The presented platform allows neural activity to be unobtrusively monitored and processed in real-time in freely behaving untethered animals-revealing insights that are not attainable through scheduled recording sessions. This system achieves the lowest power per channel to date and provides a robust, low-latency, low-bandwidth and verifiable output suitable for BMIs, closed loop neuromodulation, wireless transmission and long term data logging.

We present a platform technology encompassing a family of innovations that together aim to tackle key challenges with existing implantable brain machine interfaces. The ENGINI (Empowering Next Generation Implantable Neural Interfaces) platform utilizes a 3-tier network (external processor, cranial transponder, intracortical probes) to inductively couple power to, and communicate data from, a distributed array of freely-floating mm-scale probes. Novel features integrated into each probe include: (1) an array of niobium microwires for observing local field potentials (LFPs) along the cortical column; (2) ultra-low power instrumentation for signal acquisition and data reduction; (3) an autonomous, self-calibrating wireless transceiver for receiving power and transmitting data; and (4) a hermetically-sealed micropackage suitable for chronic use. We are additionally engineering a surgical tool, to facilitate manual and robot-assisted insertion, within a streamlined neurosurgical workflow. Ongoing work is focused on system integration and preclinical testing. I. INTRODUCTION Brain Machine Interfaces (BMIs) have a genuine opportunity to effect a transformative impact on both medical [1], [2] and non-medical [3] applications. More specifically, clinical translation can lead to the restoration of movement and communication in patient populations with tetraplegia, amylotrophic lateral sclerosis, locked-in-syndrome, and speech disturbances. Current translational efforts utilize implantable medical devices (IMDs), e.g. Medtronic PC+S [1], experimental neuroscience tools, e.g. Blackrock Neuroport [2], or engineer new devices leveraged on IMDs [4], [5]. A. Key Challenges The major technical challenges with state-of-the-art BMI technology are chronic reliability (device longevity, recording stability, calibration/training) and scalability (extending number of recording and/or stimulation sites). In tackling these, wireless capability is crucial, but brings on its own set of challenges (wireless transfer efficiency, data throughput).

Abstract.Objective. Longitudinal observation of single unit neural activity from large numbers of cortical neurons in awake and mobile animals is often a vital step in studying neural network behaviour and towards the prospect of building effective Brain Machine Interfaces (BMIs). These recordings generate enormous amounts of data for transmission & storage, and typically require offline processing to tease out the behaviour of individual neurons. Our aim was to create a compact system capable of: 1) reducing the data bandwidth by circa 3 orders of magnitude (greatly improving battery lifetime and enabling low power wireless transmission); 2) producing real-time, low-latency, spike sorted data; and 3) long term untethered operation. Approach. We have developed a headstage that operates in two phases. In the short training phase a computer is attached and classic spike sorting is performed to generate templates. In the second phase the system is untethered and performs template matching to create an event driven spike output that is logged to a micro-SD card. To enable validation the system is capable of logging the high bandwidth raw neural signal data as well as the spike sorted data. Main results. The system can successfully record 32 channels of raw neural signal data and/or spike sorted events for well over 24 hours at a time and is robust to power dropouts during battery changes as well as SD card replacement. A 24-hour initial recording in a non-human primate M1 showed consistent spike shapes with the expected changes in neural activity during awake behaviour and sleep cycles. Significance The presented platform allows neural activity to be unobtrusively monitored and processed in real-time in freely behaving untethered animals revealing insights that are not attainable through scheduled recording sessions and provides a robust, low-latency, low-bandwidth output suitable for BMIs, closed loop neuromodulation, wireless transmission and long term data logging.

Respiratory rate (RR) is typically the first vital sign to change when a patient decompensates. Despite this, RR is often monitored infrequently and inaccurately. The Circadia Contactless Breathing Monitor™ (model C100) is a novel device that uses ultra-wideband radar to monitor RR continuously and un-obtrusively. Performance of the Circadia Monitor was assessed by direct comparison to manually scored reference data. Data were collected across a range of clinical and non-clinical settings, considering a broad range of user characteristics and use cases, in a total of 50 subjects. Bland–Altman analysis showed high agreement with the gold standard reference for all study data, and agreement fell within the predefined acceptance criteria of ±5 breaths per minute (BrPM). The 95% limits of agreement were −3.0 to 1.3 BrPM for a nonprobability sample of subjects while awake, −2.3 to 1.7 BrPM for a clinical sample of subjects while asleep, and −1.2 to 0.7 BrPM for a sample of healthy subjects while asleep. Accuracy rate, using an error margin of ±2 BrPM, was found to be 90% or higher. Results demonstrate that the Circadia Monitor can effectively and efficiently be used for accurate spot measurements and continuous bedside monitoring of RR in low acuity settings, such as the nursing home or hospital ward, or for remote patient monitoring.

Abstract-This paper proposes a novel method for integrating CMOS microelectronics with microwire-based electrodes for next generation implantable brain machine interfaces. There is strong evidence to suggest that microwire-based electrodes outperform micromachined and polymer-based electrodes in terms of signal integrity and chronic viability. Furthermore, it has been shown that the recording of Local Field Potentials (LFPs) is more robust to tissue damage and scar tissue growth when compared to action potentials. This work therefore investigates the suitability of microwire electrodes for LFP recording by studying the electrical properties of key materials. We identify Niobium (Nb) as a candidate material with highly desirable properties. There is however also an inherent incompatibility when it comes to connection of microwire-based electrodes to silicon chips. Here we present a new process flow utilising a recessed glass substrate for mechanical support, silicon interposer for interconnection, and electroplating for contact adhesion. Furthermore, the proposed structure lends itself to hermetic encapsulation towards gas cavity based micropackages.