Across-subject calibration of an instrumented glove to measure hand movement for clinical purposes

Abstract

Motion capture of all degrees of freedom of the hand collected during performance of daily living activities remains challenging. Instrumented gloves are an attractive option because of their higher ease of use. However, subject-specific calibration of gloves is lengthy and has limitations for individuals with disabilities. Here, a calibration procedure is presented, consisting in the recording of just a simple hand position so as to allow capture of the kinematics of 16 hand joints during daily life activities even in case of severe injured hands. 'across-subject gains' were obtained by averaging the gains obtained from a detailed subject-specific calibration involving 44 registrations that was repeated three times on multiple days to 6 subjects. In additional 4 subjects, joint angles that resulted from applying the 'across-subject calibration' or the subject-specific calibration were compared. Global errors associated with the 'across-subject calibration' relative to the detailed, subjectspecific protocol were small (bias: 0.49º; precision: 4.45º) and comparable to those that resulted from repeating the detailed protocol with the same subject on multiple days (0.36º; 3.50º). Furthermore, in one subject, performance of the 'across-subject calibration' was directly compared to another fast calibration method, expressed relative to a videogrammetric protocol as a gold-standard, yielding better results.

A large calibrated database of hand movements and grasps kinematics

“…Calibration is required to keep into account some issues related to datagloves, such as non-linearities. Therefore, joint angles were computed by transforming the raw data according to specific gain values computed on the basis of a post-processing calibration protocol 17 that was recorded for 10 subjects. The protocol consists of recording 65 poses and guided movements to obtain the sensor gains and some corrections to cross-coupling effects for specific anatomical angles.…”

“…Third, usually only postural movements were considered, without taking into account the entire movement, while "reach to grasp" and release are important phases in grasps modelling. Finally, most studies are based on raw instrumented glove data, which do not provide the linear outputs required to obtain reliable joint angles and can invalidate kinematic models obtained without a specific and accurate calibration method 16,17 .…”

“…A recently presented calibration method assures the possibility to calibrate the kinematic data recorded with a data glove in post-processing 17 . The method was described having a reasonable maximum precision error (below 5 degrees), thus it can improve the accuracy with which hand kinematics and anatomical angles are quantified.…”

“…The 77 subjects performed 40 hand movements and grasps plus rest, leading to our knowledge to the biggest hand kinematics dataset currently available. To obtain the hand anatomical angles, an across-subject calibration procedure 17 was applied.…”

A Three-dimensional Finger Motion Measurement System of a Thumb and an Index Finger Without a Calibration Process

“…Therefore, the calibration process which maps the sensor signal to actual finger joint angle is required. As an extreme case, Cyberglove may require up to 44 different poses or guided movements [14].…”