Sensors, Vol. 20, Pages 2114: DataSpoon: Validation of an Instrumented Spoon for Assessment of Self-Feeding

Sensors, Vol. 20, Pages 2114: DataSpoon: Validation of an Instrumented Spoon for Assessment of Self-Feeding Sensors doi: 10.3390/s20072114 Authors: Tal Krasovsky Patrice L. Weiss Oren Zuckerman Avihay Bar Tal Keren-Capelovitch Jason Friedman 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 &am...
Source: Sensors - Category: Biotechnology Authors: Tags: Article Source Type: research