A digestive profiling system comprises a breath analysis device comprising an inlet arranged to receive a breath sample from a user, a gas sensor arranged to generate a gas measurement of an amount of gas in the breath sample, and a first communication interface arranged to transmit a plurality of gas measurements generated by the gas sensor. The system further comprises a remote user interface device. The remote user interface device comprises a second communication interface arranged to receive the gas measurements generated by the gas sensor, a storage module arranged to store the received gas measurements, and a display arranged to display information to the user based on the stored gas measurements. The remote user interface device is remote from the breath analysis device.

Apparatus, system, and computer readable media determine the probability of visual recognition of an image by a subject using electroencephalography (EEG) corresponding to a Visual Evoked Potential (VEP). The apparatus comprises means for presenting a series of visual stimuli corresponding to said image to evoke EEG signals. The visual stimuli of the image are presented in an orientation sequence based on a timing cycle. At least one prism is provided for placement in front of the series of visual stimuli corresponding to said image. The EEG signals evoked in response to said visual stimuli and said prism placed in front of said visual stimuli are recorded and processed by a processor. VEP is generated corresponding to the presence of a shift and thereby provides object statistic reliability of the visual recognition of the image by the subject.

A system and a method for correcting posture are provided where the system comprises a smart bag including at least one pressure sensor and a first communication unit for transmitting an input value recognized by the pressure sensor to a user terminal. The user terminal including a second communication unit for receiving the input value from the first communication unit, an adhesion status checking unit for determining whether a user's human body and the smart bag are in close contact each other or not and determining an adhesion degree between the user's human body and the smart bag by using the input value received by the second communication unit, and a display unit for displaying the adhesion degree between the user's human body and the smart bag determined by the adhesion status checking unit.

A method of predicting likelihood for childhood obesity, comprises: obtaining a plurality of parameters, wherein at least a few of the parameters characterize an infant or toddler subject. A machine learning procedure trained for predicting likelihoods for childhood obesity is feed with the plurality of parameters. An output indicative of a likelihood that the infant or toddler subject is expected to develop childhood obesity is received from the procedure. The output is related non-linearly to the parameters.

A biological information measuring device includes a buckle including a first plate having a plate shape and being fixed to the other end of a second plate frame member and a second plate having a plate shape being rotatable. The second plate has a part that extends beyond the first plate when the second plate overlaps an outer surface of the first plate. A first fixing element is on a side of the extended part that becomes an inner surface when the second plate overlaps the outer surface of the first plate. A second fixing element is engageable with the first fixing element on the outer surface of the front end of the belt. An first engagement protrusion is on the first plate, and a second engagement protrusion overlaps the first engagement protrusion in a direction with the first engagement protrusion is on the second plate.

Disclosed are systems and methods for automated analysis of facial photographs for improved airway management and patient safety using unsupervised computer algorithms based on feature extraction from facial photographs by deep-learning algorithms. A deep-learning algorithm-based feature extractor uses frontal and/or profile views of the face to identify important information about potential intubation difficulty. This information is used by a trained advanced algorithm to classify faces as easy or difficult to intubate based on the extracted features.

A method and associated computer system and computer program product for monitoring the use of language of a patient that may enable the identification, analysis and reporting on of the natural progression of various neurological or speech disorders, is provided. The method includes obtaining a verbal response of the patient to a stimulus, converting the verbal response into text and the generating of verbal and textual response data by analyzing the verbal response and response text, respectively. A response vector may be formed base on the verbal and textual response data, which may then be used to determine a reply to the patient. Improved accuracy and consistency of monitoring the use of language associated with neurological and speech disorders is achieved, leading to a greater rate of success in the treatment of these conditions.

A process for treating femoral fractures in children includes diagnosing a patient with a femoral shaft fracture and enclosing the affected limb in a splint. The process further includes scanning the unaffected limb with a three-dimensional scanner and obtaining measurements of the unaffected limb that may be used to form a brace for the affected limb. In addition, the process includes fabricating an orthosis to support the affected limb based on the scan and measurements taken of the unaffected limb, and applying the orthosis to the affected limb.

At least partial function of a human limb is restored by surgically removing at least a portion of an injured or diseased human limb from a surgical site of an individual and transplanting a selected muscle into the remaining biological body of the individual, followed by contacting the transplanted selected muscle, or an associated nerve, with an electrode, to thereby control a device, such as a prosthetic limb, linked to the electrode. Simulating proprioceptive sensory feedback from a device includes mechanically linking at least one pair of agonist and antagonist muscles, wherein a nerve innervates each muscle, and supporting each pair with a support, whereby contraction of the agonist muscle of each pair will cause extension of the paired antagonist muscle. An electrode is implanted in a muscle of each pair and electrically connected to a motor controller of the device, thereby simulating proprioceptive sensory feedback from the device.

An intelligent defecation device for living creature includes a device body, a supporting portion, an image module, and a first analysis module. The supporting portion is formed within the inner side of the device body for accommodating a moisture absorption member so as to allow the living creature to leave over its excrement therein. The image module is also arranged at the device body for dynamically capturing the images of the excrement in the supporting portion and outputting the image. The first analysis module is arranged in the device body and connected with the image module to analyze and calculate the defecation mode with the image based on preset or accumulated data, so as to generate a signal when an abnormal defecation mode is diagnosed.