T1 - Skill assessment in upper limb myoelectric prosthesis users

Conventional myoelectric control schemes use an amplitude measure at each electrode site (such as the root-mean-square or mean absolute value of the EMG) to quantify the intensity of contraction in the underlying muscles. Control is achieved by mapping this activity to the required prosthetic function; therefore, it is desirable that these muscles be functionally related to the functions that are to be restored. If physiologically appropriate muscles are available to restore lost function, the EMG can be used intuitively, such as when a person with transhumeral amputation controls a prosthetic elbow by using the residual biceps and triceps. In the absence of physiologically appropriate musculature, substitutions must be used, such as using the wrist flexors/extensors to control a hand. If more than one device is to be used, mode switching is often the only strategy (using a hardware switch or co-contraction) to divert control to an elbow, wrist, or hand. This method of control is, however, slow and counterintuitive.

T1 - Tactile feedback for myoelectric forearm prostheses

ArmElbowi-LIMB™LTI Boston Digital Arm™ SystemMyoelectricProsthesisUtah Arm Wrist

KW - myoelectric forearm prostheses

The use of myoelectric upper extremity prosthetic devices is considered medically necessary when ALL of the following criteria have been met:

A myoelectric-controlled prosthesis may be a good choice if you:

The use of myoelectric upper extremity prosthetic devices is considered not medically necessary when any of the criteria above are not met.

DynamicArm can be combined with other myoelectric prosthetic components from Ottobock, such as:

Emily Von Dollen with her Myoelectric Prosthetic Hand in use

Comparison of (a) six feature sets using linear discriminant analysis (LDA) classifier and (b) five classifiers using autoregressive (AR) feature set. Source: Reprinted with permission of IEEE from Har-grove LJ, Englehart K, Hudgins B. A comparison of surface and intra-muscular myoelectric signal classification. IEEE Trans Biomed Eng. 2007;54(5):847???53. .

What is a Myoelectric prosthesis

During the pretest prior to the learning sessions, SHAP was assessed to establish the baseline skill of the participants in both the experimental groups and the control group. After the last learning session, SHAP was administered again to determine the improvement of skills in the posttest. To determine the effect of learning over a longer period in the experimental group, two retention tests were assessed (see Table for the experimental design). The control group only performed the first two SHAP tests, with the same time in between them as the pretest and posttest of the experimental group. This setup was chosen because SHAP is not validated yet for prosthesis users, and the control group served to examine the learning effect of performing SHAP twice.

04/01/2018 · Myoelectric Prostheses Offer Advantages

Ultimately, the most meaningful assessment of prosthetic control is an evaluation of the function that a user derives from the device. Several tests of prosthetic function have been developed and are widely used for conventional prosthetics [42-47]. These tests are largely qualitative and are intended to measure skill and efficacy during functional tasks. Given the commercially available prosthetic options, most have evolved to be primarily intended for hand manipulation, not multiarticulated tasks involving positioning and orienting a hand using powered wrist, elbow, and shoulder devices. Moreover, they require that a user be fitted with a prosthesis, so conducting these tests on subjects before fitting is not possible. The qualitative nature of the tests presents a challenge when one is trying to develop quantitative metrics for control performance. These tests are affected as much by the capabilities of the prosthetic devices; the fit of the socket; and the opinion, skill, and experience of the admitting clinician as they are by the performance of the control system. For these reasons, EMG pattern recognition has been measured instead by offline metrics (largely classification accuracy) and, only more recently, by real-time tests.