Abstract: Methods of using low dose naltrexone to treat chronic pain in a patient. The methods of using low dose naltrexone to treat chronic pain generally includes administering to the patient a first amount of naltrexone in an immediate-release agent and a second amount of naltrexone in a modified-release agent.

Abstract: A system for fecal propulsion includes one or more sensors, a stimulator, one or more pairs of electrodes, a controller and a programming device. The sensors detect at least one marker of colonic activity from the enteric, autonomic and/or somatic nervous system. The stimulator generates energy of a particular waveform, intensity and/or time-course to modulate targeted neural circuitry with stimulation parameters being adaptable and dynamic to accommodate the various types of modulated tissues. The electrodes deliver stimulation to the enteric, autonomic and/or somatic nervous systems to control fecal propulsion. The controller and programing device change the stimulation parameters in real-time based on sensor feedback to acutely drive the circuitry from rest to productive defecation. The stimulation waveforms can be simultaneously or sequentially delivered to condition some tissues, while modulating others.

Abstract: Methods of using low dose naltrexone to treat chronic pain in a patient. The methods of using low dose naltrexone to treat chronic pain generally includes administering to the patient a first amount of naltrexone in an immediate-release agent and a second amount of naltrexone in a modified-release agent.

Abstract: Methods of using low dose naltrexone to treat chronic pain in a patient. The methods of using low dose naltrexone to treat chronic pain generally includes administering to the patient a first amount of naltrexone in an immediate-release agent and a second amount of naltrexone in a modified-release agent.

Abstract: An automated neuromodulation system which uses patient feedback during a training phase in combination with machine learning to automatically provide optimal nerve stimulation parameters based on the patient's needs without patient input. The automated neuromodulation system generally includes a lead which is implanted in a patient for treatment of a wide range of conditions, such as chronic pain. The patient is provided with a remote control through which the patient may provide either positive or negative feedback relating to how the patient is responding to electrical stimulation in different situations. A control unit monitors feedback from the patient as well as information and data from the time of feedback, such as the patient's position, orientation, speed of movement, or other considerations. Using machine learning, the control unit may process the feedback and data to formulate an optimized neuromodulation protocol and criteria which may be automatically applied to the patient.

Abstract: A neuromodulation system and method with feedback optimized electrical field generation for stimulating target tissue of a patient to treat neurological and non-neurological conditions. The system generally includes implantable electrodes, implantable sensors, an implantable or external electrical signal generator, and an implantable or external controller. The controller controls the electrical signal generator to generate electrical noise stimulation signals that are delivered to the target tissue via the electrodes and that produce an optimized electric field having maximized voltage with low current density. The sensors produce temperature and impedance data for the target tissue and the controller automatically responds to values of the sensor data that indicate potential damage to the target tissue to reduce the strength of the electric field.

Abstract: An automated neuromodulation system which uses patient feedback during a training phase in combination with machine learning to automatically provide optimal nerve stimulation parameters based on the patient's needs without patient input. The automated neuromodulation system generally includes a lead which is implanted in a patient for treatment of a wide range of conditions, such as chronic pain. The patient is provided with a remote control through which the patient may provide either positive or negative feedback relating to how the patient is responding to electrical stimulation in different situations. A control unit monitors feedback from the patient as well as information and data from the time of feedback, such as the patient's position, orientation, speed of movement, or other considerations. Using machine learning, the control unit may process the feedback and data to formulate an optimized neuromodulation protocol and criteria which may be automatically applied to the patient.

Abstract: A neuromodulation system and method with feedback optimized electrical field generation for stimulating target tissue of a patient to treat neurological and non-neurological conditions. The system generally includes implantable electrodes, implantable sensors, an implantable or external electrical signal generator, and an implantable or external controller. The controller controls the electrical signal generator to generate electrical noise stimulation signals that are delivered to the target tissue via the electrodes and that produce an optimized electric field having maximized voltage with low current density. The sensors produce temperature and impedance data for the target tissue and the controller automatically responds to values of the sensor data that indicate potential damage to the target tissue to reduce the strength of the electric field.

Abstract: A neuromodulation system and method with feedback optimized electrical field generation for stimulating target tissue of a patient to treat neurological and non-neurological conditions. The system generally includes implantable electrodes, implantable sensors, an implantable or external electrical signal generator, and an implantable or external controller. The controller controls the electrical signal generator to generate electrical noise stimulation signals that are delivered to the target tissue via the electrodes and that produce an optimized electric field having maximized voltage with low current density. The sensors produce temperature and impedance data for the target tissue and the controller automatically responds to values of the sensor data that indicate potential damage to the target tissue to reduce the strength of the electric field.

Abstract: A neuromodulation system and method with feedback optimized electrical field generation for stimulating target tissue of a patient to treat neurological and non-neurological conditions. The system generally includes implantable electrodes, implantable sensors, an implantable or external electrical signal generator, and an implantable or external controller. The controller controls the electrical signal generator to generate electrical noise stimulation signals that are delivered to the target tissue via the electrodes and that produce an optimized electric field having maximized voltage with low current density. The sensors produce temperature and impedance data for the target tissue and the controller automatically responds to values of the sensor data that indicate potential damage to the target tissue to reduce the strength of the electric field.