Development of innovative techniques for the endoscopic implantation and securing of a novel, wireless, miniature gastrostimulator (with videos).

BACKGROUND: Gastric stimulation via high-frequency, low-energy pulses can provide an effective treatment for gastric dysmotility; however, the current commercially available device requires surgical implantation for long-term stimulation and is powered by a nonrechargeable battery. OBJECTIVE: To test and describe endoscopic implantation techniques and testing of stimulation of a novel, wireless, batteryless, gastric electrical stimulation (GES) device. DESIGN: Endoscopic gastric implantation techniques were implemented, and in vivo gastric signals were recorded and measured in a non-survival swine model (n = 2; 50-kg animals). INTERVENTION: Five novel endoscopic gastric implantation techniques and stimulation of a novel, wireless, batteryless, GES device were tested on a non-survival swine model. MAIN OUTCOME MEASUREMENTS: Feasibility of 5 new endoscopic gastric implantation techniques of the novel, miniature, batteryless, wireless GES device while recording and measurement of in vivo gastric signals. RESULTS: All 5 of the novel endoscopic techniques permitted insertion and securing of the miniaturized gastrostimulator. By the help of these methods and miniaturization of the gastrostimulator, successful GES could be provided without any surgery. The metallic clip attachment was restricted to the mucosal surface, whereas the prototype tacks, prototype spring coils, percutaneous endoscopic gastrostomy wires/T-tag fasteners, and submucosal pocket endoscopic implantation methods attach the stimulator near transmurally or transmurally to the stomach. They allow more secure device attachment with optimal stimulation depth. LIMITATIONS: Non-survival pig studies. CONCLUSION: These 5 techniques have the potential to augment the utility of GES as a treatment alternative, to provide an important prototype for other dysmotility treatment paradigms, and to yield insights for new technological interfaces between non-invasiveness and surgery.

A closed loop feedback system for automatic detection and inhibition of mechano-nociceptive neural activity.

Clinical studies have shown that spinal or cerebral neurostimulation can significantly relieve pain. Current neurostimulators work in an open loop; hence, their efficacy depends on the patient's or physician's comprehension of pain. We have proposed and developed a real-time automatic recognition program with signal processing functions to detect action potentials. By using a wireless neurorecording module, spinal neuronal responses to mechanical stimuli (brush, pressure, and pinch) applied to rats' hind paws were recorded. Nociceptive spinal responses were detected and suppressed by our automated module through delivering electrical stimulation to the periaqueductal gray (PAG). The interspike intervals (ISIs) of the fired action potentials were used to distinguish among the three different mechanical stimuli. Our system was able to detect the neuronal activity intensities and deliver trigger signals to the neurostimulator according to a pre-set threshold in a closed-loop feedback configuration, thereby suppressing excessive activity in spinal cord dorsal horn neurons.

Recognition and inhibition of dorsal horn nociceptive signals within a closed-loop system.

We implemented an integrated system that can acquire neuronal signals from spinal cord dorsal horn neurons, wirelessly transmit the signals to a computer, and recognize the nociceptive signals from three different mechanical stimuli (brush, pressure and pinch). Positive peak detection method was chosen to distinguish between signal spikes. The inter spike intervals (ISIs) were calculated from the identified action potentials (APs) and fed into a numerical array called cluster. When the sum of the ISIs in the cluster reached a critical level, the program recognized the recorded signals as nociceptive inputs. The user has the flexibility to tune both the cluster size and critical threshold for individual's need to reach optimization in pain signal recognition. The program was integrated with a wireless neurostimulator to form a feedback loop to recognize and inhibit nociceptive signals.