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Friedman, J., Amiaz, A., & Korman, M. (2022). The online and offline effects of changing movement timing variability during training on a finger-opposition task. Sci Rep, 12(1), 13319.
Abstract: In motor learning tasks, there is mixed evidence for whether increased task-relevant variability in early learning stages leads to improved outcomes. One problem is that there may be a connection between skill level and motor variability, such that participants who initially have more variability may also perform worse on the task, so will have more room to improve. To avoid this confound, we experimentally manipulated the amount of movement timing variability (MTV) during training to test whether it improves performance. Based on previous studies showing that most of the improvement in finger-opposition tasks comes from optimizing the relative onset time of the finger movements, we used auditory cues (beeps) to guide the onset times of sequential movements during a training session, and then assessed motor performance after the intervention. Participants were assigned to three groups that either: (a) followed a prescribed random rhythm for their finger touches (Variable MTV), (b) followed a fixed rhythm (Fixed control MTV), or (c) produced the entire sequence following a single beep (Unsupervised control MTV). While the intervention was successful in increasing MTV during training for the Variable group, it did not lead to improved outcomes post-training compared to either control group, and the use of fixed timing led to significantly worse performance compared to the Unsupervised control group. These results suggest that manipulating MTV through auditory cues does not produce greater learning than unconstrained training in motor sequence tasks.
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Krasovsky, T., Weiss, P. L., Zuckerman, O., Bar, A., Keren-Capelovitch, T., & Friedman, J. (2020). DataSpoon: Validation of an Instrumented Spoon for Assessment of Self-Feeding. Sensors (Basel), 20(7).
Abstract: Clinically feasible assessment of self-feeding is important for adults and children with motor impairments such as stroke or cerebral palsy. However, no validated assessment tool for self-feeding kinematics exists. This work presents an initial validation of an instrumented spoon (DataSpoon) developed as an evaluation tool for self-feeding kinematics. Ten young, healthy adults (three male; age 27.2 +/- 6.6 years) used DataSpoon at three movement speeds (slow, comfortable, fast) and with three different grips: “natural”, power and rotated power grip. Movement kinematics were recorded concurrently using DataSpoon and a magnetic motion capture system (trakSTAR). Eating events were automatically identified for both systems and kinematic measures were extracted from yaw, pitch and roll (YPR) data as well as from acceleration and tangential velocity profiles. Two-way, mixed model Intraclass correlation coefficients (ICC) and 95% limits of agreement (LOA) were computed to determine agreement between the systems for each kinematic variable. Most variables demonstrated fair to excellent agreement. Agreement for measures of duration, pitch and roll exceeded 0.8 (excellent agreement) for >80% of speed and grip conditions, whereas lower agreement (ICC < 0.46) was measured for tangential velocity and acceleration. A bias of 0.01-0.07 s (95% LOA [-0.54, 0.53] to [-0.63, 0.48]) was calculated for measures of duration. DataSpoon enables automatic detection of self-feeding using simple, affordable movement sensors. Using movement kinematics, variables associated with self-feeding can be identified and aid clinical reasoning for adults and children with motor impairments.
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