Abstract: A system includes chemical marker, verification, and third sensors. The chemical marker sensor is configured to detect one or more markers of a therapeutic agent in sweat vapor. The verification sensor is configured to detect whether the system is less than a threshold distance from skin. The third sensor is configured to detect a manifestation of an expected effect of the therapeutic agent on the heart rate of the user. The processor is communicatively coupled to the sensors and is configured to calculate a confidence level indicative of whether the user has taken the therapeutic agent based on the chemical marker sensor detecting the one or more markers in the sweat vapor, the verification sensor detecting that the system is less than the threshold distance from skin, and the third sensor detecting the manifestation of the expected effect of the therapeutic agent on the heart rate of the user.

Abstract: An example method includes generating a signal correlated with blood perfusion or SpO2 of a subject at a location and orientation on a body of the subject; determining a signal quality and/or signal strength of the signal; and in dependence on the signal quality and/or signal strength, either indicating that at least one of the location or the orientation is acceptable for placement of a biosensor on the body of the subject or prompting the subject or other person to reposition the biosensor. The biosensor may be part of a chest sensor device that includes: an adhesive with a liner having pull tabs for easy removal when the chest sensor device is positioned at a desired location; a finger grip to facilitate removal of the chest sensor device from the subject after a period of use; and/or wraparound fingers to secure the chest sensor device to the adhesive.

Abstract: A method to determine medication adherence may include detecting whether a wearable electronic device is in use. The method may include detecting one or more markers in sweat vapor of the user using a chemical marker sensor of the wearable electronic device. The method may include, in response to detecting that the system is in use, determining whether the user has taken a therapeutic agent that includes the one or more markers based on detecting the one or more markers in the sweat vapor.

Abstract: In an example, a torso sensor device includes a housing, first and second optical sensors, and a processor. The housing is configured to be coupled to a subject's torso. The first optical sensor is disposed in the housing. The second optical sensor is disposed in the housing spaced apart from the first optical sensor. The processor is electrically coupled to each of the first and second optical sensors and is configured to control the first and second optical sensors to generate oxygen saturation measurements of the subject.

Abstract: The present disclosure generally relates to the determination of blood pressure of a human being. More specifically, but not exclusively, in one aspect the present disclosure relates to determination of blood pressure of a human being over an extended period of time. In one form, a method for determining a blood pressure value of a human being includes determining a period of time during which the human being is stationary. The method also includes determining, during the period of time, a plurality of measurements providing pulse-related data values from the human being. From the plurality of measurements, a representative pulse-related data value representative of the pulse-related data values determined during the period of time may be determined. The method also includes determining, from the representative pulse-related data value, a blood pressure value of the human being for the period of time.

Abstract: In an example, a method to monitor blood pressure of a subject includes: generating a first signal representing cardiac electrical activity of the subject using a first sensor of a wearable system; generating a second signal representing cardiac photonic activity of the subject using a second sensor of the wearable system; generating a third signal representing cardiac mechanical activity of the subject using a third sensor of the wearable system; determining from the third signal a time period during which the first and second signals are likely clean; extracting one or more features from portions of two or more of the first, second, or third signals corresponding to the time period, the one or more extracted features including at least one of a PTT, a PAT, or BVE features; and determining a current blood pressure of the subject based on the one or more extracted features.

Abstract: In an example, an electrocardiogram (ECG) device includes a housing, an ECG sensor, and first and second electrodes. The ECG sensor is disposed in the housing. The first electrode is accessible from outside the housing and is electrically coupled to the ECG sensor. The second electrode is accessible from outside the housing and is electrically coupled to the ECG sensor. The housing and the first and second electrodes define an ECG device electromechanical interface that is complementary to a common patch electromechanical interface that is included in at least two different types of attachment patches.

Abstract: In an example, a method includes collecting biodata of a subject. The method includes generating or updating a personalized ML model of the subject from the biodata of the subject. The method includes detecting anomalies in the biodata based on the personalized ML model. The method includes filtering the detected anomalies to determine whether the detected anomalies indicate that the subject has a clinical condition or is at risk of having the clinical condition.

Abstract: An adhesive device may include a first adhesive surface configured to be adhered to skin of a user, and a second adhesive surface opposite the first adhesive surface and configured to be adhered to a medical device. The adhesive device may also include an intermediate region between the first adhesive surface and the second adhesive surface, where the intermediate region includes a detector compound embedded in the intermediate region configured to change based on interaction of the detector compound with a target molecule.

Abstract: A method may include generating a frequency-agnostic signal using an adjustable oscillator, and applying the frequency-agnostic signal to a user. The method may also include determining a reflecting value based on the frequency-agnostic signal as reflected by the user. The method may additionally include identifying a peak in the reflecting value by at least repeatedly comparing the determined reflecting value to a previously stored highest reflecting value, and adjusting the adjustable oscillator based on the comparison. The method may also include, after identifying the peak, determining a frequency of the oscillator corresponding to the peak, and outputting the frequency of the oscillator.

Abstract: An adhesive device may include a first adhesive surface configured to be adhered to skin of a user, and a second adhesive surface opposite the first adhesive surface and configured to be adhered to a medical device. The adhesive device may also include an intermediate region between the first adhesive surface and the second adhesive surface, where the intermediate region includes a detector compound embedded in the intermediate region configured to change based on interaction of the detector compound with a target molecule.

Abstract: According to an aspect of an embodiment, a method may include obtaining, at a mobile biometric-data hub, a first biometric reading of a user. The method may also include, based on the first biometric reading, associating the mobile biometric-data hub with the user. The method may also include wirelessly receiving, at the mobile biometric-data hub, a second biometric reading from a biometric sensor distinct from the mobile biometric-data hub. The method may also include determining that the second biometric reading is of the user. The method may also include, based on the second biometric reading being of the user and based on the association between the mobile biometric-data hub and the user, tagging the second biometric reading with an identifier of the user. The method may also include communicating the tagged second biometric reading from the mobile biometric-data hub to a network-attached device.

Abstract: A method to determine medication adherence may include detecting whether a wearable electronic device is in use. The method may include detecting one or more markers in sweat vapor of the user using a chemical marker sensor of the wearable electronic device. The method may include, in response to detecting that the system is in use, determining whether the user has taken a therapeutic agent that includes the one or more markers based on detecting the one or more markers in the sweat vapor.

Abstract: Some embodiments relate to ear-mountable devices with one or more sensors and both input and output capabilities. Such ear-mountable devices may validate behaviors, biometrics, and/or environmental conditions by generating a signal indicative of the same at an ear of the user and then determining the behaviors, biometrics, and/or environmental conditions based on the signal. Such ear-mountable devices may determine compliance of a user by outputting, through an audio output device of the ear-mountable devices, a compliance message to evoke a target behavior in the user, monitoring behavior of the user through a sensor of the ear-mountable device, and determining compliance of the user with the target behavior based on the monitoring.

Abstract: A system to determine medication adherence may include a chemical marker sensor, a verification sensor, and a processor. The chemical marker sensor may be configured to detect one or more markers in sweat vapor of a user. The verification sensor may be configured to detect whether the system is in use. The processor may be communicatively coupled to the chemical marker sensor and the verification sensor and may be configured to determine whether the user has taken a therapeutic agent that includes the one or more markers based on signals generated by the chemical marker sensor and the verification sensor.

Abstract: A method to create autonomous decision logic (ADL) may include receiving a request to create the ADL. The request includes a selection of an input and a selection of an output. When executed by a client device, the ADL is configured to provide the output based at least partially on an identification of the input. The method further includes electronically packaging the input and the output to generate the ADL. The method includes sending the ADL via a transport layer to the client device for execution of the ADL on the client device. The client device is configured to generate encrypted data pertaining to the execution of the ADL. The method includes receiving, from the client device, the encrypted data pertaining to the execution of the ADL. The method further includes decrypting the encrypted data. The method includes presenting at least some of the decrypted data on a display.

Abstract: A system to determine medication adherence may include a chemical marker sensor, a verification sensor, and a processor. The chemical marker sensor may be configured to detect one or more markers in sweat vapor of a user. The verification sensor may be configured to detect whether the system is in use. The processor may be communicatively coupled to the chemical marker sensor and the verification sensor and may be configured to determine whether the user has taken a therapeutic agent that includes the one or more markers based on signals generated by the chemical marker sensor and the verification sensor.

Abstract: A method to create autonomous decision logic (ADL) may include receiving a request to create the ADL. The request includes a selection of an input and a selection of an output. When executed by a client device, the ADL is configured to provide the output based at least partially on an identification of the input. The method further includes electronically packaging the input and the output to generate the ADL. The method includes sending the ADL via a transport layer to the client device for execution of the ADL on the client device. The client device is configured to generate encrypted data pertaining to the execution of the ADL. The method includes receiving, from the client device, the encrypted data pertaining to the execution of the ADL. The method further includes decrypting the encrypted data. The method includes presenting at least some of the decrypted data on a display.