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Krasovsky, T., Keren-Capelovitch, T., Friedman, J., & Weiss, P. L. (2021). Self-feeding kinematics in an ecological setting: typically developing children and children with cerebral palsy. IEEE Trans Neural Syst Rehabil Eng, 29, 1462–1469.
Abstract: Assessment of self-feeding kinematics is seldom performed in an ecological setting. In preparation for development of an instrumented spoon for measurement of self-feeding in children with cerebral palsy (CP), the current work aimed to evaluate upper extremity kinematics of self-feeding in young children with typical development (TD) and a small, age-matched group of children with CP in a familiar setting, while eating with a spoon. METHODS: Sixty-five TD participants and six children diagnosed with spastic CP, aged 3-9 years, fed themselves while feeding was measured using miniature three-dimensional motion capture sensors (trakStar). Kinematic variables associated with different phases of self-feeding cycle (movement time, curvature, time to peak velocity and smoothness) were compared across age-groups in the TD sample and between TD children and those with CP. RESULTS: Significant between-age group differences were identified in movement times, time to peak velocity and curvature. Children with CP demonstrated slower, less smooth self-feeding movements, potentially related to activity limitations. CONCLUSIONS: The identified kinematic variables form a basis for implementation of self-feeding performance assessment in children of different ages, including those with CP, which can be deployed via an instrumented spoon.
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.