Changes in performance over time while learning to use a myoelectric prosthesis

Abstract

Background: Training increases the functional use of an upper limb prosthesis, but little is known about how people learn to use their prosthesis. The aim of this study was to describe the changes in performance with an upper limb myoelectric prosthesis during practice. The results provide a basis to develop an evidence-based training program.

Methods: Thirty-one able-bodied participants took part in an experiment as well as thirty-one age- and gender-matched controls. Participants in the experimental condition, randomly assigned to one of four groups, practiced with a myoelectric simulator for five sessions in a two-weeks period. Group 1 practiced direct grasping, Group 2 practiced indirect grasping, Group 3 practiced fixating, and Group 4 practiced a combination of all three tasks. The Southampton Hand Assessment Procedure (SHAP) was assessed in a pretest, posttest, and two retention tests. Participants in the control condition performed SHAP two times, two weeks apart with no practice in between. Compressible objects were used in the grasping tasks. Changes in end-point kinematics, joint angles, and grip force control, the latter measured by magnitude of object compression, were examined.

Results: The experimental groups improved more on SHAP than the control group. Interestingly, the fixation group improved comparable to the other training groups on the SHAP. Improvement in global position of the prosthesis leveled off after three practice sessions, whereas learning to control grip force required more time. The indirect grasping group had the smallest object compression in the beginning and this did not change over time, whereas the direct grasping and the combination group had a decrease in compression over time. Moreover, the indirect grasping group had the smallest grasping time that did not vary over object rigidity, while for the other two groups the grasping time decreased with an increase in object rigidity.

Conclusions: A training program should spend more time on learning fine control aspects of the prosthetic hand during rehabilitation. Moreover, training should start with the indirect grasping task that has the best performance, which is probably due to the higher amount of useful information available from the sound hand.

Figure 1

The myoelectric simulator.

Figure 2

One of the deformable objects, consisting of two plates with a spring in between and Velcro mounted on top.

Figure 3

Illustrative examples of a direct grasp trial with the low-resistance object. Velocity of the hand, hand aperture, and object deformation are plotted against time (A) and against displacement of the hand from start position to the position of the object (B). Dependent variables that are indicated in 4A: a = Reach time; b = Hand open phase; c = Plateau phase; d = Hand close phase; e = Total Grasp time; f = Compression during grasp; g = Compression during manipulation.

Figure 4

Mean (± SD) Index of functionality scores on SHAP for the experimental and the control groups on the different test times: pretest (Tpre), posttest (Tpost), retention test 1 (Rt1) and retention test 2 (Rt2).

Figure 5

Behavior of the different training groups during the grasping tasks. A) The amount of compression of the objects over the sessions for each of the training groups that trained grasping (DG, IG, and COM); B) Total grasping time for each of the training groups for the different object resistances LO, MO, HO, and solid.

Figure 6

The mean course in angles (degrees) of shoulder plane of elevation (SPE), shoulder elevation (SE), elbow flexion (EFl), thorax flexion (TrFl), thorax lateral bend (TrLB) and thorax rotation (TrR) from movement start to end in normalized time for the three types of tasks (direct grasping, indirect grasping, and fixating). The solid lines represent the mean and standard error of the angles on the first session, the dashed lines represent mean and standard error for the fifth session.