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. 2018 May 13;18(5):1545.
doi: 10.3390/s18051545.

Design of an Inertial-Sensor-Based Data Glove for Hand Function Evaluation

Bor-Shing Lin  1 , I-Jung Lee  2   3 , Shu-Yu Yang  4 , Yi-Chiang Lo  5 , Junghsi Lee  6 , Jean-Lon Chen  7   8   9
Affiliations

Design of an Inertial-Sensor-Based Data Glove for Hand Function Evaluation

Bor-Shing Lin et al. Sensors (Basel). .

Abstract

Capturing hand motions for hand function evaluations is essential in the medical field. Various data gloves have been developed for rehabilitation and manual dexterity assessments. This study proposed a modular data glove with 9-axis inertial measurement units (IMUs) to obtain static and dynamic parameters during hand function evaluation. A sensor fusion algorithm is used to calculate the range of motion of joints. The data glove is designed to have low cost, easy wearability, and high reliability. Owing to the modular design, the IMU board is independent and extensible and can be used with various microcontrollers to realize more medical applications. This design greatly enhances the stability and maintainability of the glove.

Keywords: data glove; inertial sensor; joint measurement; motion capture; rehabilitation.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
System architecture of data glove system.
Figure 2
Figure 2
IMU positions on the data glove.
Figure 3
Figure 3
MCM components.
Figure 4
Figure 4
Bluetooth module and wireless adapter board.
Figure 5
Figure 5
(a) Side view of FFCB and (b) FFCB.
Figure 6
Figure 6
Prototype of the data glove.
Figure 7
Figure 7
Flowchart of program on host system.
Figure 8
Figure 8
Well-calibrated raw data from the magnetometer. The center of the distribution is at (0, 0, 0) and the radius is 400 mG.
Figure 9
Figure 9
Direction of IMUs.
Figure 10
Figure 10
Position of ROMs and IMUs.
Figure 11
Figure 11
Validation results of accelerometer data.
Figure 12
Figure 12
Verification results of gyro data.
Figure 13
Figure 13
Verification results of magnetometer data.
Figure 14
Figure 14
The data of magnetometer before and after calibration.
Figure 15
Figure 15
Self-made measurement platform for measuring finger angle.
Figure 16
Figure 16
Self-made measurement platform for measuring finger angle. The angles are set to change in different intervals: (a) interval 0°–30°; (b) interval 0°–60°; and (c) interval 0°–90°.
Figure 17
Figure 17
The mean error of the static angle for each minute.
Figure 18
Figure 18
The real-time Unity program for visualizing the hand’s movement.
See this image and copyright information in PMC

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