Combined use of sEMG and accelerometer in hand motion classification considering forearm rotation

Abstract

Hand motion classification using surface electromyography (sEMG) has been widely studied for its applications in upper-limb prosthesis and human-machine interface etc. Pattern-recognition based control methods have many advantages, and the reported classification accuracy can meet the requirements of practical applications. However, the pattern instability of sEMG in actual use limited their real implementations, and limb position variations may be one of the potential factors. In this paper, we give a pilot study of the reverse effect of forearm rotations on hand motion classification, and the results show that the forearm rotations can substantially degrade the classifier's performance: the average intra-position error is only 2.4%, but the average interposition classification error is as high as 44.0%. To solve this problem, we use an extra accelerometer to estimate the forearm rotation angles, and the best combination of sEMG data and accelerometer outputs can reduce the average classification error to 3.3%.

Classification of Muscle Inertial Motion and Electromyographic Activity Integration to Improve Accuracy in Pattern Recognition

“…The experimental protocol design in this study was based on related studies that collected data from individuals with sound limbs, 14,17,23 unilateral transradial limb-absent subjects, 24 and simultaneous measurement of EMG and inertial activities. 6,7,9,19,[25][26][27][28] The independence of movements between individuals and high correlated characteristics of EMG patterns between movements were also taken into consideration when selecting the tasks. 29…”

“…Moreover, several researchers have been using inertial sensors as a complement to the EMG, such as accelerometers and gyroscopes 3,5–8 . These types of sensors were introduced in human-machine interfaces to provide information related to the position of the limb and rotational movements improving the robustness of classification because the position of the limb during muscle contraction can cause changes in the EMG signal 9 . These inertial sensors, however, were never used to measure the pattern of the muscle contraction during different hand movements.…”