Patent Publication Number: US-9402597-B1

Title: Mobile vascular health evaluation processes

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     Benefit Claim 
     This application claims the benefit under 35 U.S.C. §119(e) of provisional application 61/694,728, filed Aug. 29, 2012, the entire contents of which is hereby incorporated by reference as if fully set forth herein. 
    
    
     FIELD OF THE INVENTION 
     The present disclosure generally relates to medical devices and medical diagnostic methods, and more specifically relates to computer program applications and techniques for assessing health conditions of elements of the vascular system. 
     BACKGROUND 
     The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section. 
     In humans, negative vascular condition has been associated with or is known to be symptomatic with a variety of serious diseases including coronary artery disease, hypertension, stroke, kidney disease, muscular skeletal disorders, nervous system disorders, respiratory diseases, cardiac rhythm disease, diabetes, and others. For example, reduced elasticity of the coronary arteries may indicate the presence of plaque on the walls of the arteries and may contribute to myocardial infarction. Vascular function information also may be useful in early recognition of sepsis, hypertension, hypotension, or respiratory dysfunction, and cardiac rhythm dysfunctions. Accurate measurements of the elasticity, thickness, and mechanical performance of blood vessels in conducting blood flow may permit better evaluation of diseases that are associated with negative vascular health and recommendation of a variety of therapies. 
     However, in the state of the art, vascular measurements typically require elaborate equipment and can only be performed in a clinical setting on a periodic basis. For example, one typical method involves using Doppler sonography systems to obtain acoustic readings from the peripheral principal arteries from one or more body locations, such as the ankles. Most systems are large, expensive, and normally capable of use only in a medical office. Other vascular systems try to measure vascular wall thickness, so that it is difficult to accurately measure abnormal plaque from normal artery wall. Further, these systems normally are not integrated with other valuable measures of personal health. 
     Devices are available that measure vital signs, blood glucose, gases in the body, respiratory activity, cardiac rhythm and other aspects of physiology. For example, smartphone applications or “apps” are available to enable an individual to take their pulse using a smartphone, and other apps can take pictures of food and provide readouts of food contents and calories. However, these measurements and apps may be incapable of integrating with other valuable health information or providing a global assessment, involving vascular function, of healthy or unhealthy status. 
     SUMMARY OF THE INVENTION 
     The appended claims may serve as a summary of the invention. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The present invention is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements and in which: 
         FIG. 1  is a block diagram that illustrates a computer system upon which an embodiment of the invention may be implemented. 
         FIG. 2  illustrates an example mobile measurement device. 
         FIG. 3  illustrates an example process of generating recommendations based at least in part on vascular function information. 
         FIG. 4  illustrates a networked physiological measurement system in one example implementation. 
         FIG. 5  illustrates data flows in example processes of performing a global assessment of health with correlations of various data sources and sensors relating to vascular systems. 
     
    
    
     DESCRIPTION OF EXAMPLE EMBODIMENTS 
     In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the present invention. It will be apparent, however, that the present invention may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form in order to avoid unnecessarily obscuring the present invention. 
     Overview of Example Mobile Measurement Devices 
     In an embodiment, a mobile measurement device is configured to process information from the environment and human physiology and anatomy.  FIG. 2  illustrates an example mobile measurement device. In an embodiment, the mobile measurement device  202  comprises: a computing device  204 ; one or more sensors  206  that are coupled to the computing device using one or more corresponding compatible digital interfaces  208 ; and vascular function logic  210  encoded with instructions which when executed perform determining and storing vascular function information  211  and one or more of: values of metrics or parameters  212 ; physiological analysis  214  of the parameters and the vascular function information; recommendations  216  for actions that an individual or healthcare provider should take in response to the recommendations or parameters. 
     In various embodiments, the computing device  204  comprises any of: a smartphone; a tablet computer; a laptop computer or other personal computer; a workstation; a watch computer; a ring-mounted computer; an active steering wheel of a motor vehicle; a hat-mounted computer; a helmet-mounted computer; an eyewear-mounted computer. In other embodiments, the computing device  204  comprises or is integrated with any of: a body garment such as a short, swimsuit, vest, shorts or shoes. 
     In various embodiments, the sensors  206  comprise at least one of the following: an ultrasound sensor configured to acoustically measure structure, performance or other metrics associated with a blood vessel or other element of the vascular system and to cooperate with the program logic to provide output waveform data representing acoustic measurements of blood flow in a blood vessel, and provide vascular structure or performance metrics  212  based on bidirectional vascular waveform analysis. In an embodiment, one of the sensors  206  or the vascular function logic  210  perform bidirectional waveform Doppler ultrasound analysis that can measure or indicate the elasticity of one or more blood vessels. In an embodiment, the vascular function information  211  comprises or is based on the bidirectional waveform Doppler ultrasound analysis. 
     In various embodiments, the sensors  206  comprise one or more of any of the following: an infrared sensor, crystal technology sensor, sensors configured for use with augmented reality technology, auto-fluorescence sensors, or light-based physiological monitor; a blood pressure sensor; a pulse sensor; a respiratory rate sensor comprising, for example, one or more chest patches, wrist patches, and/or chest straps; a body temperature sensor; an oxygen absorption sensor; a carbon dioxide sensor; a nitric oxide sensor; a blood glucose sensor; a sensor of electrolytes, nutrients in the circulation, or other metrics; one or more contact lenses configured to measure capillary blood flow; a flow meter; a spirometer; a mouthpiece. In an embodiment, at least one of the sensors  206  is configured to sense and store at least one measurement relating to vascular structure, status or performance. Thus, as alternatives to using ultrasound as a form of energy for sensing, in some embodiments sensors that use infrared spectroscopy, auto-fluorescence, crystal technology, augmented reality technology, and other forms of energy or radiation may be used to obtain vascular waveforms for analysis. 
     In various embodiments, the vascular function logic  210  comprises one or more of any of the following: non-volatile random access memory (NVRAM); flash memory; an application-specific integrated circuit (ASIC); a field programmable gate array; read-only memory (ROM) including any of electrically erasable ROM (EEROM) or electrically programmable ROM (EPROM); disk storage; any of which may be configured with stored program instructions that are arranged to perform the processes that are further described herein. Wireless devices such as wireless probes may be used as sensors  206 . 
     In various embodiments, the vascular function information  211  provides metrics, reports, or values that indicate overall health attributes of blood vessels or other components of the vascular system, or particular attributes of blood vessels or other components of the vascular system. Examples of attributes include elasticity of vascular walls; thickness of vascular walls; and an indication of whether a heart pulse cycle results in one, two, or three elastic responses of the vascular walls; presence or amount of plaque formation on the vascular walls. 
     In various embodiments, the vascular function information  211  includes phenotypic, genotypic, proteomic, and/or neural process information such as weight, blood pressure, cholesterol, genetic characteristics/diseases, biofeedback from the nervous system, etc. 
     In various embodiments, the vascular function information  211  may be used to generate, using vascular function logic  210  or other program logic, one or more reports, recommendations  216 , or protocols based on the vascular function information. Recommendations  216  may collectively and broadly represent reports and protocols as well as recommendations. In various embodiments, the reports, recommendations or protocols may comprise any of the following: a status report on vascular function; a list of options for medical intervention in the patient based on medical standards of practice based on one or more medical indications represented in the vascular function information; reports or recommendations suggesting sepsis, hypertension, hypotension, respiratory dysfunction, kidney function, heart rhythm, hydration level; a protocol for exercise; a protocol for sports performance; a protocol for patient lifestyle or changes in lifestyle; a protocol for patient stress management; a report of recommendations, or the expected effects of, any of several aspects of treatment including but not limited to hydration, nutrition, exercise, supplements, and medications. 
     In various embodiments, the mobile measurement device  202  may be configured to directly generate the vascular function information  211 , and the one or more reports, recommendations, or protocols based on the vascular function information. Alternatively, the mobile measurement device  202  may be activated or used in a clinical setting such as an emergency room, hospital ward or medical office. The mobile measurement device  202  also may be used or activated in non-clinical settings such as during driving a car, during exercise, during sleep, and during other activities. For example, in any of these embodiments, the mobile measurement device  202  may internally generate the vascular function information  211  and also provide logic for interfacing with an external host computer  220  to download the vascular function information; on the host computer, stored program logic may be configured to generate the one or more reports, recommendations, or protocols based on the vascular function information. 
     In this manner, the mobile measurement device  202  provides a useful interface between the patient and the medical office; the device may be used to collect a variety of physiological metrics from an individual, including at least one measurement of vascular structure, status or performance, which are then downloaded from the device to the host computer  220 . After downloading, program logic on the host computer  220  may be used to generate the one or more reports, recommendations, or protocols for disease intervention based on the vascular function information. Data collected over time can be used to better understand factors influencing the cardiovascular system. 
     Alternatively, after downloading data from the mobile measurement device  202 , an independent measurement of at least one measurement of vascular structure, status or performance is performed in association with the host computer. For example, in one approach, an individual uses the mobile measurement device  202  to monitor any of the physiological metrics described above, then downloads the metrics and transfers or provides the metrics to a healthcare provider via host computer  220 . In a clinical setting or quasi-clinical setting, the healthcare provider may use a conventional Doppler vascular sensor to capture an acoustic profile of the vascular performance of the same individual; for example, the healthcare provider could perform a Doppler vascular test of the peripheral arteries. The resulting acoustic waveform data may be combined with the metrics that have been downloaded from the patient&#39;s mobile measurement device  202  and, under control of program logic at the host computer  220 , used to generate the one or more reports, recommendations, or protocols. In various embodiments, the patient may transfer or provide the metrics to the healthcare provider by any of the following: connecting the mobile measurement device  202  to a personal computer that is owned or operated by the patient, downloading a data file from the device, and streaming, e-mailing or uploading the data file to the healthcare provider; going to the premises of the healthcare provider, connecting the device to a host computer that is owned or operated by the healthcare provider, downloading a data file from the device to the host computer. 
     In various embodiments, the sensors  206  may comprise units that can detect activity of the nervous system either centrally or peripherally. For example, waveform data from an electroencephalogram (EEG) unit may reveal brain activity that can be correlated to vascular waveform data to identify progress in therapeutic goals and/or the condition of the vasculature. 
     In various embodiments, the data from sensors  206  may be combined with results or detections of blood test measurements for substances such as cortisol, cholesterol, triglycerides, epinephrine, asymmetrical dimethyl argenine. In various embodiments, the data from sensors  206  may be combined with results or detections of urinalysis to identify blood glucose, proteins, ketone, or blood in the urine, and specific gravity of urine. Values obtained from any of the foregoing measurements or units can be correlated to vascular waveform data to identify progress in therapeutic goals and/or the condition of the vasculature. 
     Unlike prior approaches, the integration of physiological monitoring metrics with information about vascular function, obtained either in a clinical setting or directly from the monitoring device, enables generating improved overall health assessments or health status information. Further, reports in the embodiments herein provide an explanation of the effect of all the measured physiological functions on vascular health, or overall health. Embodiments typically integrate and incorporate at least one vascular study or vascular analysis, so that an evaluation of vascular health is an integral aspect of the reporting and recommendations herein. 
       FIG. 3  illustrates an example process of generating recommendations based at least in part on vascular function information. At step  302 , vascular function information is received from at least one Doppler vascular sensor that is used, for example, at the peripheral arteries, such as at the ankles, wrists, as well as the neck, chest or other site. One of the sensors  206  typically is a Doppler vascular sensor in an embodiment and obtains the vascular function information  211 , which may be received at step  302  and stored in the form of raw sensor data or as a rendered waveform or in any other form suitable for later analysis. 
     At step  304 , the process receives one or more other values of physiological metrics or parameters. In an embodiment, values at step  304  are received through one or more other sensors  206  and may include, for example, values for one or more vital signs such as pulse, blood pressure, oxygenation, etc. 
     At step  306 , the process performs a physiological analysis of the data that was received at steps  302 ,  304 . Step  306  may include determining trend values (“increasing,” “decreasing,” etc.) based on prior measurements from the same device, or whether the current magnitude of a particular value has crossed a particular threshold that is associated with a particular physiological condition or change or is associated with a particular qualitative or quantitative descriptor or condition, for example, “elevated”, “normal”, “baseline”, “exceptional,” “average,” “severe,” etc. 
     At step  306 , the process generates one or more recommendations for changes in behavior, activity, or treatment. Recommendations may comprise reports or protocols and may be based on stored tables that map the values obtained at step  302 , step  304  to particular recommendations, reports, or protocols. Step  306  also may include computation such as determining whether a particular value is greater or less than values stored in the tables, and/or comparing particular trend values to corresponding trend indicators stored in the tables. Data representations other than tables may be used. 
     OVERVIEW OF EXAMPLE USES 
     For the purposes of illustrating clear examples, in various embodiments, the wireless or mobile measurement device  202  described herein may be used in one or more of the following ways. The examples refer to certain input parameters, algorithms and resulting recommendations. In one embodiment, each algorithm may be implemented using one or more computer programs or other software elements, or other computer logic, and may implement the clinical state of the art reflecting the current standard of care. However, unlike past approaches, each algorithm receives as an input at least one element of digital vascular waveform data. Thus, the approaches herein can use vascular analysis as a contributing parameter in determining a resulting recommendation. Further, the integration of vascular analysis data means that a healthcare provider can correlate the other parameter values to the vascular data to result in a better assessment of the overall health of the individual, or to provide a better clinical judgment of responsive treatment that should be considered. 
     In particular, an improvement provided herein is in the contribution of vascular analysis data, obtained for example from a bidirectional Doppler ultrasound measurement of the peripheral arteries, in a health assessment with other biomedical parameters. The vascular analysis data is usable in individuals who are in a health state or an unhealthy state, to recognize responses of the vasculature to the individual&#39;s health state, activity or environment. The vascular analysis data may be used to recommend personal interventions and determine how other parameter values, or the responses or interventions, may be affecting vascular structure or performance. For example, the vascular analysis data might indicate only two instances of dynamic activities of arteries, which are reflected as two “bounces” in a waveform obtained from the vascular analysis. The vascular analysis data also might indicate particular values or changes in the width(s) of waveform(s) and/or the velocity of waveform(s). In response, a healthcare provider might recommend a relaxation exercise, breathing exercises, increasing hydration, specific aerobic exercises, and/or self-administer a supplement or medication. A subsequent vascular analysis performed shortly thereafter might reveal that the individual has achieved three (3) “bounces”, indicating improved vascular performance resulting from the relaxation exercise or other intervention as stated above. 
     The vascular analysis data may be used in combination with other apparatus such as ultrasound units that measure heart chamber activity or blood flow measurement apparatus. 
     Alternatively, a clinician may observe that a subject individual has elevated body temperature arising, for example, from heat exhaustion. With the availability of the vascular analysis data for the individual in addition to body temperature data, the clinician may be able to observe the effect of heat exhaustion on the vascular system. Further, the accumulation of data values from all other parameters may help explain anomalies that are seen in the waveform reflecting the vascular analysis. The combination of the vascular analysis data with other parameter values therefore permits a better global assessment of the individual and a better explanation of the individual&#39;s vascular response. 
     1. Use of Mobile Measurement Device to Motivate Change from Sedentary Behavior 
     John, a sedentary individual, is sprawled upon the couch in his living room, wearing or using a mobile monitoring device. Fortunately, in his view, his favorite television show has just begun. Based on data collected from the mobile monitoring device, John&#39;s first hour of enjoyable viewing corresponds to a reasonably normal vitality condition. However, after ingesting a rather fatty meal and continuous television viewing for three more hours, John&#39;s vitality signals begin to decline, as measured by the mobile measurement device  202  as follows: 
     
       
         
           
               
               
               
               
             
               
                   
                   
               
               
                   
                 Parameters: 
                 1 st  Hour: 
                 4 th  Hour: 
               
               
                   
                   
               
             
            
               
                   
                 Blood Pressure 
                 Normal 
                 Elevated 
               
               
                   
                 Pulse 
                 Normal 
                 Elevated 
               
               
                   
                 Respiration 
                 Normal 
                 Elevated 
               
               
                   
                 Oxygenation 
                 Normal 
                 Decreased 
               
               
                   
                 Nitric Oxide 
                 Normal 
                 Increased 
               
               
                   
                 Doppler Vascular Waveform 
                 Moderately Severe 
                 More Severe 
               
               
                   
                   
               
            
           
         
       
     
     The sensors  206  process these physical changes in real-time. During hour 4, John decides to connect his mobile measurement device  202  to his tablet computer (an example of host computer  220 ). In an embodiment, John couples a universal serial bus (USB) cable from his tablet computer to the mobile measurement device  202 . The mobile measurement device  202  contains a diagnostic computer program, which is automatically downloaded to the tablet computer and begins running as part of standard USB connection operations. During execution, based on the amount of change that the sensors detected in the 3-hour period, the diagnostic program generates and displays a report (an example of recommendations  216 ) to recommend a beneficial change in life activity as follows: 
     Algorithm Implementation &amp; Recommendation: 
     1. 20 minute walking activity 
     2. 8 fl oz. water consumption 
     3. 2 tablet aspirin intake to relieve blood pressure 
     4. Utilize inhaler to increase oxygenation 
     In response, John ceases his laziness and follows the step by step process. He continues to use or wear the mobile measurement device  202 , and then re-connects it to his tablet computer. The diagnostic program reports the following changes in metrics or parameters: 
                                                 Parameters:   Decline:   Ascent:                          Blood Pressure   Elevated   Normal           Pulse   Elevated   Normal           Respiration   Elevated   Normal           Oxygenation   Decreased   Normal           Nitric Oxide   Increased   Normal           Waveform   More Severe   Baseline                        
Results:
 
The individual&#39;s blood pressure steadily returns to normal after the intake of aspirin. The recommended use of an inhaler returns his Oxygenation and Nitric Oxide levels to stable. Drinking water decreases the flow viscosity in his vascular system. Most importantly, the waveform velocity reaches its healthy baseline value.
 
     2. Use of Mobile Measurement Device in Hospital Intensive Care Unit (ICU) 
     John was recently been admitted to the ICU. Upon arrival, healthcare providers are perplexed by John&#39;s symptoms. However, for the past day, John had been using his mobile measurement device  202  and has it with him. One of the healthcare providers connects the mobile measurement device  202  to a host computer  220  in the ICU, downloads or streams data from the mobile measurement device, and uses program logic on the host computer to generate a report of the following historical parameter values that the mobile measurement device had captured: 
     
       
         
           
               
               
               
               
             
               
                   
                   
               
               
                   
                 Parameters: 
                 5 hrs prior to Arrival: 
                 Point of Arrival: 
               
               
                   
                   
               
             
            
               
                   
                 Blood Pressure 
                 Normal 
                 Major Drop 
               
               
                   
                 Nitric Oxide 
                 Normal 
                 Normal 
               
               
                   
                 Respiration 
                 Normal 
                 Increasing 
               
               
                   
                 Temperature 
                 Normal 
                 Increasing 
               
               
                   
                 Pulse 
                 Normal 
                 Increasing 
               
               
                   
                 Waveform 
                 Baseline 
                 Increasing Velocity 
               
               
                   
                   
               
            
           
         
       
     
     Based on the collected data, the host program provides the following recommendation: 
     Algorithm Assessment: 
     1. Body Inflammatory State 
     2. Potential Diagnosis: Sepsis 
     
       
         
           
               
               
               
             
               
                   
                   
               
             
            
               
                   
                 Action 
                 Skin infection diagnosis and treatment. 
               
               
                   
                   
                 Perform blood cultures. Increase antibiotics. 
               
               
                   
                   
               
            
           
         
       
     
     The healthcare provider evaluates the assessment and recommended action, and decides to perform the recommended actions. As a result, the following physiological effects are observed: 
     Results: 
     Patient temperature returns to normal. Nitric oxide returns to normal. Pulse returns to normal. Blood Pressure becomes normalized. Temperature cools down. Waveform velocity returns to normal. 
     3. Use of Mobile Measurement Device in Athletics 
     Alice, marathon runner, regularly uses her mobile measurement device  202 , which stores a data file indicating the following baseline parameters and goals: 
     
       
         
           
               
               
               
               
             
               
                   
                   
               
               
                   
                 Parameters: 
                 Baseline:  
                 Goal: 
               
               
                   
                   
               
             
            
               
                   
                 Weight 
                 Average 
                 Exceptional 
               
               
                   
                 Blood Pressure 
                 Average 
                 Above Average 
               
               
                   
                 Pulse 
                 Average 
                 Above Average 
               
               
                   
                 Respiration 
                 Average 
                 Above Average 
               
               
                   
                 Nitric Oxide 
                 Average 
                 Exceptional 
               
               
                   
                 Oxygen 
                 Average 
                 Exceptional 
               
               
                   
                 Waveform 
                 Average 
                 Exceptional 
               
               
                   
                   
               
            
           
         
       
     
     Over a training period of six months, Alice periodically downloads data from her mobile measurement device  202  to her laptop computer and reviews the data using program logic on the laptop. The program logic reports that, based on the data from the mobile measurement device, her body has met her goals. She is now prepared for the big race. 
     During the marathon, Alice continues to use her mobile measurement device  202 . The mobile measurement device  202  comprises a near-field radio transceiver  230 , such as a Bluetooth transceiver, that communicates with host computers having compatible transceivers that are located at waypoints on the race route. At various waypoints, Alice&#39;s team members, healthcare providers or race officials download data from Alice&#39;s mobile measurement device  202  to laptop computers at the waypoints. Host programs on the laptop computers periodically generate reports of Alice&#39;s performance. Additionally or alternatively, the mobile measurement device  202  comprises internal program logic that can display, on a wrist-mounted display, eyewear-mounted display or other output device  240 , a brief report or indication of the following results. In either alternative, the vitality sensors remain intact to ensure Alice&#39;s physical condition is suitable to continue racing: 
                                                Distance:   Health:                       1 st  Mile   Ok           2 nd  Mile   Ok           3 rd  Mile   Ok           4 th  Mile   Ok           5 th  Mile   Decline                       Parameters:   Status:                       Blood Pressure   Dropped below baseline           Pulse   Slight Increase           Body Temperature   Slight Increase           Waveform   Slight Increase                        
Algorithm Assessment:
 
     1. Individual&#39;s bodily temperature increased 
     2. Blood pressure is dropping 
     3. Pulse is increasing 
     Algorithm Recommendation: 
     Subject is tending towards dehydration. Take more time at water stations. Consume more carbohydrates to replenish energy. Resume Running and decrease rate of pace slightly. 
     In this example, one or more of the values indicated above for Health, Status, Algorithm Assessment and Algorithm Recommendation may be represented in stored data that is maintained in the mobile measurement device  202 , but not displayed or reported to Alice. Alternatively, one or more of the metrics may be reported to Alice or using the laptop computer at the waypoints; the alternatives are design choices that may depend, for example, on the size of display that is available on Alice&#39;s device. For example, if Alice is using a wrist-mounted computer or other output device  240  that has a liquid crystal display (LCD) having limited display capability, then the metrics may be reported in more limited form. Alternatively, if Alice&#39;s mobile measurement device  202  comprises a smartphone with a high-resolution color graphics display  250 , then more elaborate reporting may be provided. 
     Continuing with the example, assume that Alice takes heed of the recommendations of the mobile measurement device  202  and changes her running behavior. Thereafter, the mobile measurement device  202  collects data indicating the following: 
                                             Distance:   Health:                          6 th  Mile   Improved!           7 th  Mile   Ok           8 th  Mile   Ok           9 th  Mile   Ok           10 th  Mile    Ok                        
Algorithm Assessment:
 
     1. Vital signs are normal and stable 
     2. Body is adequately hydrated 
     Algorithm Recommendation 
     The body may continue further exertion! 
     Alice continues to review reports or indications from her mobile measurement device  202  as she enters later stages of the race. The mobile measurement device  202  collects data indicating the following: 
                                             Distance:   Health:                          11 th  Mile   Ok           12 th  Mile   Ok           13 th  Mile   Ok           14 th  Mile   Ok           15 th  Mile   Ok           16 th  Mile   Ok           17 th  Mile   Ok           18 th  Mile   Declining           19 th  Mile   Declining           20 th  Mile   Sharp Decline                        
Algorithm Assessment:
         1. Health parameters started falling after the 18 th  Mile.   2. Experienced a sharp decline after the 20 th  Mile.   3. Further analysis of parameters required:       

                                                Parameters:   18 th  Mile:   20 th  Mile                   Blood Pressure   Moderate   Severe           Pulse   Moderate   Severe           Respiration   Moderate   Severe           Body Temperature   Moderate   Severe           Waveform   Moderate   Severe                                     Ambient Temperature   Sharp decrease in humidity                    
Algorithm Assessment:
 
     1. All Parameters are experiencing a sharp decline. 
     2. Further Decline is hazardous. 
     3. Individual is severely dehydrated. 
     Algorithm Recommendation: 
     1. Halt running immediately. 
     2. Consume water and carbs to replenish body. 
     3. Continue walking until vitality signals increase. 
     Results: 
     Because it was much hotter towards the end of the race, our athlete experienced severe dehydration at her 20 th  mile. Without her vitality sensors, there would be no way to accurately determine her state of condition and hydration. 
     In each of the preceding examples, the metric “Waveform” represents data obtained from at least one vascular sensor  206  and is based on bidirectional waveform analysis. “Bidirectional” refers to the fact that in normal circulation, blood is pumped and flows in a first direction through a blood vessel, then briefly reverses direction, and then is pumped and flows again in the first direction. For example, a miniaturized Doppler vascular sensor may be used as one of the sensors  206  to generate and store data representing an acoustic waveform based on detecting the flow of blood in one or more blood vessels. This data is indicative of the elasticity of the blood vessels, among other metrics; for example, a wider waveform is observed to indicate greater elasticity of the walls of the blood vessels, larger volume of blood flow, or a thinner waveform is observed to indicate lesser volume and less elasticity, at least at the measurement site, and greater elasticity is associated with reduced risk of certain major diseases such as CVD, diabetes and respiratory ailments. Through data collection, observation of velocity and volume of waveform of the first, second, third, and sometimes a fourth waveform, the processes herein will be able to correlate more accurately the status of physiological responses. The inventor fundamentally has recognized that combining vascular function information  211  representing vascular condition with one or more other physiological metrics  212  will provide a better capability for evaluating overall health of an individual and for providing recommendations for activity or treatment. Further, the integration of vascular bidirectional waveform analysis data representing vascular condition with a plurality of other physiological metrics will provide a superior capability for evaluating overall health of an individual and for providing recommendations for activity or treatment. Still further, having multiple examples of vascular data available over a long period of time can provide better environmental information on which health assessments may be based. Moreover, the vascular data is expected to indicate, relate to, represent or be proportional to the relative condition of the endothelium, a thin layer of cells that lines the interior of vascular vessels. Its condition or other indicators derived from the vascular data are believed to represent one or more factors or variables that are independent with respect to contribution to the onset of vascular disease and/or an independent contributing factor in the onset or occurrence of atherosclerosis or myocardial infarction. 
     Physiological Measurement System and Methods Featuring Doppler Vascular Measurement 
       FIG. 4  illustrates a networked physiological measurement system in one example implementation. 
     The elements of  FIG. 4  may be located entirely in a clinical setting such as a physician&#39;s office, or located in whole or in part with a patient. 
     In an embodiment, data collection system  12  is a computer that interfaces to network  14  and hosts server software  26  to receive and store signals and patient measurements and to perform analysis logic. Data collection system  12  typically comprises a laptop computer or other portable computing device that can be moved to different treatment rooms where patients are located, but the data collection system also could be a physician&#39;s home computer or multiple computers at a data center. Server software  26  consists of control programs that generally enable a physician to review measurements obtained from the Doppler system that is further described herein, or other data sources, and/or to review a complete electronic patient chart or record that includes historical vital signs measurements, records of interventions and medications, and other data. In one approach, electronic patient charts and the server software  26  are hosted on a separate server computer that is connected to network  14 . The data collection system  12  can be periodically connected to or disconnected from the network  14  depending on clinical needs. 
     The local network  14  may include a printer or other output devices for printing reports or other materials for physician or staff use. 
     A personal computer  16  is connected to the local network  14  and includes client software  24  and a display unit  22  that are accessible to a patient  18 . In a typical deployment the provider&#39;s office includes a kiosk, carrel, viewing room, or other private or semi-private area in which the patient  18  can access the personal computer  16  and view or interact with modules from the module library  30 . Alternatively the personal computer  16  may be located at a patient&#39;s home or business. The computer  16  may include a sound card, headphones, speakers or other audio output units. 
     A Doppler system  10  is connected to the personal computer  16  and comprises sensors that are placed preferably on the peripheral arteries  19  of the patient  18 . Peripheral arteries  19  may be at the ankles, wrists, or other peripheral locations of the body of the patient. In an embodiment, the Doppler system  10  has sensors that can be temporarily attached to the feet and ankles of a patient to acoustically detect pulses of the bloodstream in the circulatory system of the patient. The Doppler system  10  may include stored programs for generating and storing data representing signal waveforms derived from the acoustic measurements. Typically the data indicates the velocity of the bloodstream, at a particular measurement point in the vascular system, over time. An example is a modification of V-link software commercially available from Koven Technology Inc., Saint Louis, Mo., but other programs may be used. 
     The patient  18  also may own or have access to a mobile computing device  22 , which may comprise a tablet computer, smartphone or laptop that transports with the patient to various locations. In such an embodiment, one or both of the Doppler system  10  and physiological measuring device  20  may interface to the mobile computing device  22 , rather than to personal computer  16 , or to both. For example, the Doppler system  10  and physiological measuring device  20  may have wireless networking interfaces that can communicate through a wireless access point to the personal computer  16  or through network  14  to data collection system  12 . 
     The patient  18  may provide additional personal health data to the data collection system  12  in the form of data, files, or images that are stored on or obtained using a physiological measuring device  20 . For example, in some cases a patient  18  may perform measurements of blood pressure, pulse, respiration rate, temperature, or other data at home using instruments or measurement devices, store the measurements or data on the physiological measuring device  20 , and bring the device to the provider&#39;s office at the time of an office visit. Additionally or alternatively, client software  24  may facilitate communicating data from one or both of the Doppler system  10  and device  20  to personal computer  16  and to data collection system  12 . 
     The provider&#39;s office may include any number of additional computers that are networked using local network  14  for the purpose of entering measurements, chart data, vital signs, or other health information. For example, each workstation, examining room or other station of the provider&#39;s office may include a terminal or computer at which medical staff can enter data into the electronic patient chart for a particular patient. In some deployments the additional computers may consist of portable digital assistants, other portable computers, barcode readers, and other portable data entry or data viewing devices that are connected to the local network  14  using wireless signals and protocols. 
     Using this arrangement, the physician can collect and review a variety of patient-generated data and office-generated data including Doppler vascular data. Based on the data, the physician can select and provide each patient with a customized version of one or more reports or. The version provided to the patient is customized in relation to that particular patient&#39;s specific condition, pathology, physiology, personality, goals or treatment plan. 
     For example, the physician examining a significantly overweight patient may determine that the patient could benefit from detailed, patient-customized education relating to diabetes. At the time of an office visit or at another time, and while working with server software  26  at the data collection system  12  or another networked computer in the office and viewing an electronic patient chart for that patient, the physician would select a diabetes module from a list of modules in a module library. The physician would also customize the module for presentation to this particular patient in several ways. First, the physician can select one or more parameters of the module by interacting with a graphical user interface and program logic provided as part of the server software. Second, the physician can receive selections of module parameters that are determined automatically by the server software  26  based on the stored values in the electronic patient chart for the present patient. 
     Network  14  broadly represents one or more local networks, wide area networks, internetworks or internets using wire line, wireless, terrestrial or satellite links. 
     In an embodiment, server software  26  implements a service that uses various bodily measures or parameters, such as vital signs, blood glucose, gases in body, respiratory activity, exercise, nutrition and vascular function, to help achieve better vascular and overall health. The parameters may be measured automatically via wireless devices or mobile apps, or manually. Measurement using wireless devices may include receiving input from Withings&#39; wireless scale, Withings&#39; blood pressure monitor, Fitbit&#39;s activity monitor, or the Doppler system  10 . Measurement using mobile apps may include receiving data apps hosted on mobile computing device  22 , such as Heart Pal to record blood pressure and heart rate, Livestrong Calorie Tracker to record food intake and exercise, Daily Burn to scan bar codes of food items, and/or Mint Nutrition to get restaurant food nutritional information. 
     Obtaining patient data manually may occur through medical office visits at which test result data is collected using Doppler ultrasound measurements, laboratory tests, patient medical history and physical exams, or other sources. Obtaining patient data manually may occur through recording patient data values using at-home or other field equipment such as personally recorded data for diet and exercise routines, at-home scales, at-home blood pressure cuffs, at-home sphygmomanometers, or other devices. 
     In an embodiment, server software  26  is configured to generate and provide one or more interpretations of data that has been collected from devices  10 ,  20  via computers  16 ,  22 . The interpretations of data may be provided in any of several forms including reports, animations, and figures. Reports may include text or graphical reports that relate to patient health in relation to hypertension, obesity, diabetes, cardiovascular disease, or other issues. 
     Animations may include 2-dimensional or 3-dimensional representations of the blood flow in the arteries of the patient  18  with varying degrees of plaque formation and/or varying constituents such as fatty acid, glucose, or others. Animations may also depict blood flow across the whole body. Animations may be representative, rather than specific. That is, rather than attempting to accurately depict exactly the interior condition of the vascular system of the patient  18 , which cannot be known with certainty, the animations may have the same general graphic appearance for every patient but may illustrate different degrees of plaque formation or other constituents that the server software  26  has inferred based on analysis of the measured data from the patient  18 . 
     Figures may include a graphical image of a typical body image for the patient based on the patient&#39;s actual height, weight, age and sex data. In an embodiment, data received from patient  18  may include a digital image of the patient and server software  26  is configured to modify and re-render the digital image to illustrate that patient&#39;s ideal body image or a goal image. 
     In an embodiment, server software  26  is configured to provide educational information such as one or more explanations of interpretations of the data that has been received from the patient  18 . 
     In an embodiment, server software  26  is configured to provide one or more real time recommendations for the patient  18 , dependent on the health status of the patient. For example, in various embodiments the recommendations may include:
         Protocols for nutrition   Protocols for exercise   Protocols for sports performance   Protocols for patient lifestyle or changes   Protocols for stress management   Protocols for patient lifestyle or changes   Protocols for supplements/medications       

     In an embodiment, server software  26  is configured to record and track progress of the patient  18  with respect to one or more health metrics. Recording and tracking progress can involve using one or more devices or apps to repeatedly record parameters mentioned in real time, or close in time, or received through periodic inputs or uploads from the user. Recording and tracking progress also can involve creating and storing one or more journals, charts and figures that compile or consolidate patient data to allow the patient to track progress. 
     In an embodiment, server software  26  is configured to provide one or more reminders to the patient  18  to encourage continual engagement with the processes and systems that are described herein. In various embodiments, reminders may comprise any of notifications messages, alarms, and/or calendar reminders. 
     In an embodiment, server software  26  is configured to provide an interface between a physician and a user such as patient  18 . In an embodiment, server software  26  is configured to allow a physician to access data from patient  18  either using a terminal or computer to connect to data collection system  12  or to receive emails of data from the patient. In an embodiment, server software  26  is configured to allow the physician to relay messages to the patient. Examples of messages from physician to patient  18  may include positive feedback, negative feedback, scheduling appointments, and scheduling interventions. 
     In an embodiment, server software  26  is configured to provide an interface between the clinical setting and a non-clinical setting. For example, by storing and managing patient  18 , the server software  26  makes the patient data available for easy access at hospitals, medical offices, clinics or other locations. 
     In an embodiment, server software  26  is configured to provide social forums. Examples of social forums include patient to patient communication. Anonymity may be allowed and non-disclosure agreements may be enforced. In an embodiment, physicians may provide input in the social forums also. 
     The system as described has numerous uses and applications. A first set of applications are facilitated by using one or both of the devices  10 ,  20  on the peripheral arterial system, whether on the ankle, the arm, or the wrist, as well as neck, chest or other sites in the body. Applications and scenarios may include people with heart failure; people with cardiac myopathy; people with cardiac hypertrophy; athletes that have enlarged hearts, whether physiological or pathological; patients with ventricular assisted devices. In the case of the latter, typical patients are people with heart failure who are not able to have a heart transplant, and instead use ventricular assisted devices to improve blood flow; the use of Doppler system  10  enables the server software  26  to help assess circulation and assist in medical treatment or lifestyle treatment. 
     In an embodiment, server software  26  is configured to support analysis of cardiac arrhythmias. In one approach, medical centers have used Doppler evaluation of the pulmonary artery. However, it is difficult to evaluate pulmonary artery function in terms of elasticity and velocity, and what effects it is having during arrhythmias or atrial fibrillation, using Doppler because the lungs lie between the exterior sensor and the pulmonary artery, and therefore the air contained in the lungs has to be taken into account in evaluating the Doppler signals or signature. The use of peripheral sites such as the wrist, arm, or ankles will be more accurate, and has fewer challenges for interpretation of the resulting data. Further, as data is accumulated, the data can be used to see changes before arrhythmias occur, and thus the physician will have the opportunity to initiate intervention before the onset of arrhythmia. Moreover, the physician may be able to perform further analysis based on data from Doppler system  10  to modify treatment after the arrhythmia. That information will help to monitor hemodynamics even while an arrhythmia is occurring. 
     In an embodiment, server software  26  is configured to support analysis for sports medicine using biomarkers and biosensors and waveform analysis to provide recommendations and provide performance status of athletes. 
     In an embodiment, server software  26  is configured to use waveform analysis based on input from Doppler system  10  to form and report associations with changes in electrocardiography (EKG) data. With time, changes in waveforms seen via data from Doppler system  10  may show a correlation with wave changes that occur on the EKG/ECG, specifically the P wave, T wave and QRS complex, and the changes on voltages. Changes in EKG/ECG waveforms are important in assessing cardiac function, and the use of Doppler in the periphery will add to the understanding of those EKG changes over time. 
     In an embodiment, server software  26  is configured to assess changes in physiology that occur during conditions of athletic stress. For example, deaths continue to occur on the basketball court and playing fields in other sports, at all levels. Analysis of data from Doppler system  10  may be used to detect or assess vagal stimulation or early repolarization changes, which are usually noted through EKG data; the Doppler system  10  may also provide assessing information when an EKG may not be feasible. 
     In an embodiment, server software  26  is configured to detect and generate reports or assessments about cardiac irregularities such as unusual rhythms, extra beats or premature ventricular contractions. In an embodiment, server software  26  is configured to use a peripheral bi-directional Doppler analysis based on data from Doppler system  10  to assess hemodynamics. 
     To be clear, the hypertrophic heart or enlarged heart is a major health concern when detected, especially for athletes. EKG changes may be used as a means of detection, but past approaches have not used peripheral vascular correlation to try to understand when this diagnosis or condition needs to be better addressed and treated differently or more aggressively. 
     In an embodiment, server software  26  is configured to provide assessments in support of genetic testing for hypertrophy problems. The application of a vascular study on a daily basis can help answer questions of EKG changes during physiological or pathological states of hypertrophy. 
       FIG. 5  illustrates data flows in example processes of performing a global assessment of health with correlations of various data sources and sensors relating to vascular systems. 
     Referring to  FIG. 5 , a process of determining a global assessment of health using the devices, sensors and data sources described herein may have one or more elements of internal influence and external influence  506 . Influence  506 , internal is equivalent to biological sensors such as vital signs, oxygenation, glucose, nitric oxide, etc. Influence  506 , external reflects environmental factors such as running a race, exertion, anxiety, stress, or occupational exposure such as that seen in firefighters. 
     These influences lead to physiological changes  505 ,  507 , which may be positive or negative depending on the influence  506 . 
     A response  504 ,  508  is a biological result of the changes  505 ,  507  and may be Immediate or Delayed. For example the nervous system is structured for Immediate response  504 ,  508  to changes  505 ,  507  to cause increase in oxygenation or another biological effect. An example of a Delayed response  504 ,  508  is the release of hormones and their effects. An example of Immediate response  504 ,  508  is production of nitric oxide as a result of exercise. An example of Delayed response  504 ,  508  is from the immune system. 
     Three waveforms  500  typically are possible and degrees of the waveforms are observed. Vascular measurement involves determining whether one, two or three waveforms  500  are present. There could be intermediate phases or steps that occur as the body transitions from one waveform type to the next, so it may be unclear whether two or three waveforms  500  are represented. Velocity may have green (average to normal) range for the first waveform. Normal velocity for the 2 nd , 3 rd , 4 th  waveform is not known, as there is no known research on it. Width or space between waveforms  500  (or periodicity) indicates relative vascular health; as vascular health improves, waveforms  500  get wider. 
     The data leads to an interpretation  501  of Normal, Mild, Moderate or Severe plaque formation or occlusion of the cardiovascular arteries. 
     Various embodiments allow more precision as to the degrees of these four categories, degrees of Moderate for example. Various embodiments are configured to measure degrees of velocity not just of the 1 st  waveform but all the waveforms  500  and the widths. 
     Interpretation  501  leads to an action plan  502  which may take the form as disclosed in the preceding sections of recommendations, reports and/or protocols. 
     Units of measurement from other tests  503  in various embodiments from blood pressure, EKG, spirometry, heart rate yield data over time associated with changes  505 ,  507  and responses  504 ,  508  and how the measured values relate to the vascular measurements. Patterns can be deduced and associated with the individual&#39;s vascular response. 
     Hardware Overview 
     According to one embodiment, the techniques described herein are implemented by one or more special-purpose computing devices. The special-purpose computing devices may be hard-wired to perform the techniques, or may include digital electronic devices such as one or more application-specific integrated circuits (ASICs) or field programmable gate arrays (FPGAs) that are persistently programmed to perform the techniques, or may include one or more general purpose hardware processors programmed to perform the techniques pursuant to program instructions in firmware, memory, other storage, or a combination. Such special-purpose computing devices may also combine custom hard-wired logic, ASICs, or FPGAs with custom programming to accomplish the techniques. The special-purpose computing devices may be desktop computer systems, portable computer systems, handheld devices, networking devices or any other device that incorporates hard-wired and/or program logic to implement the techniques. 
     For example,  FIG. 1  is a block diagram that illustrates a computer system  100  upon which an embodiment of the invention may be implemented. 
     Computer system  100  includes a bus  102  or other communication mechanism for communicating information, and a hardware processor  104  coupled with bus  102  for processing information. Hardware processor  104  may be, for example, a general purpose microprocessor. 
     Computer system  100  also includes a main memory  106 , such as a random access memory (RAM) or other dynamic storage device, coupled to bus  102  for storing information and instructions to be executed by processor  104 . Main memory  106  also may be used for storing temporary variables or other intermediate information during execution of instructions to be executed by processor  104 . Such instructions, when stored in non-transitory storage media accessible to processor  104 , render computer system  100  into a special-purpose machine that is customized to perform the operations specified in the instructions. 
     Computer system  100  further includes a read only memory (ROM)  108  or other static storage device coupled to bus  102  for storing static information and instructions for processor  104 . A storage device  110 , such as a magnetic disk or optical disk, is provided and coupled to bus  102  for storing information and instructions. 
     Computer system  100  may be coupled via bus  102  to a display  112 , such as a cathode ray tube (CRT), for displaying information to a computer user. An input device  114 , including alphanumeric and other keys, is coupled to bus  102  for communicating information and command selections to processor  104 . Another type of user input device is cursor control  116 , such as a mouse, a trackball, or cursor direction keys for communicating direction information and command selections to processor  104  and for controlling cursor movement on display  112 . This input device typically has two degrees of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allows the device to specify positions in a plane. 
     Computer system  100  may implement the techniques described herein using customized hard-wired logic, one or more ASICs or FPGAs, firmware and/or program logic which in combination with the computer system causes or programs computer system  100  to be a special-purpose machine. According to one embodiment, the techniques herein are performed by computer system  100  in response to processor  104  executing one or more sequences of one or more instructions contained in main memory  106 . Such instructions may be read into main memory  106  from another storage medium, such as storage device  110 . Execution of the sequences of instructions contained in main memory  106  causes processor  104  to perform the process steps described herein. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions. 
     The term “storage media” as used herein refers to any non-transitory media that store data and/or instructions that cause a machine to operation in a specific fashion. Such storage media may comprise non-volatile media and/or volatile media. Non-volatile media includes, for example, optical or magnetic disks, such as storage device  110 . Volatile media includes dynamic memory, such as main memory  106 . Common forms of storage media include, for example, a floppy disk, a flexible disk, hard disk, solid state drive, magnetic tape, or any other magnetic data storage medium, a CD-ROM, any other optical data storage medium, any physical medium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM, NVRAM, any other memory chip or cartridge. 
     Storage media is distinct from but may be used in conjunction with transmission media. Transmission media participates in transferring information between storage media. For example, transmission media includes coaxial cables, copper wire and fiber optics, including the wires that comprise bus  102 . Transmission media can also take the form of acoustic or light waves, such as those generated during radio-wave and infra-red data communications. 
     Various forms of media may be involved in carrying one or more sequences of one or more instructions to processor  104  for execution. For example, the instructions may initially be carried on a magnetic disk or solid state drive of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a telephone line using a modem. A modem local to computer system  100  can receive the data on the telephone line and use an infra-red transmitter to convert the data to an infra-red signal. An infra-red detector can receive the data carried in the infra-red signal and appropriate circuitry can place the data on bus  102 . Bus  102  carries the data to main memory  106 , from which processor  104  retrieves and executes the instructions. The instructions received by main memory  106  may optionally be stored on storage device  110  either before or after execution by processor  104 . 
     Computer system  100  also includes a communication interface  118  coupled to bus  102 . Communication interface  118  provides a two-way data communication coupling to a network link  120  that is connected to a local network  122 . For example, communication interface  118  may be an integrated services digital network (ISDN) card, cable modem, satellite modem, or a modem to provide a data communication connection to a corresponding type of telephone line. As another example, communication interface  118  may be a local area network (LAN) card to provide a data communication connection to a compatible LAN. Wireless links may also be implemented. In any such implementation, communication interface  118  sends and receives electrical, electromagnetic or optical signals that carry digital data streams representing various types of information. 
     Network link  120  typically provides data communication through one or more networks to other data devices. For example, network link  120  may provide a connection through local network  122  to a host computer  124  or to data equipment operated by an Internet Service Provider (ISP)  126 . ISP  126  in turn provides data communication services through the world wide packet data communication network now commonly referred to as the “Internet”  128 . Local network  122  and Internet  128  both use electrical, electromagnetic or optical signals that carry digital data streams. The signals through the various networks and the signals on network link  120  and through communication interface  118 , which carry the digital data to and from computer system  100 , are example forms of transmission media. 
     Computer system  100  can send messages and receive data, including program code, through the network(s), network link  120  and communication interface  118 . In the Internet example, a server  130  might transmit a requested code for an application program through Internet  128 , ISP  126 , local network  122  and communication interface  118 . 
     The received code may be executed by processor  104  as it is received, and/or stored in storage device  110 , or other non-volatile storage for later execution. 
     In the foregoing specification, embodiments of the invention have been described with reference to numerous specific details that may vary from implementation to implementation. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense. The sole and exclusive indicator of the scope of the invention, and what is intended by the applicants to be the scope of the invention, is the literal and equivalent scope of the set of claims that issue from this application, in the specific form in which such claims issue, including any subsequent correction.