Extrusion-based 3D Bioprinting of Bioactive and Piezoelectric Scaffolds for Treating Critical Soft Tissue Wounds.

OBJECTIVE: This study focuses on developing bioactive piezoelectric scaffolds that could deliver bioelectrical cues to potentially treat injuries to soft tissues such as skeletal muscles and promote muscle regeneration. APPROACH: To address the underexplored aspect of bioelectrical cues in skeletal muscle tissue engineering (SMTE), we developed piezoelectric bioinks based on natural bioactive materials such as alginate, gelatin, and chitosan. Extrusion-based 3D bioprinting was utilized to develop scaffolds that mimic muscle stiffness and generate electrical stimulation when subjected to forces. The biocompatibility of these scaffolds was tested with C2C12 muscle cell line. RESULTS: The bioinks demonstrated suitable rheological properties for 3D bioprinting, resulting in high-resolution composite alginate-gelatin-chitosan scaffolds with good structural fidelity. The scaffolds exhibited a 42-60 kPa stiffness, similar to muscles. When a controlled force of 5 N was applied to the scaffolds at a constant frequency of 4 Hz, they generated electrical fields and impulses (charge), indicating their suitability as a standalone scaffold to generate electrical stimulation and instill bioelectrical cues in the wound region. The cell viability and proliferation test results confirm the scaffold's biocompatibility with C2C12s and the benefit of piezoelectricity in promoting muscle cell growth kinetics. Our study indicates that our piezoelectric bioinks and scaffolds offer promise as autonomous electrical stimulation-generating regenerative therapy for SMTE. INNOVATION: A novel approach for treating skeletal muscle wounds was introduced by developing a bioactive electroactive scaffold capable of autonomously generating electrical stimulation without stimulators and electrodes. This scaffold offers a unique approach to enhancing skeletal muscle regeneration through bioelectric cues, addressing a major gap in the SMTE, i.e., fibrotic tissue formation due to delayed muscle regeneration. CONCLUSION: A piezoelectric scaffold was developed, providing a promising solution for promoting skeletal muscle regeneration. This development can potentially address skeletal muscle injuries and offer a unique approach to facilitating skeletal muscle wound healing.

Early evaluation of a powered transfemoral prosthesis with force-modulated impedance control and energy regeneration.

Individuals with an above-knee (AK) amputation typically use passive prostheses, whether reactive (microprocessor) or purely mechanical. Though sufficient for walking, these solutions lack the positive power generation observed in able-bodied individuals. Active (powered) prostheses can provide positive power but suffer complex control and limited energy storage capacities. These shortcomings motivate the development of an active prosthesis implementing a novel impedance controller design with energy regeneration. The controller requires only five tuning parameters that are intuitive to adjust in contrast to the current standard-finite state machine impedance scheduling of up to 45 gains. This simplification is uniquely achieved by modulating knee joint impedance by axial shank force. Furthermore, the proposed control approach introduces analytical guidance for impedance tuning to purposely integrate energy regeneration; specifically, a precise amount of negative damping is injected into the joint. A pilot study conducted with a volunteer with an AK amputation walking at three distinct speeds and at continually self-selected varying speeds demonstrated the adaptability of the controller to changes in speed. Self-powered operation was attained for all trials despite low mechanical component efficiencies. These early results suggest the efficacy of simplifying impedance control tuning and fusing control and energy regeneration in transfemoral prostheses.

Targeted muscle effort distribution with exercise robots: Trajectory and resistance effects.

The objective of this work is to relate muscle effort distributions to the trajectory and resistance settings of a robotic exercise and rehabilitation machine. Muscular effort distribution, representing the participation of each muscle in the training activity, was measured with electromyography sensors (EMG) and defined as the individual activation divided by the total muscle group activation. A four degrees-of-freedom robot and its impedance control system are used to create advanced exercise protocols whereby the user is asked to follow a path against the machine's neutral path and resistance. In this work, the robot establishes a zero-effort circular path, and the subject is asked to follow an elliptical trajectory. The control system produces a user-defined stiffness between the deviations from the neutral path and the torque applied by the subject. The trajectory and resistance settings used in the experiments were the orientation of the ellipse and a stiffness parameter. Multiple combinations of these parameters were used to measure their effects on the muscle effort distribution. An artificial neural network (ANN) used part of the data for training the model. Then, the accuracy of the model was evaluated using the rest of the data. The results show how the precision of the model is lost over time. These outcomes show the complexity of the muscle dynamics for long-term estimations suggesting the existence of time-varying dynamics possibly associated with fatigue.

Real-time optimization of an ellipsoidal trajectory orientation using muscle effort with Extremum Seeking Control.

We present an approach for real-time model-free optimization of the orientation of the elliptical trajectory. The performance is evaluated in simulation and experimental stages. Our model-free approach is based on the use of Extremum Seeking Control (ESC) as the real-time optimizer. The experimental stage is performed using a 4 degrees-of-freedom robot and its impedance control system to create advanced exercise protocols whereby the user is asked to follow a path against the machine's neutral path and resistance. Another model-free approach based on the use of the global optimizer Biogeography-based optimization (BBO) was previously reported for simulation results. This last framework has a good performance as a result of exhaustive searches but with a high computational cost limiting its use on real-time experiments. The performance of the ESC approach was validated by comparing the results with those of BBO using five different arm models representing real human arms. In the real-time experiments, muscle activations representing the participation of each muscle in the training activity were measured with electromyography sensors (EMG) and real-time processed from raw signals. The muscle objective can be professionally selected by a therapist to emphasize or de-emphasize certain muscle groups. The robot establishes a zero-effort circular path, and the subject is asked to follow an elliptical trajectory. The control system produces a user-defined stiffness between the deviations from the neutral path and the force/torque applied by the subject. The results show that the framework was able to successfully find the optimal ellipsoidal orientation converging to similar solutions in short period trials of 50 s.

Optimal Mixed Tracking/Impedance Control With Application to Transfemoral Prostheses With Energy Regeneration.

OBJECTIVE: We design an optimal passivity-based tracking/impedance control system for a robotic manipulator with energy regenerative electronics, where the manipulator has both actively and semi-actively controlled joints. The semi-active joints are driven by a regenerative actuator that includes an energy-storing element. METHOD: External forces can have a large influence on energy regeneration characteristics. Impedance control is used to impose a desired relationship between external forces and deviation from reference trajectories. Multi-objective optimization (MOO) is used to obtain optimal impedance parameters and control gains to compromise between the two conflicting objectives of trajectory tracking and energy regeneration. We solve the MOO problem under two different scenarios: 1) constant impedance; and 2) time-varying impedance. RESULTS: The methods are applied to a transfemoral prosthesis simulation with a semi-active knee joint. Normalized hypervolume and relative coverage are used to compare Pareto fronts, and these two metrics show that time-varying impedance provides better performance than constant impedance. The solution with time-varying impedance with minimum tracking error (0.0008 rad) fails to regenerate energy (loses 9.53 J), while a solution with degradation in tracking (0.0452 rad) regenerates energy (gains 270.3 J). A tradeoff solution results in fair tracking (0.0178 rad) and fair energy regeneration (131.2 J). CONCLUSION: Our experimental results support the possibility of net energy regeneration at the semi-active knee joint with human-like tracking performance. SIGNIFICANCE: The results indicate that advanced control and optimization of ultracapacitor-based systems can significantly reduce power requirements in transfemoral prostheses.

Optimal design and control of an electromechanical transfemoral prosthesis with energy regeneration.

In this paper, we present the design of an electromechanical above-knee active prosthesis with energy storage and regeneration. The system consists of geared knee and ankle motors, parallel springs for each motor, an ultracapacitor, and controllable four-quadrant power converters. The goal is to maximize the performance of the system by finding optimal controls and design parameters. A model of the system dynamics was developed, and used to solve a combined trajectory and design optimization problem. The objectives of the optimization were to minimize tracking error relative to human joint motions, as well as energy use. The optimization problem was solved by the method of direct collocation, based on joint torque and joint angle data from ten subjects walking at three speeds. After optimization of controls and design parameters, the simulated system could operate at zero energy cost while still closely emulating able-bodied gait. This was achieved by controlled energy transfer between knee and ankle, and by controlled storage and release of energy throughout the gait cycle. Optimal gear ratios and spring parameters were similar across subjects and walking speeds.