Dynamic Measurement Assessments of Sensory Gloves Based on Resistive Flex Sensors and Inertial Measurement Units

• Published in: IEEE transactions on instrumentation and measurement Vol. 72; p. 1
• Main Authors: Saggio, Giovanni, Calado, Alexandre, Errico, Vito, Lin, Bor-Shing, Lee, I-Jung
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Calibration; Correlation coefficients; Data acquisition; Feasibility studies; Gloves; inertial measurement unit; Inertial platforms; Inertial sensing devices; Light emitting diodes; Measuring instruments; motion measurements; Reliability; Reproducibility; resistive flex sensor; Robot sensing systems; Sensors; Sensory gloves; Testing; Thumb; Wearable electronics
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2023.3265102

Sensory gloves are devices capable of measuring finger movements and are useful in numerous applications, many of which require real-time data acquisition. However, the procedures explored in the literature to assess measurement repeatability and reliability mainly rely on static or quasi-static conditions. To overcome this limitation, here we propose a testing procedure for assessing measurements under dynamic conditions (slow, medium, and rapid finger joint movements). To this aim, we used two sensory gloves, one based on resistive flex sensors (RFSs) and another based on inertial measurement units (IMUs) - as two of the most adopted types. Our study demonstrated the feasibility of measuring dynamic finger movements and the differences in dynamic measurement repeatability and reliability between RFS- and IMU-based gloves when considering the angles (in degrees) of each finger joint. The RFS-based glove scored with an average range ± standard deviation (SD) of 6.84 ± 2.77°, and an intraclass correlation coefficient (ICC) of 0.77 ± 0.14, whereas the IMU-based glove scored with an average range of 8.49 ± 2.72°, and an ICC of 0.75 ± 0.14. Both gloves exhibited better repeatability and reliability at the slowest speed, with the RFS-based glove having an higher repeatability than the IMU-based one ( p < 0.001). Moreover, when compared to previous studies, the results (in terms of reliability and repeatability) here obtained under dynamic conditions are comparable to those obtained under static or quasi-static conditions. In summary, our results indicate that both proposed sensory gloves are suitable for most applications that require dynamic interactions.