A medical monitoring system for use in residential facilities, nursing homes, or home environments is disclosed. The system utilizes a variety of modules and wearable medical devices that convey vital patient information to a series of smart hubs which are connected to the cloud. In the event a change in medical status of a patient occurs, the health care workers receive an Alert notifying them of which specific patient needs attention. The system is monitored using a specialized dashboard.

A dynamic neuropsychological assessment tool according to an embodiment utilizes speech recognition, speech synthesis and machine learning to assess whether a patient is at risk for a neurological disorder, such as Alzheimer's disease. The dynamic neuropsychological assessment tool enables self-administration by a patient. The tool performs pre-test validation operations on the test environment, test equipment, and the patient's capability for performing the test at that time. The tool also enables dynamic modification of a questionnaire presented to the patient while the patient completes the questionnaire. Also provides the dynamic modification of which tests to present the patient with. The modification can be rule based or modified by a provider. The dynamic neuropsychological assessment tool enables providers and administrators to modify and improve tests and validate them using machine learning based on previously completed assessments and results.

Improved optical coherence tomography systems and methods to measure thickness of the retina are presented. The systems may be compact, handheld, provide in-home monitoring, allow the patient to measure himself or herself, and be robust enough to be dropped while still measuring the retina reliably.

Provided is an exacerbation prediction device equipped with a respiration sensing means of continuously sensing respiration data of a patient, a calculation means of calculating stable respiration data that are respiration data during a condition in which a respiratory rate is lowered and stable for a certain period of time from the sensed continuous respiration data of the patient, and a prediction means of predicting occurrence of an acute exacerbation in the patient in accordance with the stable respiration data calculated during a certain period of time.

Presented is a system and method for assessing the functional ability of a person to perform a task. The system comprises: a task identification unit adapted to identify the task to be performed by the person; and a task complexity unit adapted to obtain a task-specific complexity signal representative of a required level of functional ability to perform the identified task. A functional ability unit is adapted to obtain a functional ability signal representative of a determined functional ability of the person. An assessment unit is adapted to determine an ability of the person to perform the identified task based on the task-specific complexity signal and the functional ability signal.

A travel distance calculation device is configured to: add a first distance between a first main sensor and a hub sensor to a travel distance when a person is detected by the hub sensor provided in a third space connecting a first space and a second space after the person is detected by the first main sensor provided in the first space; add a second distance between a second main sensor and the hub sensor to the travel distance when the person is detected by the hub sensor after the person is detected by the second main sensor provided in the second space; and add no third distance between the first main sensor and the second main sensor to the travel distance when the person is detected by the second main sensor after the person is detected by the first main sensor.

Embodiments of a wearable monitoring device system can include one or more dry ECG electrodes and a processor that can be configured with one or more algorithms for detecting atrial fibrillation (AF) from sensed ECG signals sensed by the one or more dry ECG electrodes, and optionally other signals. In some embodiments the algorithms include one or more AF detection algorithms and optionally a noise detection algorithm. In some embodiments the wearable monitoring device or a remote system that receives data from the wearable medical device may calculate and/or characterize AF burden from ECG signals sensed by the one or more dry ECG electrodes.

A method can include receiving, using one or more processors, a first record including a first data associated with a personal identification from a first database, receiving, using the one or more processors, a second record including a second data associated with a user identification from a second database, pairing, using the one or more processors, the first data and the second data based upon a shared data item contained in the first record and the second record, and displaying, using one or more processors, a report based upon the first data and the second data.

In one embodiment, a computer-implemented method includes receiving, from a computing device of a clinician, an image of a credential issued to the clinician, where the credential pertains to healthcare. The method also includes extracting information from the image of the credential, where the information includes an expiration date of the credential. The method also includes storing the image of the credential and the expiration date of the credential in a database, receiving, from the computing device of the clinician, a selection to join a home health agency, and transmitting, to a computing device of the home health agency, a notification pertaining to the credential issued to the clinician, where the notification indicates whether the credential is active based on the expiration date.

Provided are transdermal microneedle-based devices for sensing the presence and concentration of analytes such as electrolytes, biomarkers, drugs, and proteins in interstitial fluid. Also provided are methods and systems to transmit the data obtained by wired or wireless connection to a receiver and to relay the data to the user or a clinician.