Quantification of Finger-Tapping Angle Based on Wearable Sensors

Abstract

Abstract:We propose a novel simple method for quantitative and qualitative finger-tapping assessment based on miniature inertial sensors (3D gyroscopes) placed on the thumb and index-finger. We propose a simplified description of the finger tapping by using a single angle, describing rotation around a dominant axis. The method was verified on twelve subjects, who performed various tapping tasks, mimicking impaired patterns. The obtained tapping angles were compared with results of a motion capture camera system, demonstrating excellent accuracy. The root-mean-square (RMS) error between the two sets of data is, on average, below 4 • , and the intraclass correlation coefficient is, on average, greater than 0.972. Data obtained by the proposed method may be used together with scores from clinical tests to enable a better diagnostic. Along with hardware simplicity, this makes the proposed method a promising candidate for use in clinical practice. Furthermore, our definition of the tapping angle can be applied to all tapping assessment systems.

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“…Studies on hand kinematics capturing have used noncontact-based or wearable technology [ 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 ]. Noncontact-based approaches mainly use cameras or depth-based cameras to capture hand kinematics and analyze continuous hand movements through image processing [ 4 , 6 , 7 ].…”

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“…Several IMU-based data gloves have been proposed [2][3][4][5][6][7]. In 2014, Kortier et al presented a data glove with inertial magnetic sensors to assess hand kinematics [6].…”