Systems, methods, and devices for remote health monitoring and management

Inventors

RAMESH, MANEESHA VINODINI • PATHINARUPOTHI, RAHUL KRISHNAN • RANGAN, EKANATH SRIHARI

Assignees

Amrita Vishwa Vidyapeetham • Nokomis Inc

Abstract

A remote health monitoring system, method and device is disclosed. The systems utilize one or more sensors, data aggregation and transmission units, mobile computing devices, processing, analytics and storage (PAS) units, and a framework based on a novel location- and power-aware communication systems and analytics to notify and manage patient health. Methods to transmit data to a PAS unit through the patients' smart phone that is connected to internet, abnormality detection in the data, advanced analytical diagnostics and communication system between the health service provider (HSP) and patient are also provided. The health monitoring systems, methods and devices allows for continuous monitoring of the patient without disrupting their normal lives, provides access even in sparsely connected and remote regions which lack good healthcare facilities, allows intervention by specialized practitioners, and sharing of resource or information in the existing healthcare facilities.

Core Innovation

The invention provides a remote monitoring method and system that obtains sensor data from one or more sensors attached to the patient's body and transmits the sensor data to a first mobile computing device through a wired or a short range wireless communication network. The first mobile computing device then transmits the sensor data to a processing, analytics and storage (PAS) unit through a wireless communication network. Abnormalities are detected by periodic assessment of the sensor data in the first mobile computing device, the PAS unit, or a combination thereof.

Abnormalities are converted into a quantized severity in the PAS unit by converting raw sensor values to a series of clinically relevant severity symbols arranged in a patient specific matrix (PSM). A machine learning model identifies the one or more abnormalities that exceed a personalized severity threshold over the assessment period. The personalized severity threshold for the patient is determined from sensor data, inter-sensor correlation, patient's historical data, doctor's inputs, inter-patient machine learning models obtained from hospital information system (HIS), or a combination thereof.

The PAS unit generates an alert measure index based on the personalized severity threshold. Notifications are sent to the first mobile computing device and to a second mobile computing device connected to a Health Service Provider (HSP). The notification to the HSP includes an estimate of time available to the HSP for effective intervention, and the medium of notification to the first and second mobile computing devices is determined based on at least data criticality.

Claims Coverage

The relevant independent claims are directed to a remote monitoring method, a remote monitoring system, and a computer program product. Across these independent claims, the core coverage includes periodic abnormality detection, quantized severity generation using clinically relevant severity symbols in a patient specific matrix (PSM), machine-learning-based personalization of a severity threshold, generation of an alert measure index, and notifications to a Health Service Provider (HSP)-connected device with time-available estimation and data-criticality-based notification medium selection.

The independent claims consistently cover a remote monitoring workflow in which body-attached sensor data is periodically assessed to detect abnormalities, mapped to quantized severity in a patient specific matrix, and evaluated against a personalized severity threshold determined by machine learning and patient-related inputs. The claims further cover alert measure index generation and dual-device notifications, including an HSP notification with time-available estimation and notification medium selection based on data criticality.

Stated Advantages

Documented Applications