An apparatus, system, and method for analysing and/or treating symptoms of IBS. A system for treating IBS may include a processor configured to receive a first set of data from biosensors configured to measure contractions in the bowel, receive a second set of data from a galvanic skin response sensor configured to measure electrical conductance of the skin, and analyze patterns between the first and second sets of data. An apparatus may include a base material comprising a material that fits to the body of a user, an elastic portion capable of applying compression across the abdomen of a user, and a tension adjusting mechanism for adjusting the compression applied to the abdomen in order to treat the symptoms of IBS.

An illustrative optical measurement device includes a light source configured to emit light pulses directed at a target. The optical measurement device further includes a detector configured to detect arrival times for photons of the light pulses after the photons are scattered by the target. The optical measurement device further includes a processing unit configured to generate, based on the arrival times of the photons at the detector, histogram data associated with the target. The processing unit is further configured to determine, based on the histogram data, an absolute optical property associated with the target. The processing unit is further configured to determine, based on the absolute optical property, a blood oxygenation level of the user, and perform an operation based on the blood oxygenation level.

According to various embodiments, a machine-learning based system for diabetes analysis is disclosed. The system includes one or more processors configured to interact with a plurality of wearable medical sensors (WMSs). The processors are configured to receive physiological data from the WMSs and demographic data from a user interface. The processors are further configured to train at least one neural network based on a grow-and-prune paradigm to generate at least one diabetes inference model. The neural network grows at least one of connections and neurons based on gradient information and prunes away at least one of connections and neurons based on magnitude information. The processors are also configured to output a diabetes-based decision by inputting the received physiological data and demographic data into the generated diabetes inference model.

A method includes receiving during a first time interval associated with a path of motion of a dynamic body, image data associated with a plurality of images of the dynamic body. The plurality of images include an indication of a position of a first marker coupled to a garment at a first location, and a position of a second marker coupled to the garment at a second location. The garment is coupled to the dynamic body. During a second time interval, an image from the plurality of images is automatically identified that includes a position of the first marker that is substantially the same as a position of a first localization element relative to the dynamic body and a position of the second marker that is substantially the same as a position of the second localization element relative to the dynamic body.

Training at the proper level of effort is important for athletes whose objective is to achieve the best results in the least time. In running, for example, pace is often monitored. However, pace alone does not reveal specific issues with regard to running form, efficiency, or technique, much less inform how training should be modified to improve performance or fitness. A sensing system and wearable sensor platform described herein provide real-time feedback to a user/wearer of his power expenditure during an activity. In one example, the system includes an inertial measurement unit (IMU) for acquiring multi-axis motion data at a first sampling rate, and an orientation sensor to acquire orientation data at a second sampling rate that is varied based on the multi-axis motion data.

At least some embodiments of the present disclosure is directed to a system for processing cardiac information. The system including a processing unit is configured to: receive one or more cardiac electrical signals from one or more electrodes disposed within a cardiac chamber, wherein the cardiac electrical signals are acquired over a cardiac beat; receive an indication of a measurement location corresponding to each of the cardiac electrical signals; analyze the one or more cardiac electrical signals to calculate a plurality of duty cycle values, the calculated duty cycle values corresponding to a plurality of pre-selected cycle length windows; and calculate an average duty cycle of the calculated duty cycle values over the plurality of pre-selected cycle length windows.

A method for providing a thermal feedback, performed by a feedback device. The feedback device outputs the thermal feedback, by transmitting a heat generated by a thermoelectric element, to a user via a contact surface contacting with a body part of the user. The method may include obtaining a feedback start message including a type of the thermal feedback, and when the type of the thermal feedback is a thermal grill feedback, outputting the thermal grill feedback by performing a thermal grill operation in which a heat generating operation and a heat absorbing operation is combined. The outputting of the thermal grill feedback may include applying a forward power to the thermoelectric element to perform the heat generating operation, applying a reverse power of which a current direction is opposite to the forward power to the thermoelectric element to perform the heat absorbing operation, and repeating the applying the forward power and the applying the reverse power alternatively.

Introduced are methods and systems for monitoring a person's sleeping patterns, and detecting episodes of sleeping disorders such as snoring and sleep apnea. In one embodiment, a sensor strip attached to the mattress monitors the user's breathing, and detects signature frequencies corresponding to snoring and sleep apnea. Once a sleeping disorder is detected, a notification can be sent to a device associated with the user, or the user's bed can be automatically adjusted to alleviate the sleeping disorder.

Methods, systems, and media are disclosed for detrending a bioelectric signal. In some embodiments, the disclosed system can include a processor configured to receive the bioelectric signal, identify at least one breakpoint section corresponds to a rapid change of amplitude of the bioelectric signal, smooth an amplitude of the bioelectric signal after the at least one breakpoint section; and reconstruct the bioelectric signal based on the smoothed amplitude of the bioelectric signal and a reset of the breakpoint section to remove extrinsic components caused by a non-biological factor from the bioelectric signal.

To calibrate a differential pressure measurement to a geodetic height difference of (approximately) zero, a reference position determination part is led close up to the blood pressure measuring device where a calibration signal is triggered if a minimum distance is not reached between two respective points defined at the reference position determination part and a blood pressure measuring device. A control device integrated in or connected to the blood pressure measuring device performs the calibration measurement in response to the trigger signal. The triggering means are implemented, e.g., as an RFID tag on the reference position determination part-side and an associated near-field communication reader on the blood pressure measuring device-side. If the near-field communication reader detects the correctly encoded RFID tag in the reference position determination part, it triggers the calibration signal.