Multiple-input single-output closed-loop isometric force control using asynchronous intrafascicular multi-electrode stimulation.

Although asynchronous intrafascicular multi-electrode stimulation (IFMS) can evoke fatigue-resistant muscle force, a priori determination of the necessary stimulation parameters for precise force production is not possible. This paper presents a proportionally-modulated, multiple-input single-output (MISO) controller that was designed and experimentally validated for real-time, closed-loop force-feedback control of asynchronous IFMS. Experiments were conducted on anesthetized felines with a Utah Slanted Electrode Array implanted in the sciatic nerve, either acutely or chronically ( n = 1 for each).

Muscle-selective block using intrafascicular high-frequency alternating current.

High-frequency alternating current (HFAC) applied to a peripheral nerve can reversibly block skeletal muscle contractions. We evaluated the ability of HFAC delivered via intrafascicular electrodes to selectively block activation of targeted muscles without affecting activation of other muscles. Utah slanted electrode arrays (USEAs) were implanted into the sciatic nerves of five cats, and HFAC was delivered to individual USEA electrodes.

Selective and graded recruitment of cat hamstring muscles with intrafascicular stimulation.

The muscles of the hamstring group can produce different combinations of hip and knee torque. Thus, the ability to activate the different hamstring muscles selectively is of particular importance in eliciting functional movements such as stance and gait in a person with spinal cord injury. We investigated the ability of intrafascicular stimulation of the muscular branch of the sciatic nerve to recruit the feline hamstring muscles in a selective and graded fashion.

Automated stimulus-response mapping of high-electrode-count neural implants.

Over the past decade, research in the field of functional electrical stimulation (FES) has led to a new generation of high-electrode-count (HEC) devices that offer increasingly selective access to neural populations. Incorporation of these devices into research and clinical applications, however, has been hampered by the lack of hardware and software platforms capable of taking full advantage of them. In this paper, we present the first generation of a closed-loop FES platform built specifically for HEC neural interface devices.