Chronic implantation of cuff electrodes on the pelvic nerve in rats is well tolerated and does not compromise afferent or efferent fibre functionality.

OBJECTIVE: Neuromodulation of autonomic nerve activity to regulate physiological processes is an emerging field. Vagal stimulation has received most attention whereas the potential of modulate visceral function by targeting autonomic nerves within the abdominal cavity remains under-exploited. Surgery to locate intra-abdominal targets is inherently more stressful than for peripheral nerves. Electrode leads risk becoming entrapped by intestines and loss of functionality in the nerve-target organ connection could result from electrode migration or twisting. Since nociceptor afferents are intermingled with similar-sized visceral autonomic fibres, stimulation may induce pain. In anaesthetised rats high frequency stimulation of the pelvic nerve can suppress urinary voiding but it is not known how conscious animals would react to this procedure. Our objective therefore was to determine how rats tolerated chronic implantation of cuff electrodes on the pelvic nerve, whether nerve stimulation would be aversive and whether nerve-bladder functionality would be compromised. APPROACH: We carried out a preliminary de-risking study to investigate how conscious rats tolerated chronic implantation of electrodes on the pelvic nerve, their responsiveness to intermittent high frequency stimulation and whether functionality of the nerve-bladder connection became compromised. MAIN RESULTS: Implantation of cuff electrodes was well-tolerated. The normal diurnal pattern of urinary voiding was not disrupted. Pelvic nerve stimulation (up to 4 mA, 3 kHz) for 30 min periods evoked mild alerting at stimulus onset but no signs of pain. Stimulation evoked a modest (<0.5 °C) increase in nerve temperature but the functional integrity of the nerve-bladder connection, reflected by contraction of the detrusor muscle in response to 10 Hz nerve stimulation, was not compromised. SIGNIFICANCE: Chronic implantation of cuff electrodes on the pelvic nerve was found to be a well-tolerated procedure in rats and high frequency stimulation did not lead to loss of nerve functionality. Pelvic nerve stimulation has development potential for normalizing voiding dysfunction in conscious rats.

High-density data acquisition system and signal preprocessor for interfacing with microelectromechanical system-based biosensor arrays.

Microelectromechanical system (MEMS) development has become an active area for research in over the last decade. This area has advanced rapidly in recent years due to the potential ability of MEMS devices to perform complex functions in a smaller area. There is also the prospect to develop devices that can (1) be easily manufactured, (2) offer low power consumption, and (3) reduce waste. Especially in the BioMEMS area these advantages are important in terms of applied devices for biosensing, clinical diagnostics, physiological sensing, flow cytometry, and other lab-on-a-chip applications. However, one major obstacle that has been overlooked is the interface of these microdevices with the macroworld. This is critical to enable applications and development of the technology, as currently testing and analysis of data from these devices is mostly limited to generic microprobe stations. New advancements in BioMEMS have to occur in concert with the development of data acquisition systems and signal preprocessors to fully appreciate and test these developing technologies. In this work, we present the development of a cost effective, high throughput data acquisition system (Bio-HD DAQ) and a signal preprocessor for a MEMS-based cell electrophysiology lab-on-a-Chip (CEL-C) device. The signal preprocessor consists of a printed circuit board mounted with the CEL-C device and a 64-channel filter/amplifier circuit array. The data acquisition system includes a high-density crosspoint switching matrix that connects the signal preprocessor to a 16-channel, 18 bit, and 625 kSs DAQ card. Multimodule custom software designed on LABVIEW 7.0 is used to control the DAQ system. While this version of the Bio-HD DAQ system and accompanying software are designed keeping in view the specific requirements of the CEL-C device, it is highly adaptable and, with minor modifications, can become a generic data acquisition system for MEMS development, testing, and application.

Low-power, high data rate transceiver system for implantable prostheses.

Wireless telemetry is crucial for long-term implantable neural recording systems. RF-encoded neurological signals often require high data-rates to transmit information from multiple electrodes with a sufficient sampling frequency and resolution. In this work, we quantify the effects of interferers and tissue attenuation on a wireless link for optimal design of future systems. The wireless link consists of an external receiver capable of demodulating FSK/OOK transmission at speeds up to 8 Mbps, with <1e-5 bit-error rate (BER) without error correction, and a fully implanted transmitter consuming about 1.05 mW. The external receiver is tested with the transmitter in vivo to show demodulation efficacy of the transcutaneous link at high data-rates. Transmitter/Receiver link BER is quantified in typical and controlled RF environments for ex vivo and in vivo performance.

Real-time seizure prediction from local field potentials using an adaptive Wiener algorithm.

Approximately 30% of individuals with epilepsy have refractory seizures that cannot be controlled by current pharmacological treatment measures. For such patients, responsive neurostimulation prior to a seizure may lead to greater efficacy when compared with current treatments. In this paper, we present a real-time adaptive Wiener prediction algorithm implemented on a digital signal processor to be used with local field potential (LFP) recordings. The hardware implementation of the algorithm enables it to be a miniaturized portable system that could be used in a hand-held device. The adaptive nature of the algorithm allows the seizure data to be compared with baseline data occurring in the recent past rather than a preset value. This enhances the sensitivity of the algorithm by accounting for the time-varying dynamics of baseline, inter-ictal and ictal activity. The Wiener algorithm was compared to two statistical-based naïve prediction algorithms. ROC curves, area over ROC curves, predictive power, and time under false positives are computed to characterize the algorithm. Testing of the algorithm via offline Matlab analysis on kainate-treated rats results in prediction of seizures about 27 s before clinical onset, with 94% sensitivity and a false positive rate of 0.009 min(-1). When implemented on a real-time TI C6713 signal processor, the algorithm predicts seizures about 6.7s before their clinical onset, with 92% sensitivity and a false positive rate of 0.08 min(-1). These results compare favorably with those obtained in similar studies in terms of sensitivity and false positive rate.