A wireless, patient-worn, physiological sensor configured to, among other things, help manage a patient that is at risk of forming one or more pressure ulcers is disclosed. According to an embodiment, the sensor includes a base having a top surface and a bottom surface. The sensor also includes a substrate layer including conductive tracks and connection pads, a top side, and a bottom side, where the bottom side of the substrate layer is disposed above the top side of the base. Mounted on the substrate layer are a processor, a data storage device, a wireless transceiver, an accelerometer, and a battery. In use, the sensor senses a patient's motion and wirelessly transmits information indicative of the sensed motion to, for example, a patient monitor. The patient monitor receives, stores, and processes the transmitted information.

An apparatus for real time monitoring of a patient is provided and includes a memory element for storing data, a processor that executes instructions associated with the data, an interface that receives sensor data from a sensor that takes measurements from the patient and sends the sensor data according to the sensor's measurement latency, a latency calculator that frequently calculates a latency threshold that varies according to at least a health status of the patient, a timer that continuously monitors the sensor's measurement latency, a comparator that frequently compares the sensor's measurement latency with the calculated latency threshold, and a feedback module that automatically changes the sensor's measurement latency to match with the calculated latency threshold.

Embodiments herein relate to reflective optical medical sensor devices. In an embodiment, a reflective optical medical sensor device including a central optical detector and a plurality of light emitter units disposed around the central optical detector is provided. A plurality of peripheral optical detectors can be disposed to the outside of the plurality of light emitter units. Each of the plurality of peripheral optical detectors can form a channel pair with one of the plurality of light emitter units. The reflective optical medical sensor device can also include a controller in electrical communication with the central optical detector, the light emitter units, and the peripheral optical detectors. The controller can be configured to measure performance of channel pairs; select a particular channel pair; and measure a physiological parameter using the selected channel pair. Other embodiments are also included herein.

Embodiments herein relate to reflective optical medical sensor devices. In an embodiment, a reflective optical medical sensor device including a central optical detector and a plurality of light emitter units disposed around the central optical detector is provided. A plurality of peripheral optical detectors can be disposed to the outside of the plurality of light emitter units. Each of the plurality of peripheral optical detectors can form a channel pair with one of the plurality of light emitter units. The reflective optical medical sensor device can also include a controller in electrical communication with the central optical detector, the light emitter units, and the peripheral optical detectors. The controller can be configured to measure performance of channel pairs; select a particular channel pair; and measure a physiological parameter using the selected channel pair. Other embodiments are also included herein.

Systems and methods for monitoring patients with multiple chronic diseases are described. A system may include a health status monitor that receives diagnostic data including physiological signals sensed from a patient. The system may produce at least a first risk indication of the patient developing a first disease and a second risk indication of the patient developing a different second disease. The system may detect the first and second diseases from the physiological signals, and generate a composite health status indicator using the detections of the first and second diseases and the first and second risk indications. An alert of worsening health status may be generated if the composite detection score exceeds an alert threshold.

Systems and methods for monitoring patients with multiple chronic diseases are described. A system may include a health status monitor that receives diagnostic data including physiological signals sensed from a patient. The system may produce at least a first risk indication of the patient developing a first disease and a second risk indication of the patient developing a different second disease. The system may detect the first and second diseases from the physiological signals, and generate a composite health status indicator using the detections of the first and second diseases and the first and second risk indications. An alert of worsening health status may be generated if the composite detection score exceeds an alert threshold.

The disclosure provides a measurement circuit. The measurement circuit includes a control engine. An excitation source is coupled to the control engine. A first set of electrodes and a second set of electrodes are coupled to the excitation source and receive current from the excitation source. The control engine operates the excitation source in a first mode and a second mode. The control engine, in the first mode, measures a parasitic impedance associated with the first and the second set of electrodes, and the control engine, in the second mode, measures an impedance of the first and the second set of electrodes and of an external object.

A system for generating an alimentary plan is disclosed. The system comprises a computing device which is configured to receive an input that includes physiological data related to a skin sample. Computing device is configured to extract a plurality of biological indicators related to disease state from the physiological data. Computing device is configured to determine a biological indicator score for each biological score for each biological indicator of the plurality of biological indicators. Computing device is configured to generate a skin disorder classifier by receiving skin disorder training data. The computing device is configured to classify, using the skin disorder classifier, the at least one biological indicator and the biological indicator score to a positive result for a skin disorder. Computing device is configured to generate an alimentary plan as a function of the positive result. A method for generating an alimentary plan is also disclosed.

A method for uterine activity monitoring may include: acquiring a plurality of signals from a plurality of sensors during uterine activity; processing the plurality of signals to extract a plurality of uterine electrical activity characteristics; analyzing the plurality of uterine electrical activity characteristics; and classifying the uterine activity as one of: a preterm labor contraction, a labor contraction, a Braxton-Hicks contraction, and a state of no contraction. A method of assessing over time a pre-term birth risk of a pregnant female may include: calculating a baseline pre-term birth risk score based on a user input; acquiring, over time, a signal from a sensor; analyzing the signal to extract a parameter of interest, such that the parameter of interest comprises a physiological parameter; and calculating an instant pre-term birth risk score based, at least in part, on the parameter of interest and the user input.

A method for uterine activity monitoring may include: acquiring a plurality of signals from a plurality of sensors during uterine activity; processing the plurality of signals to extract a plurality of uterine electrical activity characteristics; analyzing the plurality of uterine electrical activity characteristics; and classifying the uterine activity as one of: a preterm labor contraction, a labor contraction, a Braxton-Hicks contraction, and a state of no contraction. A method of assessing over time a pre-term birth risk of a pregnant female may include: calculating a baseline pre-term birth risk score based on a user input; acquiring, over time, a signal from a sensor; analyzing the signal to extract a parameter of interest, such that the parameter of interest comprises a physiological parameter; and calculating an instant pre-term birth risk score based, at least in part, on the parameter of interest and the user input.