Development of a BIONic muscle spindle for prosthetic proprioception

Implants with Sensing Capabilities

Because of the aging human population and increased numbers of surgical procedures being performed, there is a growing number of biomedical devices being implanted each year. Although the benefits of implants are significant, there are risks to having foreign materials in the body that may lead to complications that may remain undetectable until a time at which the damage done becomes irreversible. To address this challenge, advances in implantable sensors may enable early detection of even minor changes in the implants or the surrounding tissues and provide early cues for intervention. Therefore, integrating sensors with implants will enable real-time monitoring and lead to improvements in implant function. Sensor integration has been mostly applied to cardiovascular, neural, and orthopedic implants, and advances in combined implant-sensor devices have been significant, yet there are needs still to be addressed. Sensor-integrating implants are still in their infancy; however, some have already made it to the clinic. With an interdisciplinary approach, these sensor-integrating devices will become more efficient, providing clear paths to clinical translation in the future.

Design of a bio-inspired pneumatic artificial muscle with self-contained sensing

Pneumatic artificial muscles (PAMs) are one of the most famous linear actuators in bio-inspired robotics. They can generate relatively high linear force considering their form factors and weights. Furthermore, PAMs are inexpensive compared with traditional electromagnetic actuators (e.g. DC motors) and also inherently light and compliant. In robotics applications, however, they typically require external sensing mechanisms due to their nonlinear behaviors, which may make the entire mechanical system bulky and complicated, limiting their use in simple systems. This study presents the design and fabrication of a low-cost McKibben-type PAM with a self-contained displacement and force sensing capability that does not require any external sensing elements. The proposed PAM can detect axial contraction force and displacement at the same time. In this study, the design of a traditional McKibben muscle was modified to include an inductive coil surrounding the muscle fibers. Then, a thin, soft silicone layer was coated outside of the muscle to protect and hold the sensing coil on the actuator. This novel design measures coil inductance change to determine the contraction force and the displacement. The process can be applied to a variety of existing McKibben actuator designs without significantly changing the rigidity of the actuator while minimizing the device's footprint.

A Battery-Less, Implantable Neuro-Electronic Interface for Studying the Mechanisms of Deep Brain Stimulation in Rat Models

Although deep brain stimulation (DBS) has been a promising alternative for treating several neural disorders, the mechanisms underlying the DBS remain not fully understood. As rat models provide the advantage of recording and stimulating different disease-related regions simultaneously, this paper proposes a battery-less, implantable neuro-electronic interface suitable for studying DBS mechanisms with a freely-moving rat. The neuro-electronic interface mainly consists of a microsystem able to interact with eight different brain regions bi-directionally and simultaneously. To minimize the size of the implant, the microsystem receives power and transmits data through a single coil. In addition, particular attention is paid to the capability of recording neural activities right after each stimulation, so as to acquire information on how stimulations modulate neural activities. The microsystem has been fabricated with the standard 0.18 μm CMOS technology. The chip area is 7.74 mm (2) , and the microsystem is able to operate with a single supply voltage of 1 V. The wireless interface allows a maximum power of 10 mW to be transmitted together with either uplink or downlink data at a rate of 2 Mbps or 100 kbps, respectively. The input referred noise of recording amplifiers is 1.16 μVrms, and the stimulation voltage is tunable from 1.5 V to 4.5 V with 5-bit resolution. After the electrical functionality of the microsystem is tested, the capability of the microsystem to interface with rat brain is further examined and compared with conventional instruments. All experimental results are presented and discussed in this paper.

Computational Models for Neuromuscular Function

Computational models of the neuromuscular system hold the potential to allow us to reach a deeper understanding of neuromuscular function and clinical rehabilitation by complementing experimentation. By serving as a means to distill and explore specific hypotheses, computational models emerge from prior experimental data and motivate future experimental work. Here we review computational tools used to understand neuromuscular function including musculoskeletal modeling, machine learning, control theory, and statistical model analysis. We conclude that these tools, when used in combination, have the potential to further our understanding of neuromuscular function by serving as a rigorous means to test scientific hypotheses in ways that complement and leverage experimental data.

Feasibility of prosthetic posture sensing via injectable electronic modules

A bionic neuron (BION) is an inductively powered, miniature implant developed for functional electric stimulation (FES) to reanimate paralyzed limbs. This paper investigates the possibility of reusing the BION antenna coil as a magnetic sensor to provide meaningful posture information for feedback control of FES. A variety of techniques have been developed to model and cancel nonideal effects caused by the shapes of the internal and external coils, ferrite material, and electronic connections. Field warping has been employed to both amplitude and direction to achieve more accurate description of the dipole magnetic field generated by external coils suitable for generating a reference magnetic frame in the environment of a wheelchair. Models of the transmitting coil and the receiving BION coil were validated against experimental data, providing a solid foundation for implementing a sensor system. Based on the established model, a magnetic sensing system combined with customized microelectro-mechanical systems (MEMS) accelerometer has been designed and tested as a prototype on the bench. The sensor output can be employed to compute 6-D position and orientation. A two-step algorithm integrated with multiple error-cancelling techniques demonstrated sufficient accuracy in bench tests to appear promising for control of reach-and-grasp tasks. A sensor fusion step is proposed to estimate the position and orientation of a limb segment using data from multiple implants in muscles, where they will also function as neuromuscular stimulators to produce the movements to be controlled.

Flexible communication and control protocol for injectable neuromuscular interfaces

BION2 is a system based on injectable neuromuscular implants whose main goal is to restore the functional movement of paralyzed limbs. To achieve this objective, the functional requirements of the implanted interfaces include not only stimulation but also integrated sensors in order to detect patient intention, to provide servocontrol of muscle activation and to sense posture to inform more global motor planning and coordination. The technical constraints for managing the system include the efficient use of forward and reverse telemetry channels with limited capacity, minimization of adverse consequences from errors in data transmission or intermittent loss of power to the implants, and ability to adjust stimulation rates and phases to achieve efficient fine control of muscle force while minimizing fatigue. This paper describes a communication and control architecture with several novel features that address these requirements.