A method for providing treatment recommendations for a patient to a physician is disclosed. The method includes receiving health information associated with the patient, determining a first risk score for the patient based on the health information using a trained predictor model, determining a second risk score for the patient based on the health information and at least one artificially closed care gap included in the health information using the predictor model, determining a predicted risk reduction score based on the first risk score and the second risk score, determining a patient classification based on the predicted risk reduction score, and outputting a report based on at least one of the first risk score, the second risk score, or the predicted risk reduction score.

Disclosed is an IoT enabled, portable, multiple stimuli reinforced non-nutritive Sucking Training System, Method and Device that implements a function that measures suction pressure of a non-nutritive sucking event produced by a pre-mature infant; then converts the measured pressure value using transducer to digital form; then transmits the pressure value in digital form using IoT (Internet-of-Things) controller to a server and/or to an app and/or a software installed on a smartphone device. The app and/or software installed on the smartphone device which receives the pressure measurement uses an algorithm to produce a stimulus such as music and/or haptic feedback for the pre-mature infant, to train the premature infant to suck optimally; thereby improving self-feeding capability of the premature infant.

A bruxism training device is disclosed that is capable of detecting bruxism events (e.g., jaw clenching and teeth grinding) via external electromyography (EMG). The training device is shaped to be easily placed in a proper location and proper orientation over a masseter muscle of a user. A locator region is provided to facilitate easy locating of a reference electrode over the gonial angle of the mandible, while an alignment edge of the training device is provided to facilitate easy locating of end electrodes adjacent an end of the masseter muscle coupled to the mandible. With the locator region and alignment edge in place, an array of mid electrodes is automatically positioned over a bulk of the masseter muscle, allowing useful EMG measurement to be acquired of masseter activation.

A garment (e.g., a shirt) for monitoring biometric properties of the wearer of the garment is disclosed. The garment may include sensors for monitoring or assessing the vital signs and body position of the wearer. A processor associated with the garment may provide an output indicative of an assessed condition of the wearer based on the assessed vital signs and the assessed body position of the wearer of the fabric. The garment may include an injector assembly that is used to administer a drug injection to the wearer when the assessed condition indicates that the wearer is in an alert condition.

Systems and methods for identifying a condition of a user. A treatment apparatus is configured to be manipulated by the user for performing an exercise, and an interface is communicably coupled to the treatment apparatus. One or more sensors are configured to sense one or more characteristics of an anatomical structure of the user. A processing device and a memory is communicatively coupled to the processing device. The memory includes computer readable instructions, that when executed by the processing device, cause the processing device to: receive, from the sensors, one or more sensor inputs representative of the one or more of characteristics of the anatomical structures; calculate an infection probability of a disease based on the one or more characteristics of the anatomical structures; and output, to the interface, a representation of the infection probability.

A method and system for providing and aggregating bioelectrical signal data comprising: providing a stimulus configured to prompt an action in both a first user and a second user; at a first biosignal detector and a second biosignal detector, automatically collecting a first bioelectrical signal dataset from the first user as the first user performs the action and a second bioelectrical signal dataset from the second user as the second user performs the action; generating a first anonymized bioelectrical signal dataset from the first bioelectrical signal dataset and a second anonymized bioelectrical signal dataset from the second bioelectrical signal dataset; coupling the first and the second anonymized bioelectrical signal datasets with an action tag characterizing the action; and generating an analysis based upon the first the second anonymized bioelectrical signal datasets. An embodiment of the system comprises a biosignal detector and a processor configured to implement an embodiment of the method.

The present invention relates to a system for neuromuscular rehabilitation of a patient having an affected limb comprising: a feedback member arranged to give real-time visual feedback; a plurality of electrodes arranged to acquire an electric signal corresponding to an intent to move said affected limb; a control unit configured to: perform pattern recognition of said electric signals, wherein at least one feature in said electric signal is used to predict motion intent of said affected limb adjacent to at least one joint, such aggregated motions of said affected limb are predicted; based on output signals from said performed pattern recognition, control said feedback member to perform actions corresponding to said motions, whereby said actions of said feedback member are individually and simultaneously controlled by said patient via said intended motions.

Methods for controlling an aspect of an application in a mobile or wearable device and a mobile or wearable device user's representation in real time are described, where the user is performing a gait activity with a gait cadence, and the gait cadence is used for control. Additional user's mobility characteristics leveraged for control may include velocity and stride length, and the sensors utilized to obtain any contextual information may be accelerometers.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for geofencing and location tracking for predicting and limiting disease exposure. In some implementations, location tracking data is received indicating locations of user devices over time. Location tags specifying visits of the user devices to different locations indicated by the location tracking data are defined. A geofence is assigned to each of the location tags to specify a geofenced area corresponding to the location tag. Disease transmission scores are assigned to first location tags representing visits of a first user. A disease exposure score is determined for a second user whose user device is determined, based on the location tracking data, to have entered at least one of the geofenced areas corresponding to the first location tags.

A posture detection system for detecting a user's posture according to the embodiments includes a pressure sensor unit, a controller, a feedback mechanism, and a display unit. The pressure sensor unit has a sheet shape or a padded shape and includes plurality of sensors. Each of the sensors is configured to detect a pressure applied from the user. The controller is configured to classify the user's posture based on detection data detected by the pressure sensor unit. The feedback mechanism is configured to provide feedback to the user by vibrating based on a result of the classification. The display unit is configured to perform a display according to the result of the classification.