Wireless Neuromodulation: From Bench to Bedside

Spinal cord stimulation (SCS), as a neuromodulation therapy, has rapidly evolved over the past few decades to become the treatment of choice for many chronic pain syndromes. However, many equipment-related limitations such as the bulk of the equipment, an implantable pulse generator (IPG), the limited therapeutic stimulation frequency utilized, and the potential adverse events have restricted SCS applications. Recently, advanced nanotechnology and minimally invasive surgical techniques have shown promising options to expand the indications due to reduced surgical trauma/hospital time/costs. We describe the basis for nanotechnology neuromodulation and the preliminary experience with wireless SCS in the treatment of chronic pain conditions. The equipment utilizes a miniature stimulator with microelectronics, percutaneously placed at the appropriate stimulation target, with wireless control to provide the desired stimulation, and then moderated by the clinician and the patient. The wireless device reduces the bulk of the SCS equipment to a single electrode (with embedded sensors), using the new improved neural-electric interface. This wireless neuromodulation (WNM) has been clinically used in several chronic pain conditions, including failed back surgery syndrome, facial pain, chronic regional pain syndrome, and postherpetic neuralgia, with encouraging outcome, without the complications of a traditional SCS resulting from the IPG or its accessories

STP-H7-CASPR: A Transition from Mission Concept to Launch

The Configurable and Autonomous Sensor Processing Research (CASPR) project is a university-led experiment developed by student and faculty researchers at the NSF Center for Space, High-performance, and Resilient Computing (SHREC) at the University of Pittsburgh for the Space Test Program – Houston 7 (STP-H7) mission to the International Space Station (ISS). Autonomous sensor processing, the mission theme of the CASPR experiment, is enabled by combining novel sensor technologies with innovative computing techniques on resilient and high-performance flight hardware in a small satellite (SmallSat) form-factor. CASPR includes the iSIM-90, an innovative, high-resolution optical payload for Earth-observation missions developed by SATLANTIS MICROSATS SL. For the CASPR mission, the opto-mechanics of iSIM-90 will be mounted atop a gimbal-actuated platform for agile, low-GRD (ground-resolved distance), and multispectral Earth-observation imaging. This mission will also feature the Prophesee Sisley neuromorphic, event-driven sensor for space situational awareness applications. The CASPR avionics system consists of the following: three radiation-tolerant, reconfigurable space computers, including one flight-proven CSP and two next-gen SSPs; one μCSP Smart Module; one power card; and one backplane. CASPR also features a sub-experiment with an AMD GPU to evaluate new accelerator technologies for space. CASPR is a highly versatile experiment combining a variety of compute and sensor technologies to demonstrate on-orbit capabilities in onboard data analysis, mission operations, and spacecraft autonomy. As a research sandbox, CASPR enables new software and hardware to be remotely uploaded to further enhance mission capabilities. Finally, as a university-led mission, cost is a limiting constraint, leading to budget-driven design decisions and the use of affordable methods and procedures. Other factors, such as a power budget and limited equipment, facilities, and engineering resources, pose additional challenges to the CASPR mission. To address these challenges, we describe cost-effective procedures and methods used in the assembly, integration, and testing of the CASPR experiment

CASPR: Autonomous Sensor Processing Experiment for STP-H7

As computing technologies improve, spacecraft sensors continue to increase in fidelity and resolution, their dataset sizes and data rates increasing concurrently. This increase in data saturates the capabilities of spacecraft-to-ground communications and necessitates the use of powerful onboard computers to process data as it is collected. The pursuit of onboard, autonomous sensor processing while remaining within the power and memory restrictions of embedded computing becomes vital to prevent the saturation of data downlink capabilities. This paper presents a new ISS research experiment to study and evaluate novel technologies in sensors, computers, and intelligent applications for SmallSat-based sensing with autonomous data processing. Configurable and Autonomous Sensor Processing Research (CASPR) is being developed to evaluate autonomous, onboard processing strategies on novel sensors and is set to be installed on the ISS as part of the DoD/NASA Space Test Program –Houston 7(STP-H7) mission. CASPR features a flight-qualified CSP space computer as central node and two flight-ready SSP space computers for apps execution, both from SHREC, a telescopic, multispectral imager from Satlantis Inc., an event-driven neuromorphic vision sensor, an AMD GPU subsystem, and Intel Optane phase-change memory. CASPR is a highly versatile ISS experiment meant to explore many facets of autonomous sensor processing in space

NASA SpaceCube Next-Generation Artificial-Intelligence Computing for STP-H9-SCENIC on ISS

Recently, Artificial Intelligence (AI) and Machine Learning (ML) capabilities have seen an exponential increase in interest from academia and industry that can be a disruptive, transformative development for future missions. Specifically, AI/ML concepts for edge computing can be integrated into future missions for autonomous operation, constellation missions, and onboard data analysis. However, using commercial AI software frameworks onboard spacecraft is challenging because traditional radiation-hardened processors and common spacecraft processors cannot provide the necessary onboard processing capability to effectively deploy complex AI models. Advantageously, embedded AI microchips being developed for the mobile market demonstrate remarkable capability and follow similar size, weight, and power constraints that could be imposed on a space-based system. Unfortunately, many of these devices have not been qualified for use in space. Therefore, Space Test Program - Houston 9 - SpaceCube Edge-Node Intelligent Collaboration (STP-H9-SCENIC) will demonstrate inflight, cutting-edge AI applications on multiple space-based devices for next-generation onboard intelligence. SCENIC will characterize several embedded AI devices in a relevant space environment and will provide NASA and DoD with flight heritage data and lessons learned for developers seeking to enable AI/ML on future missions. Finally, SCENIC also includes new CubeSat form-factor GPS and SDR cards for guidance and navigation

Tissue Depth Study for a Fully Implantable, Remotely Powered and Programmable Wireless Neural Stimulator

Miniature, remotely powered and programmable neural stimulators were implanted on the sciatic nerve in nine pig hind limbs. An external dipole antenna was used to transmit power and waveforms to the implant at 915 MHz. For each placement location, external power was swept until motor threshold was achieved. Thresholds were determined via visual observation of muscle twitches in the lower leg. The external antenna was placed at several different distances from the implant and the threshold power was recorded as a function of the tissue thickness overlying the implant. Verification of the current was measured by: 1) optical recording electrodes and 2) Random validation using wired recording electrodes. Both methods recorded the current required to reach motor threshold. Results from these tests confirmed that wireless neural stimulation could effectively excite motor nerves remotely in up to 12 cm of soft tissue of a mixed medium. Propagation losses for this verification also agreed with simulation models. These measurements verified that ample current densities could be achieved at significant tissue depths and therefore, a wireless neural stimulator can be potentially be utilized in existing neural stimulation therapeutic treatments

Migratory behavior of eastern North Pacific gray whales tracked using a hydrophone array

<div><p>Eastern North Pacific gray whales make one of the longest annual migrations of any mammal, traveling from their summer feeding areas in the Bering and Chukchi Seas to their wintering areas in the lagoons of Baja California, Mexico. Although a significant body of knowledge on gray whale biology and behavior exists, little is known about their vocal behavior while migrating. In this study, we used a sparse hydrophone array deployed offshore of central California to investigate how gray whales behave and use sound while migrating. We detected, localized, and tracked whales for one full migration season, a first for gray whales. We verified and localized 10,644 gray whale M3 calls and grouped them into 280 tracks. Results confirm that gray whales are acoustically active while migrating and their swimming and acoustic behavior changes on daily and seasonal time scales. The seasonal timing of the calls verifies the gray whale migration timing determined using other methods such as counts conducted by visual observers. The total number of calls and the percentage of calls that were part of a track changed significantly over both seasonal and daily time scales. An average calling rate of 5.7 calls/whale/day was observed, which is significantly greater than previously reported migration calling rates. We measured a mean speed of 1.6 m/s and quantified heading, direction, and water depth where tracks were located. Mean speed and water depth remained constant between night and day, but these quantities had greater variation at night. Gray whales produce M3 calls with a root mean square source level of 156.9 dB re 1 <i>μ</i>Pa at 1 m. Quantities describing call characteristics were variable and dependent on site-specific propagation characteristics.</p></div