Additive Manufacturing of Degradable Materials via Ring-Opening Metathesis Polymerization (ROMP).

Thermoset materials comprise a significant proportion of high-performance plastics due to their shape permanence and excellent thermal and mechanical properties. However, these properties come at the expense of degradability. Here, we show for the first time that the industrial thermoset polydicyclopentadiene (PDCPD) can be additively manufactured (AM) with degradable 2,3-dihydrofuran (DHF) linkages using a photochemical approach. Treatment of the manufactured objects with acid results in rapid degradation to soluble byproducts. This work highlights the potential of ring-opening metathesis polymerization (ROMP) chemistry to create degradable materials amenable to advanced manufacturing processes.

Upper Limb Prosthesis Control for High-Level Amputees via Myoelectric Recognition of Leg Gestures.

Recognition of motion intent via surface electromyography (EMG) has become increasingly practical for prosthesis control, but lacking residual muscle sites remains a major obstacle to its use by high-level amputees. Currently, there are few approaches to upper limb prosthesis control for individuals with amputations proximal to the elbow, all of which suffer from one or more of three primary problems: invasiveness, the need for intensive training, and lacking functionality. Using surface EMG sensors placed on the lower leg and a natural mapping between degrees of freedom of the leg and the arm, we tested a noninvasive control approach by which high-level amputees could control prosthetic elbow, wrist, and hand movements with minimal training. In this paper, we used able-bodied subjects to facilitate a direct comparison between control using intact arm and leg muscles. First, we found that foot gestures could be classified offline using time domain features and linear discriminant analysis with accuracy comparable to an equivalent system for recognizing arm movements. Second, we used the target achievement control test to evaluate real-time control performance in three and four degrees of freedom. After approximately 20 min of training, subjects tended to perform the task as well with the leg as with intact arm muscles, and performance overall was comparable to other control methods.

Learning to modulate the partial powers of a single sEMG power spectrum through a novel human-computer interface.

New human-computer interfaces that use bioelectrical signals as input are allowing study of the flexibility of the human neuromuscular system. We have developed a myoelectric human-computer interface which enables users to navigate a cursor to targets through manipulations of partial powers within a single surface electromyography (sEMG) signal. Users obtain two-dimensional control through simultaneous adjustments of powers in two frequency bands within the sEMG spectrum, creating power profiles corresponding to cursor positions. It is unlikely that these types of bioelectrical manipulations are required during routine muscle contractions. Here, we formally establish the neuromuscular ability to voluntarily modulate single-site sEMG power profiles in a group of naïve subjects under restricted and controlled conditions using a wrist muscle. All subjects used the same pre-selected frequency bands for control and underwent the same training, allowing a description of the average learning progress throughout eight sessions. We show that subjects steadily increased target hit rates from 48% to 71% and exhibited greater control of the cursor's trajectories following practice. Our results point towards an adaptable neuromuscular skill, which may allow humans to utilize single muscle sites as limited general-purpose signal generators. Ultimately, the goal is to translate this neuromuscular ability to practical interfaces for the disabled by using a spared muscle to control external machines.

Real-time evaluation of a myoelectric control method for high-level upper limb amputees based on homologous leg movements.

Electromyography-based gesture classification methods for control of advanced upper limb prostheses are limited either to individuals with amputations distal to the elbow or to those willing to undergo targeted muscle reinnervation surgery. Based on the natural similarity between gestures of the lower leg and the arm and on established methods in electromyography-based gesture classification, we propose a noninvasive system with which users control an upper limb prosthesis via homologous movements of the leg and foot. Eight inexperienced able-bodied subjects controlled a simulated robotic arm in a target achievement control (TAC) task with command of up to four degrees of freedom toward targets requiring one motion class. All subjects performed the task with analogous electromyography recording configurations on both the leg and the arm (as a benchmark), achieving slightly better performance with leg control overall. Only a brief demonstration of the arm-leg gesture mapping was necessary for subjects to perform the task, establishing the minimal training time required to begin using the control scheme. Our findings indicate that electromyography-based recognition of leg gestures may be a viable noninvasive prosthesis control option for high-level amputees.

Paralyzed subject controls telepresence mobile robot using novel sEMG brain-computer interface: case study.

Here we demonstrate the use of a new singlesignal surface electromyography (sEMG) brain-computer interface (BCI) to control a mobile robot in a remote location. Previous work on this BCI has shown that users are able to perform cursor-to-target tasks in two-dimensional space using only a single sEMG signal by continuously modulating the signal power in two frequency bands. Using the cursor-to-target paradigm, targets are shown on the screen of a tablet computer so that the user can select them, commanding the robot to move in different directions for a fixed distance/angle. A Wifi-enabled camera transmits video from the robot's perspective, giving the user feedback about robot motion. Current results show a case study with a C3-C4 spinal cord injury (SCI) subject using a single auricularis posterior muscle site to navigate a simple obstacle course. Performance metrics for operation of the BCI as well as completion of the telerobotic command task are developed. It is anticipated that this noninvasive and mobile system will open communication opportunities for the severely paralyzed, possibly using only a single sensor.

Piezoelectric ribbons printed onto rubber for flexible energy conversion.

The development of a method for integrating highly efficient energy conversion materials onto stretchable, biocompatible rubbers could yield breakthroughs in implantable or wearable energy harvesting systems. Being electromechanically coupled, piezoelectric crystals represent a particularly interesting subset of smart materials that function as sensors/actuators, bioMEMS devices, and energy converters. Yet, the crystallization of these materials generally requires high temperatures for maximally efficient performance, rendering them incompatible with temperature-sensitive plastics and rubbers. Here, we overcome these limitations by presenting a scalable and parallel process for transferring crystalline piezoelectric nanothick ribbons of lead zirconate titanate from host substrates onto flexible rubbers over macroscopic areas. Fundamental characterization of the ribbons by piezo-force microscopy indicates that their electromechanical energy conversion metrics are among the highest reported on a flexible medium. The excellent performance of the piezo-ribbon assemblies coupled with stretchable, biocompatible rubber may enable a host of exciting avenues in fundamental research and novel applications.