sclerosis: A Systematic Review of Outcome Measures and Their Psychometric Properties. Arch. Phys. Med. Rehabil. 2014;95:1184–1200. doi: 10.1016/j.apmr.2014.02.023. - DOI - PubMed
    1. Schwarz A., Kanzler C.M., Lambercy O., Luft A.R., Veerbeek J.M. Systematic Review on Kinematic Assessments of Upper Limb Movements After Stroke. Stroke. 2019;50:718–727. doi: 10.1161/STROKEAHA.118.023531. - DOI - PubMed
    1. Bayle N., Fried J.S. Movement Smoothness Differentiates Voluntary from Parkinsonian Bradykinesia. J. Addict. Res. Ther. 2015;7:1–8. doi: 10.4172/2155-6105.1000264. - DOI

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