A system for monitoring patients during a consciousness-altering therapeutic treatment session including a data collection module in electronic communication with network servers for storage of data on non-transitory computer readable media for monitoring a patient's well-being during and after the treatment session. A method of using the system in treating a patient, by continuously, continually, or at the healthcare professionals discretion monitoring the well-being of the patient during a consciousness-altering therapeutic treatment session through one or more wearable devices and a patient mobile device in electronic communication with a facilitator mobile device, and continuously monitoring the well-being of the patient after the treatment session with the wearable device.

An electronic device is provided. The electronic device includes a communication module, a display, a memory, a biosensor configured to measure oxygen saturation, and at least one processor. The at least one processor may be configured to obtain electronic medical record (EMR) data from an external server through the communication module, identify oxygen saturation-related medical records based on the EMR data, based on occurrence of an event, determine a specified oxygen saturation measurement period and a specified reference oxygen saturation range based on the oxygen saturation-related medical records, measure oxygen saturation based on the specified oxygen saturation measurement period by using the biosensor, identify whether the measured oxygen saturation satisfies the specified reference oxygen saturation range, and display the measured oxygen saturation and information indicating whether the measured oxygen saturation satisfies the specified reference oxygen saturation range on the display.

A health data management system includes a health data measurement apparatus and a health management server communicable therewith. The apparatus includes medical and health equipment that measures health data of a user and first circuitry that collects the health data. The management server includes a first memory that stores the health data from the apparatus and second circuitry. Based on the stored health data, the second circuitry generates health management data representing a health state of the user, and analyzes at least one of an item indicating a worsening health state of the user, an item with insufficient measurement data, or an item lacking measurement data as a required check item. When determined that the health management data includes the required check item, the second circuitry transmits to the apparatus a message prompting the user to take a measurement of the required check item, and requests the health data.

Systems, methods, and apparatuses for reducing error between calculated analyte levels and impractical analyte measurements using practical analyte measurements as reference measurements for calibration. Reducing the error may include converting a practical reference analyte measurement into an estimated impractical analyte level, updating a conversion function using the estimated impractical analyte level, and using the updated conversion function to calculate an analyte level. In some aspects, the practical reference analyte measurement may be a capillary blood analyte measurement, and the estimated impractical analyte level may be an estimated venous blood analyte level. In some aspects, the updated conversion function may minimize the error between analyte levels calculated using the updated conversion function and estimated venous blood analyte levels.

Disclosed are devices, systems and methods for in vivo monitoring of localized environment conditions within a patient user by measuring analytes, including glucose, oxygen, and/or other analytes. In some aspects, a sensor device includes a wafer-based substrate, at least one electrochemical sensor two-electrode contingent including a working electrode and a reference electrode on the substrate and configured to detect a target analyte in a body fluid when the sensor device is deployed within a subject's body, where the working electrode is functionalized by a chemical layer configured to facilitate a reaction involving the target analyte that produces an electrical signal; and an electronics unit in communication with the electrochemical sensor electrode contingent to transmit the electrical signal to an external processor.

Systems, methods, and devices of a health device network may include: a non-invasive glucometer that non-invasively measures analyte levels; an invasive glucometer communicatively coupled directly to the non-invasive glucometer; a cloud-based server communicatively coupled to the non-invasive glucometer or the invasive glucometer; a user device communicatively coupled to the cloud-based server; and/or a user interface that displays the invasive glucose measurement, the non-invasive glucose measurement, a data batch, and/or processed data to the user. The non-invasive glucometer and/or the invasive glucometer may aggregate an invasive glucose measurement and a non-invasive glucose measurement into the data batch. A data analytics application on the cloud-based server may be configured to: integrate the invasive glucose measurement and the non-invasive glucose measurement; identify a correlation between the invasive glucose measurement and the non-invasive glucose measurement; and/or generate a predictive model based on the invasive glucose measurement and the non-invasive glucose measurement.

The disclosure provides methods and systems for determining an emotional fitness metrics for users. A physiological parameter of the user is measured during a group activity using at least one biosensor to acquire a measured signal. The measured signal of the user is compared to a measured signal for the physiological parameter of one or more additional users as measured when the one or more additional users perform the group activity. An emotional connectivity may be calculated based on a synchronicity of the measured signal of the user with the measured signal of the one or more additional users, as well as a cognitive appraisal metric, a resilience metric and an emotional fitness metric. Connectivity values for user pairings for a group activity can be computed based a synchronicity in a time-series correlation for the physiological parameters for permutations of the user pairings for the group activity.

A computer-implemented method for determining a predictive disease status of an inflammatory disease of a patient is compatible with a system including a remote platform and at least one mobile user device, wherein the at least one mobile user device is associated with the patient and is in data communication with the platform. The method comprises: receiving, at the platform, monitoring data indicative of the health state of the patient from the user device associated to the patient; determining, at the platform, a predictive disease state of the inflammatory disease of the patient based on the received monitoring data; evaluating the determined predictive disease status; providing the predictive disease status to a user at the platform and/or the patient at the user device based on the evaluating the determined predictive disease status.

Embodiments described herein include a medical monitoring system with a cloud communication interface in which individual components of the medical monitoring system, including medical sensors and data receiving devices are configured to communicate with remote cloud servers of the medical monitoring system using cellular networks. The remote cloud servers process medical data reported by the medical sensors and deliver data to the data receiving devices. The components of the medical monitoring system are low-cost and durable. The sensors are considered disposable after the expiration of their active use lifetime. The data receiving device can be manufactured using low-cost durable components to be protected against loss caused by accidental damage, destruction, or misplacement. Embodiments described herein further provide for authentication and for secure communication among the components of the medical monitoring system.

Various arrangements for sonar-based vital sign monitoring are presented herein. A mobile device may be determined to be stationary. In response, sonar-based movement sensing can be activated. Sonar data can then be captured in response to activating the sonar-based movement sensing. A breathing pattern can be detected in the sonar data and used to collect respiration data about a user.