VALIDATION OF THE 5DT DATA GLOVE FOR THE ASSESSMENT OF HAND MOVEMENT AMPLITUDE IN HEALTHY SUBJECTS

Introduction

Finger and hand movements are fundamental in many daily-life activities and many studies focus on the assessment of neural correlates of hand tasks using functional magnetic resonance imaging (fMRI) [ 1 ]. However, when task-based fMRI investigates the neural correlates of hand movements, it would be important to contextually measuring motor performance, considering that brain activity is strictly connected to movement-dependent modifications [ 2 ]. The 5DT Data Glove is an MRI-compatible hand motion capture device allowing evaluation of finger movements using optic fibre sensors embedded in a stretch lycra glove.

The aim of this study was to assess the reliability of the 5DT Data Glove in assessment of direction and quantity of movement in open and close hand task (hand tapping).

Methods

Validation study of the 5DT Data Glove movement assessment using a stereophotogrammetric system (BTS, SMART DX 7000) with six optoelectronic cameras as gold standard. Fifteen healthy volunteers wore on their left hand a 5DT Data Glove on which we placed three reflective markers (base and head of the second metacarpal bone and proximal phalanx of the second finger) to allow the assessment of metacarpophalangeal joint movements with the stereophotogrammetric system. Volunteers were asked to perform left hand tapping movements at comfortable (1HZ) and fast (3Hz) speed. Spearman’s correlation coefficient was used to assess the strength of the association between data obtained from 5DT Data Glove and from the stereophotogrammetric system.

Results

We found an overall strong significant positive correlation between data acquired by the two systems during the hand tapping task, both at 1Hz (r=0.79, p<0.001) and 3Hz (r=0.81, p<0.001). Each subject in each condition showed a strong significant positive correlation (r ranging from 0.7 to 0.9; p<0.001).

Discussion and Conclusion

The 5DT Data Glove is a reliable tool for the assessment of hand kinematics in fMRI environment giving the possibility to acquire hand tapping movement parameters fundamental to study the neural mechanisms underlying behavioural data. These data yield the floor to further studies on neural correlates of hand movements.

 

Funding: Italian Ministry of Health grant GR-2018-12366005

REFERENCES

[ 1 ] Witt ST, et al. Functional neuroimaging correlates of finger-tapping task variations: an ALE meta-analysis. Neuroimage. 2008. Doi: 10.1016/j.neuroimage.2008.04.025

[ 2 ] Martinez M, et al. MRI-compatible device for examining brain activation related to stepping. IEEE Trans Med Imaging. 2014. Doi: 10.1109/TMI.2014.2301493