Invented by Ammar Al-Ali, Masimo Corp

The market for medical characterization systems has been experiencing significant growth in recent years. These systems play a crucial role in the healthcare industry by providing accurate and detailed information about various medical conditions, enabling healthcare professionals to make informed decisions and provide better patient care. Medical characterization systems are used to analyze and evaluate different aspects of a patient’s health, such as genetic makeup, physiological functions, and disease progression. These systems utilize advanced technologies, including imaging techniques, genetic testing, and molecular diagnostics, to gather data and generate comprehensive reports. One of the key factors driving the growth of the medical characterization system market is the increasing prevalence of chronic diseases. According to the World Health Organization, chronic diseases, such as cardiovascular diseases, cancer, and diabetes, are the leading cause of mortality worldwide. Medical characterization systems help in the early detection and diagnosis of these diseases, allowing for timely intervention and treatment. Moreover, the advancements in technology have led to the development of more sophisticated and accurate medical characterization systems. For instance, the introduction of next-generation sequencing has revolutionized genetic testing, enabling healthcare professionals to identify genetic mutations and variations associated with various diseases. This has opened up new avenues for personalized medicine and targeted therapies. Another significant factor contributing to the growth of the market is the rising demand for personalized medicine. With the increasing understanding of the genetic and molecular basis of diseases, there is a growing emphasis on tailoring treatments to individual patients. Medical characterization systems play a crucial role in this process by providing detailed information about a patient’s genetic profile and disease characteristics, enabling healthcare professionals to develop personalized treatment plans. Furthermore, the increasing adoption of electronic health records (EHRs) and the digitization of healthcare data have created a vast amount of information that can be utilized for medical characterization. These systems can integrate with EHRs and other healthcare databases, allowing for seamless data exchange and analysis. This integration enables healthcare professionals to access comprehensive patient information and make more informed decisions. The market for medical characterization systems is also being driven by the growing focus on precision medicine and the need for more accurate and reliable diagnostic tools. As healthcare systems strive to improve patient outcomes and reduce healthcare costs, there is a growing demand for advanced diagnostic technologies that can provide precise and actionable information. Medical characterization systems fulfill this need by offering detailed insights into a patient’s health status, enabling healthcare professionals to make more accurate diagnoses and treatment decisions. In conclusion, the market for medical characterization systems is witnessing significant growth due to the increasing prevalence of chronic diseases, advancements in technology, the demand for personalized medicine, and the focus on precision medicine. These systems play a crucial role in improving patient care by providing accurate and detailed information about various medical conditions. As the healthcare industry continues to evolve, the demand for medical characterization systems is expected to further increase, driving innovation and advancements in this field.

The Masimo Corp invention works as follows

A medical characterisation system is configured for input of medical-related discrete and continuous data to calculate a characterization time line indicative of the physiological condition of an organism. A data source in sensor communication with a patient to generate a constant parameter. A data source can also provide test data to the patient during a test. A characterization processor has access to the test data at a results time. The characterization process is also responsive to a continuous parameter in order to generate a medical characterisation as a function time. The characterization processor can update the medical characterisation in light of the test results as at the time of the test using a characterization analyzer.

Background for Medical characterization system

A typical multi-parameter monitoring system (MPMS), derives several medical parameters, and displays them as a variety of waveforms and readouts. A MPMS responds to sensors that are attached to patients and actively responds the patient’s physiological state. However, the patient monitoring does not include test measurements or other discrete data, previously recorded sensor data, or parameters, and physiological data without a specific time reference, such as genetic data, family history, and previous diagnoses. A MPMS also does not include a medical description of a patient which includes the time associated with discrete data and test measurements, such as the time of the test or the duration of the parameter recording. MPMS information cannot be dynamically controlled by the user to include or exclude data to determine an overall impact on patient characterization.

A medical characterization system has a configuration that allows medically-related continuous data and discrete parameters to be inputted to create a characterization time line indicative of the physiological condition of an organism. The medical characterization systems consists of a parameter processor, discrete data source, and characterization analyzer. The parameter generator communicates with the living being via sensor to produce a continuous parameter. The characterization processor responds to the continuous parameter to produce a medical description of the living entity as a function time. The discrete data sources provide a datum that is responsive to the living thing at a first instance and which the characterization processor can access at a later date. The characterization processor can update the medical character in light of the datum from the first time using a characterization analyzer.

In different embodiments, the system for medical characterization also includes an analyzer model that is in communication with the characterization analyser to determine the impact of the medical character update over time. The analyzer model includes a selectionable upward shift, downward aging or upward ramp. The data source is connected to the characterization processor via a data storage, so that the characterization analyser can update the past parts of the medical characterisation with newer data. A person can control medical characterization updates using an input/output device. In one embodiment, an input/output tool displays a test epoch that can be selected at first and a result epoch corresponding to the test epoch displayed at second. In one embodiment, the analyzer is responsive to either a therapy time period or a test period in relation to a result period.

Parameters generated by sensors communicating with a human being are another aspect of a system for medical characterization. The parameters which are indicative of a person’s physiological state are used to calculate a medical characterization. At a specific test time, a medical test is conducted on the individual. The result of the medical test is received later. “The medical characterization will be updated according to the result of the medical test at the time of the test.

In various embodiments, a medical characterization is a model of how the medical characterization behaves over time as if it were undergoing a medical test. The medical characterization can be displayed as a function over time. On the display, the test time and the results time are displayed as test and result epochs. A user must select at least one of the result epoch or the test epoch to start the updating. In response to selecting, the test model is applied as of the test time to the medical characterisation. On the display, a therapy time is displayed as a epoch. Therapy effectiveness is the behavior of a medical character over time as a response to a treatment. The display shows a time period for the therapy. The selected therapy epoch, the model of therapy effectiveness is applied to the medical description as the response.

Another aspect of a system for medical characterization is an apparatus that consists of a data source and a characterization processor, as well as a characterization analyser. The data source can provide a continuous parameter timeline as well as a discrete result based on the medical status of a person at a given test time. The characterization processor communicates with the data source to calculate the medical characterization for the living being based on the continuous parameter as well as the discrete result. The characterization analyst updates the continuous parameter time line according to the discrete result at the current test time.

In various embodiments, there are three processors: a characterization processor, an engine processor and a model processor. The characterization process has an input selector which allows the user to choose a current input data or a synchronized data input for a medical data out put. The engine of the processor inputs medical data to generate a medical characterisation. The processor model is used to determine how the medical characterisation is calculated using the medical data. The analyzer of the characterization analyzer combines both current and recalled data to produce sync data based on an analyzer model. The medical characterization is output to a display by a graphics generator. Marker generators display test and result results on the display along with the medical characterisation. Analyzer models determine the impact of a test on the medical characterisation. The analyzer model also indicates, based on the test results, the effectiveness of a previous therapy.

A medical characterization system can be configured to accept real-time or non-real-time medical data and parameters in order to calculate a risk time line that indicates the probability of death or serious illness due to an injury, disease, or other physiological condition. The risk timeline is updated dynamically over the past and present to take into account newly received data or parameters. In one embodiment, a medical characterization system includes a sensor that communicates with a patient to create continuous data streams that indicate the patient’s physiological state. Risk timelines are generated by a processor that is responsive to the parameterizer. The risk processor is controlled by a risk analyzer, which modifies the timeline of the risk based on new information about the patient. This includes medical tests, diagnoses, and treatments, among others. The risk analyst relates the new information to the original time. A medical characterization system allows the user to dynamically add or remove individual parameters or selected data, or groups of parameters and/or data to determine the impact both on the past and the present risk timeline.

Although a medical characterisation system can be described in terms of calculating and generating dynamically adjustable medical risk characterization, other embodiments may reflect a wide range of medical characteristics both general and specific such as fitness, wellness or competitive readiness for athletes to name but a few. In addition, while an embodiment of a system for medical characterization is described in relation to a single timeline, a system for medical characterization can simultaneously calculate and display multiple characteristics. In addition to or in place of an overall timeline of risk, the characterization could be multiple specific risk timelines such as a range of risks to an individual’s circulatory system, respiratory system, neurological, digestive, urinary, immune and musculoskeletal systems.

DESCRIPTION DU DRAWINGS

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