A tubing assembly for electronic catheter guidance systems is provided and can include a catheter, an internal acoustic transducer and an external acoustic transducer. The catheter extends in a longitudinal direction and has proximal and distal ends that define a lumen therebetween. Further, the catheter is configured for placement within a patient's digestive or respiratory tract. The internal acoustic transducer can be located within the catheter's lumen, and the external acoustic transducer can be located on or outside the patient's body. The transducers can transmit and/or receive acoustic signals as directed by a processor and communicate with the processor to deliver sound data to a display device. The frequency response and/or attenuation of the signals can indicate placement of the catheter in the digestive tract compared to the respiratory tract. A catheter guidance system and method for accurately placing a catheter in the digestive or respiratory tract are also provided.

A swallowing diagnosis apparatus includes a controller which enables a first swallowing determination process of determining whether or not there is an aspiration risk in the swallowing on the basis of respiratory phases before and after a period in which swallowing has been estimated as having occurred; and a second swallowing determination process of extracting reference information including at least one of the sound information and the respiration information in a predetermined period including the period in which swallowing has been estimated as having occurred, obtaining a feature quantity from the extracted reference information, and performing a machine learning process on the obtained feature quantity to determine whether or not there is a possibility of dysphagia in the swallowing; and a display control process of causing a determination result obtained by the first swallowing determination process and a determination result obtained by the second swallowing determination process to be displayed.

Methods, devices and systems for predicting non-clinical, undiagnosed conditions through audio data related to intestinal sounds of a patient or subject, wherein the methods, devices and systems utilize machine learning algorithms, and predicting the likelihood of in vivo impairment relative to the identified spectral events.

Methods and systems are provided for diagnosis and possibly treatment of the large intestine, using samples from at least three portions of the large intestine, including sampling the ascending proximal portion thereof. Samples from the ascending portions of the large intestine were found to differ in their microbial characteristics significantly from prior art stool samples and from samples taken from the descending and transverse parts of the large intestine—enabling more accurate diagnosis and possibly more effective treatment of diseases of the large intestine.

A swallowing action measurement device includes a holder, a sound detector and a posture detector. The holder is fitted to a neck region of a person being measured from behind. The sound detector is held in the holder in contact with the outer side surface of the neck region close to the epiglottis, and detects sound associated with at least a swallowing action of the person being measured and outputs a measured sound signal. The posture detector detects a posture of the person being measured.

Provided is a digital stethoscope capable of outputting a heart sound data and/or a therapeutic data. The digital stethoscope includes a housing, a physiological data acquisition unit configured to acquire the heart sound data, a therapeutic data unit providing the therapeutic data and an output unit configured to output heart sound data and/or therapeutic data, wherein the physiological data acquisition unit and the therapeutic data unit are provided within the housing.

Example methods, apparatus, and articles of manufacture for monitoring use by a user of a portable research device in accordance with at least one predetermined use criterion are disclosed. The disclosed examples include passively gathering data for assessing an identity of a user of the portable research device, processing the passively gathered data to produce assessment data indicating a possibility that the user is not a predetermined correct user of the portable research device, based on the assessment data, displaying a message to the user requesting a response from which the user's identity may be determined, and processing a response to the message to produce data indicating whether the user is the predetermined correct user.

Described herein are methods and systems for monitoring acoustical activity from the abdominal region to guide the optimal timing of food ingestion. According to one embodiment of the method, the rate of intestinal digestion events, as well as the change in the rate across specific time periods, is analyzed to guide ingestion behavior in a way that improves health. The result of guidance may be to reduce weight in people who are obese, to improve performance in athletes seeking to balance energy availability and energy expenditure, or to increase caloric intake in people who are undernourished. The method can be applied using a smartphone application to provide contextually appropriate and specific user guidance about whether, when, and how much to eat in a manner that aligns with the physiologic patterns of intestinal activity.

A method for recognizing physiological symptom and a physiological symptom sensing system are provided. After the sound signal is obtained, multiple signal segments are captured from the sound signal. Afterwards, a sound type corresponding to each signal segment is recognized. Moreover, a physiological state of a living body is determined based on a plurality of the sound type of the signal segments and combinations of a plurality of the sound types.

A system, method, scope device, and camera control module device for a video endoscopy system, to enable scopes to operate with a rolling shutter-type image sensor. With selected pulsing of a strobe light, subset image data from adjacent rolling-shutter frames is selected, gain compensated for missing light and combined into a new single video frame.