Francois Martel

EMG-to-force modeling for multiple fingers

We provide a preliminary report on work to relate the EMG activity from forearm flexors and extensors to the flexion-extension forces generated at the finger tips during constant-posture, slowly force-varying contractions. EMG electrode arrays (up to 64 channels) were applied over the flexor and, separately, extensor musculature of the forearm. Spatial filters were used to create derived EMG channels that were then related to finger tip force (via least squares models). Preliminary results identify the “pinky” finger as having the most independent EMG-force control, with moderate control available from some combinations of the other fingers.

EMG-force estimation for multiple fingers

Electromyogram (EMG) activity from the extensor and flexor muscles of the forearm was sensed with high-density surface electrode arrays and related to the force produced at the four fingertips during constant-posture, slowly force-varying contractions from three healthy subjects. Various electrode montages (spatial filters) and number of electrodes used in the system identification were studied. Average errors were small, ranging from 4.21 to 8.10 %MVCF (flexion maximum voluntary contraction), with errors trending lower when more EMG channels were used and when a monopolar electrode montage was selected. Results are supportive that multiple degrees of freedom of proportional control information are available from the surface EMG of the forearm, at least in intact subjects. Applications for future study include the control of prosthetic upper limb devices in amputees.

Fingertip force estimation from forearm muscle electrical activity

Existing commercial hand prostheses can be controlled from the electrical activity (electromyogram or EMG) of remnant muscle tissue within the forearm, but are limited in function to one degree of freedom of proportional control. In a pilot study (N=3 subjects), we used least squares estimation to identify a model between forearm electrical activity recorded by high-resolution (64 channel) electrode arrays (applied over the flexor and, separately, extensor muscles of the forearm) to force in the four fingertips. Average errors ranged from 4.21 to 10.20 %MVCF (flexion maximum voluntary contraction), depending on the muscle contraction task performed, number of EMG electrodes in the model and the electrode montage selected. Results suggest that, at least for intact subjects, 2-4 degrees of freedom of proportional control are available from the EMG signals of the forearm.

EMG-torque estimation of constant-posture, quasi-constant-torque contractions at varied joint angles

This paper describes an experimental study which relates the simultaneous biceps/triceps surface electromyogram (EMG) of 12 subjects to elbow torque at seven joint angles during constant-posture, quasi-constant-torque contractions. Advanced EMG amplitude (EMGσ) estimation processors were investigated, and an EMG-torque model considering agonist and antagonist co-contractions was evaluated at each joint angle. Preliminary results show that advanced (i.e., whitened, multiple-channel) EMGσ processors lead to improved joint torque estimation and that the EMGσ torque relationship may only change by a scaling factor as a function of joint angle.

Hermitian Splines for Modeling Biological Soft Tissue Systems That Exhibit Nonlinear Force-Elongation Curves

Numerical simulation of soft tissue mechanical properties is a critical step in developing valuable biomechanical models of live organisms. A cubic Hermitian spline optimization routine is proposed in this paper to model nonlinear experimental force-elongation curves of soft tissues, in particular when modeled as lumped elements. Boundary conditions are introduced to account for the positive definiteness and the particular curvature of the experimental curve to be fitted. The constrained least-square routine minimizes user intervention and optimizes fitting of the experimental data across the whole fitting range. The routine provides coefficients of a Hermitian spline or corresponding knots that are compatible with a number of constraints that are suitable for modeling soft tissue tensile curves. These coefficients or knots may become inputs to user-defined component properties of various modeling software. Splines are particularly advantageous over the well-known exponential model to account for the traction curve flatness at low elongations and to allow for more flexibility in the fitting process. This is desirable as soft tissue models begin to include more complex physical phenomena.