Smartphone with automatic context switching to Real-Time Operating System for Critical Health Analytics
Publication Date: 2014-Sep-29
The IP.com Prior Art Database
Disclosed is a device embodiment wherein a Smartphone can act as a Smartphone for typical Smartphone functions as well an intelligent device to capture the health-data and perform Health Inteliigence. These functions will be performed by two Operating Systems [OS]; General Purpose OS [GPOS] and RTOS [Real-Time OS]. The Smartphone can do automatic context switching to real-time mode for Critical Health Data Analytics automatically by sensing health data. User can also have the option to manually switch the mode of the Smartphone from Normal to Critical Health Care. Critical Health Care Analytics data shall be captured, processed and stored instantly on a smartphone device. When the parameters with respect to a particular ailment becomes more in number the sensory data flowing in streams to the streaming software becomes complex. Every stream of patient’s health data is classified analyzed in near real time. The software extracts, transforms and stages the data. Data is staged in caching memory of smartphone so that analysis can be carried out near real-time. Analyzed multi stream data is matched with the existing pre-defined pattern from the database. This shall conclude that the person is having a similar ailment because of the pattern has matched for a certain disease condition. The input stream of a particular health data shall be matched with patients own historical data and reference data. Other features and advantages can be realized through other typical embodiments.
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Smartphone with automatic context switching to Real -Time Operating System for Critical Health Analytics
Summary of the solution:
The concept of the solution is to automatically context switch Operating Systems on a Smartphone on sensing Health Care data. A GPOS that carries out the task of a Smartphone of CALL, SMS and INTERNET and RTOS that carries out the Health Intelligence and Critical Health Analysis using protected memory space and individual thread for each stream of health data using. Trend Match based time partitioning can be performed which is shown below.
The Smartphone can automatically switch from Normal Mode to Critical Health Care Mode wherein the health data will be captured, processed, analyzed and stored by the RTOS. If a
phone-call arrives during the Critical Care Mode the GPOS shall process the call.
The concept of the solution is also to have Real-Time Critical Health Analysis & Intelligence by
producing trend reports based on the captured health data and processing the same using RTOS. The health care analytics on the Smartphone shall happen as the data is getting streamed from various health monitoring devices on the body of the patient. The algorithm for Critical Health Care shall reside on the Smartphone where the data capture, analytics and storage components in general.
The real-time operating system shall also store the various health data streams coming as input to the Smartphone in a mini Health Data Warehouse on it. Parameter patterns from the mini Health Data Warehouse that are critical or alerting shall be compared in nearness to the input streaming data and the pattern therein to alert the patient / consultant of alarming conditions based on instant analytics.
Problem in detail
There is no dedicated real-time Operating System on the Smartphone that can carry out the function of Critical Healthcare Analytics with automatic context switching. Healthcare data flows from the health monitoring devices attached to the patient's body to external computer systems exclusively. For e.g. for Holter Monitor test which captures the heart's electrical impulses from different heart nodes on the monitoring apparatus. The collected data is fed to the computer system with the analysis/plotting program in the hospital / clinic. Similarly Blood sample parameters are entered / stored on an external computer system. Either the data needs to be fed to the analysis system externally or the patient should be present in the hospital with the analysis system connected to the patient. For various other ailments/diseases there is a gap between collecting the data and feeding it to the analysis system which is external.
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Figure 1 above shows how conventionally a data is collected in As-Is scenario.
Figure 2 above shows a Smartphone with Dual OS; GPOS [General Purpose Operating System ] & RTOS [Real-Time Operating System]
Problem and limitation
Healthcare data from patient is not collected and the...