Decoding of unimanual and bimanual reach-and-grasp actions from EMG and IMU signals in persons with cervical spinal cord injury

Abstract

Objective: Chronic motor impairments of arms and hands as the consequence of a
cervical spinal cord injury (SCI) have a tremendous impact on activities of daily life.
A considerable number of people however retain minimal voluntary motor control in the
paralyzed parts of the upper limbs that are measurable by electromyography (EMG)
and inertial measurement units (IMUs). An integration into human-machine interfaces
(HMIs) holds promise for reliable grasp intent detection and intuitive assistive device
control.
Approach: We used a multimodal HMI incorporating EMG and IMU data to decode
reach-and-grasp movements of groups of persons with cervical SCI (n=4) and without
(control, n=13). A post-hoc evaluation of control group data aimed to identify optimal
parameters for online, co-adaptive closed-loop HMI sessions with persons with cervical
SCI. We compared the performance of real-time, Random Forest-based movement
versus rest (2 classes) and grasp type predictors (3 classes) with respect to their coadaptation
and evaluated the underlying feature importance maps.
Main results: Our multimodal approach enabled grasp decoding significantly better
than EMG or IMU data alone (p<0.05). We found the 0.25 s directly prior to the first
touch of an object to hold the most discriminative information. Our HMIs correctly
predicted 79.3 ± STD 7.4 (102.7 ± STD 2.3 control group) out of 105 trials with
grand average movement vs. rest prediction accuracies above 99.64% (100% sensitivity)
and grasp prediction accuracies of 75.39 ± STD 13.77% (97.66 ± STD 5.48% control
group). Co-adaption led to higher prediction accuracies with time, and we could
identify adaptions in feature importances unique to each participant with cervical
SCI.
Significance: Our findings foster the development of multimodal and adaptive HMIs
to allow persons with cervical SCI the intuitive control of assistive devices to improve
personal independence.