Abstract: Systems and methods for analyzing electrical activity in smooth muscle of the gastrointestinal tract of a patient are disclosed. The systems includes an electromyographic-sensing patch adapted for placement on the skin of the abdomen of the patient. The patch has at least one bipolar electrode pair, or a multitude arranged in an array, and is enabled for communication of a signal indicative of a sensed electromyographic signal. The methods include artifact removal, data normalization, and peak detection methods on data derived from the sensed electromyographic signal and employ, at least for example, machine learning methods.

Abstract: Embodiments of a method for removal and replacement of artifacts in electrophysiological data from muscular activity in the gastrointestinal tract of a patient are disclosed. The approach includes setting an artifact identification threshold based on the parameters of the data, assessing the full extent of the artifact in time, and replacing the values with ones that are neutral in the time series and minimizing the effect on a power spectrum of the data. More particularly, the method includes steps of identifying artifacts within the raw time series data, eliminating the identified artifacts, and replacing the artifacts with any of interpolated points or constant value points to create a clean time series data set representing valid gastrointestinal tract EMG signals.

Abstract: System and methods for acquiring and processing myoelectrical data from the gastrointestinal tract of a patient are provided. In various embodiments, the systems and methods monitor the motor activity of a patient recovering from surgery to detect a resumption in gastrointestinal motility. In some embodiments, the systems and methods enable proper post-operative ileus in the patient. In some embodiments, the systems and methods allow researchers or clinicians to determine the efficacy of one or more therapies intended to encourage gastrointestinal motility. In some embodiments, the systems and methods enable clinicians to predict and facilitate the proper timing of discharge from a healthcare facility following surgery.

Abstract: A system and method for profiling electrical activity in smooth muscle of the gastrointestinal tract muscular of a patient are disclosed. The system includes electromyographic-sensing patches adapted for placement on the skin of the abdomen of the patient. Each patch has at least one bipolar electrode pair, or a multitude arranged in an array, and is enabled for communication of a signal indicative of a sensed electromyographic signal. The system further includes networked computing devices. The local patch device is configured for wireless communication between the EMG-sensing patches and a local computing device, to enable wireless transmission from the patch to the networked computing devices. The networked computing device is configured to process large aggregate collections of multi-hour or day signals received from the local computing device to yield diagnostically valuable physiological parameters of gastrointestinal smooth muscle electrical activity.

Abstract: Embodiments of a method for removal and replacement of artifacts in electrophysiological data from muscular activity in the a gastrointestinal tract of a patient are disclosed. The approach includes setting an artifact identification threshold based on the parameters of the data, assessing the full extent of the artifact in time, and replacing the values with ones that are neutral in the time series and minimizing the effect on a power spectrum of the data. More particularly, the method includes steps of identifying artifacts within the raw time series data, eliminating the identified artifacts, and replacing the artifacts with any of interpolated points or constant value points to create a clean time series data set representing valid gastrointestinal tract EMG signals.

Abstract: A system and method for profiling electrical activity in smooth muscle of the gastrointestinal tract muscular of a patient are disclosed. The system includes electromyographic-sensing patches adapted for placement on the skin of the abdomen of the patient. Each patch has at least one bipolar electrode pair, or a multitude arranged in an array, and is enabled for communication of a signal indicative of a sensed electromyographic signal. The system further includes networked computing devices. The local patch device is configured for wireless communication between the EMG-sensing patches and a local computing device, to enable wireless transmission from the patch to the networked computing devices. The networked computing device is configured to process large aggregate collections of multi-hour or day signals received from the local computing device to yield diagnostically valuable physiological parameters of gastrointestinal smooth muscle electrical activity.

Abstract: A method for diagnosing motility disorders of a gastrointestinal tract of a body. The method can include measuring electrical signals from the gastrointestinal tract while the patient is engaged in normal daily activities, recording the measured electrical signals on a portable electronic device carried by the body, recording by the patient in real time one or more symptoms of the body and analyzing characteristics of the recorded electrical signals with the recorded symptoms of the body to diagnosis gastrointestinal disorders of the body. Apparatus for use therewith and methods for treatment thereof are provided.