Abstract:
The invention provides a monitoring device that features: 1) a cardiac sensor component with at least one light-emitting diode and a photodetector; 2) a pedometer component with at least one motion-sensing component (e.g., an accelerometer); and 3) a wireless component with a wireless interface that communicates with an external weight scale. The device also features a microprocessor in electrical communication with the cardiac sensor, pedometer, and wireless components and configured to analyze: 1) a signal from the cardiac sensor component to generate heart rate information; 2) a signal from the pedometer component to generate exercise information; 3) heart rate and exercise information to generate calorie information; and 4) a signal from the external weight scale to calculate weight information (e.g., weight and percent body fat).

Description:
CROSS REFERENCES TO RELATED APPLICATION  
       [0001]     This application claims the benefit of U.S. Provisional Application Ser. No. 60/721,665 filed on Sep. 29, 2005 and is hereby incorporated by reference. 
     
    
     BACKGROUND OF THE INVENTION  
       [0002]     1. Field of the Invention  
         [0003]     The present invention relates to medical devices for monitoring information, such as heart rate and calories burned, from a subject.  
         [0004]     2. Description of the Related Art  
         [0005]     Pedometers are common devices that typically include a motion-sensitive component, such as an accelerometer or a tilt switch, that typically generates an analog voltage that peaks in response to motion (e.g., steps). A microcontroller can receive the analog voltage, digitize it, and then process it by counting the peaks to determine a subject&#39;s steps. Heart rate monitors are also common devices that measure a subject&#39;s heart rate, typically by measuring a biometric signal (i.e., by processing an electrical signal collected by an electrode, such as that used in an ECG) or an optical plethysmograph (i.e., by processing an optical signal collected by a pulse oximeter).  
         [0006]     Pulse oximeters are typically worn on a patient&#39;s finger or ear lobe, and feature a processing module that analyzes data generated by an optical module. The optical module typically includes first and second light sources (e.g., light-emitting diodes, or LEDs) that transmit optical radiation at, respectively, red (λ˜630-670 nm) and infrared (λ˜800-1200nm) wavelengths. The optical module also features a photodetector that detects radiation transmitted or reflected by an underlying artery. Typically the red and infrared LEDs sequentially emit radiation that is partially absorbed by blood flowing in the artery. The photodetector is synchronized with the LEDs to detect transmitted or reflected radiation. In response, the photodetector generates a separate radiation-induced signal for each wavelength. The signal, called a plethysmograph, is an optical waveform that varies in a time-dependent manner as each heartbeat varies the volume of arterial blood, and hence the amount of transmitted or reflected radiation. A microprocessor in the pulse oximeter processes the relative absorption of red and infrared radiation to determine the oxygen saturation in the patient&#39;s blood. A number between 94%-100% is considered normal, while a value below 85% typically indicates the patient requires hospitalization.  
       SUMMARY OF THE INVENTION  
       [0007]     In one aspect the invention provides a monitoring device that features: 1) a cardiac sensor component with at least one LED and a photodetector; 2) a pedometer component with at least one motion-sensing component (e.g., an accelerometer); and 3) a wireless component with a wireless interface that communicates with an external weight scale. The device also features a microprocessor in electrical communication with the cardiac sensor, pedometer, and wireless components and configured to analyze: 1) a signal from the cardiac sensor component to generate heart rate information; 2) a signal from the pedometer component to generate exercise information; 3) heart rate and exercise information to generate calorie information; and 4) a signal from the external weight scale to calculate weight information (e.g., weight and percent body fat). The monitoring device also includes a transmitting component (e.g. a serial port or wireless interface) that transmits the heart rate, exercise, calorie, and weight information to an external device, such as a personal computer connected to the Internet.  
         [0008]     In embodiments, the microprocessor is configured to operate a computer algorithm that processes the heart rate and exercise information to generate calorie information, such as calories burned. For example, the algorithm can process the physical activity information to determine whether a subject is at rest or undergoing exercise, and once this is determined compare the heart rate information to pre-determined calibration information to determine an amount of calories burned by the subject. More specifically, the calibration information can include a predetermined data table or mathematical function that correlates oxygen consumed as a function of heart rate. The algorithm can then calculate caloric expenditure from the amount of oxygen consumed.  
         [0009]     The invention has many advantages, particularly in providing a small-scale, low-cost device that rapidly measures health-related indicators such as blood pressure, heart rate, and blood oxygen content. In embodiments, the device makes blood pressure measurements without using a cuff in a matter of seconds, meaning patients can easily monitoring device this property with minimal discomfort. In this way the monitoring device combines all the benefits of conventional blood-pressure measuring devices without any of the obvious drawbacks (e.g., restrictive, uncomfortable cuffs). Its measurement, made with an optical ‘pad sensor’, is basically unobtrusive to the patient, and thus alleviates conditions, such as a poorly fitting cuff, that can erroneously affect a blood-pressure measurement. Ultimately this allows patients to measure their vital signs throughout the day (e.g., while at work), thereby generating a complete set of information, rather than just a single, isolated measurement. Physicians can use this information to diagnose a wide variety of conditions, particularly hypertension and its many related diseases.  
         [0010]     The device additionally includes a simple wired or wireless interface that sends vital-sign information to a personal computer. For example, the device can include a Universal Serial Bus (USB) connector that connects to the computer&#39;s back panel. Once a measurement is made, the device stores it on an on-board memory and then sends the information through the USB port to a software program running on the computer. Alternatively, the device can include a short-range radio interface (based on, e.g., Bluetooth™ or 802.15.4) that wirelessly sends the information to a matched short-range radio within the computer. The software program running on the computer then analyzes the information to generate statistics on a patient&#39;s vital signs (e.g., average values, standard deviation, beat-to-beat variations) that are not available with conventional devices that make only isolated measurements. The computer can then send the information through a wired or wireless connection to a central computer system connected to the Internet.  
         [0011]     The central computer system can further analyze the information, e.g. display it on an Internet-accessible website. This means medical professionals can characterize a patient&#39;s real-time vital signs during their day-to-day activities, rather than rely on an isolated measurement during a medical check-up. The website typically features one or more web pages that display the blood test, vital sign, exercise, and personal information. In embodiments, the website includes a first web interface that displays information for a single patient, and a second web interface that displays information for a group of patients. For example, a medical professional (e.g. a physician, nurse, nurse practitioner, dietician, or clinical educator) associated with a group of patients could use the second web interface to drive compliance for a disease-management program. Both web interfaces typically include multiple web pages that, in turn, feature both static and dynamic content, described in detail below.  
         [0012]     The website can also include a messaging engine that processes real-time information collected from the device to, among other things, help a patient comply with a disease-management program, such as a personalized cardiovascular risk reduction program. The messaging engine analyses blood test, vital sign, exercise, and personal information, taken alone or combined, to generate personalized, patient-specific messages. Ultimately the Internet-based system, monitoring device, and messaging engine combine to form an interconnected, easy-to-use tool that can engage the patient in a disease-management program, encourage follow-on medical appointments, and build patient compliance. These factors, in turn, can help the patient lower their risk for certain medical conditions.  
         [0013]     These and other advantages of the invention will be apparent from the following detailed description and from the claims. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0014]      FIG. 1A  is a semi-schematic view of a portable, small-scale monitoring device that measures blood pressure, pulse oximetry, heart rate, glucose levels, weight, steps traveled, and calories burned;  
         [0015]      FIG. 1B  is a semi-schematic view of the monitoring device of  FIG. 1A  worn on a patient&#39;s belt;  
         [0016]      FIG. 2  is a schematic view of an Internet-based system that receives information from the monitoring device of  FIGS. 1A and 1B  through a wired connection;  
         [0017]      FIG. 3  is a schematic diagram of the electrical components of the monitoring devices of  FIGS. 1A and 1B ;  
         [0018]      FIG. 4   a  is a flow chart describing a first algorithm used by the monitoring devices of  FIGS. 1A and 1B  to calculate calories burned;  
         [0019]      FIG. 4   b  is a flow chart describing a second algorithm used by the monitoring devices of  FIGS. 1A and 1B  to calculate calories burned; and  
         [0020]      FIG. 5  is a flow chart describing a second algorithm used by the monitoring devices of  FIGS. 1A and 1B  to calculate calories burned. 
     
    
     DETAILED DESCRIPTION OF THE INVENTION  
       [0021]      FIGS. 1A and 1B  show a portable, small-scale monitoring device  5  that measures information such as blood pressure, pulse oximetry, heart rate, glucose levels, calories burned and steps traveled from a patient  1 . The monitoring device  5 , typically worn on the patient&#39;s belt  13 , features: i) an integrated, optical ‘pad sensor’  6  that cufflessly measures blood pressure, pulse oximetry, and heart rate from a patient&#39;s finger as described in more detail below; and ii) an integrated pedometer circuit  9  that measures steps and, using one or more algorithms, calories burned. To receive information from external devices, the monitoring device  5  also includes: i) a serial connector  3  that connects and downloads information from an external glucometer  22 ; and ii) a short-range wireless transceiver  7  that receives information such as body weight and percentage of body fat from an external scale  21 . The patient views information from a liquid crystal display (LCD) display  4  mounted on the monitoring device  5 , and can interact with the monitoring device  5  (e.g., reset or reprogram it) using a series of buttons  8   a ,  8   b.    
         [0022]     The monitoring device can be used for a variety of applications relating to, e.g., disease management, health maintenance, and medical diagnosis.  
         [0023]      FIG. 2  shows a preferred embodiment of an Internet-based system  36  that operates in concert with the small-scale monitoring device  5  to send information from the patient  11  to an Internet-accessible website  33 . There, a user can access the information using a conventional web browser through a patient interface  15  or a physician interface  34 . Typically the patient interface  15  shows information from a single user, whereas the physician interface  34  displays information for multiple patients. In both cases, information flows from the monitoring device  5  through a USB cable  10  to an external device, e.g., a personal computer  30 . The personal computer  30  connects to the Internet  31  through a wired gateway software system  32 , such as an Internet Service Provider.  
         [0024]     In other embodiments, the small-scale monitoring device  5  transmits patient information using a short-range wireless transceiver  7  through a short-range wireless connection  37  (e.g., Bluetooth™, 802.15.4, part-15) to the personal computer  30 . For example, the small-scale monitoring device  5  can transmit to a matched transceiver  12  within (or connected to) the personal computer  30 .  
         [0025]     During typical operation, the patient  11  uses the monitoring device  5  for a period of time ranging from a 1-3 months. Typically the patient  11  takes measurements a few times throughout the day, and then uploads the information to the Internet-based system  36  using a wired connection. Alternatively, the monitoring device  5  can measure the patient  11  continuously during periods of exercise. To view patient information sent from the monitoring device  5 , the patient  11  (or other user) accesses the appropriate user interface hosted on the website  33  through the Internet  31 .  
         [0026]      FIG. 3  shows a preferred embodiment of the electronic components within the monitoring device  5 . A data-processing circuit  61  controls: i) a pulse oximetry circuit  63  connected to an optical pad sensor  6 ; ii) LCD  4 ; iii) a glucometer interface circuit  64  that connects to an external glucometer through a mini USB port  3 ; iv) an integrated pedometer circuit  9  featuring an accelerometer  59 ; and v) a short-range wireless transceiver  7 . During operation, the optical pad sensor  6  generates an optical waveform that the data-processing circuit  61  processes to measure blood pressure, pulse oximetry, and heart rate as described in more detail below. The sensor  6  combines a photodiode  66 , color filter  68 , and light source/amplifier  67  on a single silicon-based chip. The light source/amplifier  67  typically includes light-emitting diodes that generate both red (λ˜600 nm) and infrared (λ˜940 nm) radiation. As the heart pumps blood through the patient&#39;s finger, blood cells absorb and transmit varying amounts of the red and infrared radiation depending on how much oxygen binds to the cells′ hemoglobin. The photodiode  66  detects transmission at both red and infrared wavelengths, and in response generates a radiation-induced current that travels through the sensor  6  to the pulse-oximetry circuit  63 . The pulse-oximetry circuit  63  connects to an analog-to-digital signal converter  62 , which converts the radiation-induced current into a time-dependent optical waveform. The analog-to-digital signal converter  62  sends the optical waveform to the data-processing circuit  61  that processes it to determine blood pressure, pulse-oximetry, and heart rate, which are then displayed on the LCD  4 . Once information is collected, the monitoring device  5  can send it through a mini USB port  2  to a personal computer  30  as described with reference to  FIG. 2 .  
         [0027]     In other embodiments, the monitoring device  5  connects through the mini USB port  3  and glucometer interface circuit  64  to an external glucometer to download blood-glucose levels. The monitoring device  5  also processes information from an integrated pedometer circuit  9  to measure steps and amount of calories burned, as described below.  
         [0028]     The monitoring device  5  includes a short-range wireless transceiver  7  that sends information through an antenna  67  to a matched transceiver embedded in an external device, e.g. a personal computer. The short-range wireless transceiver  7  can also receive information, such as weight and body-fat percentage, from an external scale. A battery  51  powers all the electrical components within the small-scale monitoring device  5 , and is preferably a metal hydride battery (generating 3-7V) that can be recharged through a battery-recharge interface  2 . The battery-recharge interface  52  can receive power through a serial port, e.g. a computer&#39;s USB port. Buttons control functions within the monitoring device such as an on/off switch  8   a  and a system reset  8   b.    
         [0029]      FIG. 4   a  shows a flow chart describing an algorithm  100  used by the monitoring device of  FIGS. 1A and 1B  to calculate an amount of calories burned during active and inactive periods. Parameters used in this calculation are defined in Table 1, below.  
                         TABLE 1                       Parameter Definitions                                PA -   physical activity level measured with accelerometer           (counts/minute)       PAI -   physical activity (kJ/kg/minute)         PA  -   PA threshold; median PA measured on treadmill or with           calibration (counts/minute)       PA flex  -   physical activity flex point; 50% of mean PA           (counts/minute)       HR -   heart rate measured with heart rate monitor           (beats/minute)         HR  -   HR threshold; mean of highest HR at rest and lowest HR           while walking (beats/minute)       VO 2  -   oxygen consumption (liters/minute)       EE -   acute energy expenditure (kcal/minute)       DEE -   direct energy expenditure (kcal)       TEE -   total energy expenditure (kcal)       REE -   resting energy expenditure (kcal/day)       PAEE -   physical activity energy expenditure (kJ/kg/minute)       ACC -   accelerometer output (counts/min)       DIT -   dietary induced thermogenesis (kJ)       FFM -   fat free mass (kg)       EI -   energy intake (kJ)       BM -   body mass (kg)       H -   height (m)       Age -   age (years)       WM -   minutes awake each day (minutes/day)       SM -   minutes sleeping each day (minutes/day)       RT -   recording time (the number of minutes the device is on)                    
 The algorithm  100 , which uses a patient&#39;s physical activity (PA) level and heart rate (HR), is based on a methodology developed by Moon and Butte (Moon J K and Butte N F; Combined heart rate and activity levels improve estimates of oxygen consumption and carbon dioxide production rates; J appl Physiol 81: 1754-1761, 1996), the contents of which are incorporated herein by reference. 
 
         [0030]     As a first step  101 , the algorithm  99  features a process that calibrates the monitoring device so that it can accurately measure calories burned during exercise. During the first step  101  VO 2  and HR are simultaneously measured during simulated, representative ‘active’ and ‘inactive’ periods, defined below. For example, VO 2  can be measured using indirect calorimetry while HR is measured using any number of techniques (e.g., ECG). VO 2  is then plotted as a function of HR for both the active and inactive periods. The resultant data are then fit with either a quadratic equation (for the inactive periods) or a linear equation (for the active periods), show below, to yield calibration parameters a, b, c, d. These calibration parameters will be most accurate if they are measured from a population that is representative to patients actually using the device. 
        inactive     VO 2 =a+b*(HR) 3       active     VO 2 =c+d*(HR)        
 
         [0035]     Typically the calibration process lasts a few hours and data describing VO 2  and HR are collected every minute. Active and inactive periods for the calibration process typically include the following: 
        inactive     1. 30 minutes of supine rest     2. 15 minutes of standing rest     active     1. 36 minutes of simulated daily activities 
            a. level walking at 2 mph for 6 minutes     b. level walking at 4 mph for 6 minutes     c. level jogging at 6 mph for 6 minutes     d. gardening or lawn care (mowing, raking, shoveling) for 6 minutes     e. household chores (vacuuming, sweeping and stacking groceries) for 6 minutes 
 
 Once calibrated, the algorithm  99  includes a second step  102  that determines threshold values for both PA (defined as PA) and HR (defined as HR). PA is typically the median value of PA determined while the patient is on the treadmill during the first step  101 . HR is typically the mean of highest HR measured at rest and the lowest measured HR during walking. Using the threshold values, the algorithm  99  includes a third step  106  that measures data from the subject to define periods as being either ‘active’ or ‘inactive’. For example, the subject is determined to be in an inactive state if PA&lt;PA for one or more minutes, or alternatively if HR&lt;HR. Alternatively, the subject is determined to be in an active state if PA≧PA for at least one minute and if HR&gt;HR. Using the calibration parameters a, b, c, d determined from calibration during the first step  101 , and the subject&#39;s active or passive state determined during the third step  106 , the algorithm then calculates the subject&#39;s oxygen consumed (VO 2 ) during a fourth step  108 . Specifically, the algorithm records HR during active or inactive periods, and then using the calibration parameters calculates VO 2  using either the above-mentioned quadratic equation (for an inactive period) or linear equation (for an active period). During a fifth step  110  the algorithm  100  converts VO 2  to acute energy expenditure (EE) for both active and inactive periods using the equation: 
 
 EE   active/inactive =4.88 *VO 2, active/inactive  
 
 During a sixth step  112  the algorithm converts EE (with units of kcal/minute) to total energy expenditure (TEE) using the total amount of time of either the active or inactive period. The time is typically measured in one-minute increments with a real-time clock within the monitoring device: 
 
 TEE=EE   active *time active   +EE   inactive *time inactive  
 
 The sixth step  110  yields the amount of calories burned by the subject. 
   
               
 
         [0046]      FIG. 4   b  shows an alternate embodiment of the algorithm  99  shown in  FIG. 4   a  used to calculate PAEE. The figure shows a flow chart illustrating an algorithm  100  that features a first step  113  where a parameter related to accelerometer output called ACC flex is determined from ACC (in counts/minute). During a second step  114  the algorithm calibrates VO 2  vs. ACC and VO 2  vs. HR relationships to determine the calibration coefficients a, b, c, d, e. As with  FIG. 4   a , these calibration parameters will be most accurate if they are measured from a population that is representative to patients actually using the device. During a third step  115 , after the calibration parameters are determined, the algorithm  100  defines branched equation model coefficients x, Y 1 , Y 2 , Z 1 , Z 2 , P 1-4  based on minimizing standard error of PAI estimate. During a fourth step  116  the algorithm calculates PAI using a series of branched equations  117 ,  118 , using the coefficients from the third step  115 . This leads to a fifth step  118  wherein the algorithm converts PAI (with units of kJ/kg/min) to PAEE (kcal/min).  
         [0047]     The branched equations are defined in more detail in the following reference, the contents of which are incorporated herein by reference: Brage S, Brage N, Franks P W, Ekelund U, Wong M, Andersen L B, Froberg K, and Wareham N J; Branched equation modeling of simultaneous accelerometry and heart rate monitoring improves estimate of directly measured physical activity energy expenditure;  J appl Physiol  96: 343-351, 2004. The branched equations process values of HR and PA by comparing them with benchmark values, and in response assign percentages that define the relative contribution of these parameters to PAEE. These percentages will vary depending on the group used for the calibration process, and ultimately determine the total value for PAEE.  
         [0048]      FIG. 5  shows a flow chart illustrating a second algorithm  120  used within the device to calculate the amount of calories a subject burns during both active and inactive periods. The algorithm  120  can use one of three possible steps  122 ,  124 ,  126  to calculate REE. For example, during a first step  122  REE is measured directly by first using a calibration step that determines HR and VO 2  during rest; this method is similar to that used for the first step  101  for the algorithm  100  described with reference to  FIG. 4 . VO 2  can be measured as described in steps  1 - 4  of the algorithm  100 , and REE is calculated with the following equations: 
   K cal/min→VO 2 *(3.941+1.106* RQ )         for normal and obese populations 
 
 REE= ( K cal/min)* WM+ 0.95*( K cal/min)* SM  
    for post-obese populations 
 
 REE= ( K cal/min)* WM+ 0.85*( K cal/min)* SM  
 
 Using an alternate first step  124  REE is determined using simple equation that takes into account the patient&#39;s fat-free mass (FFM): 
 
 REE= 21.7* FFM+ 374 
 
 In this case, FFM is the patient&#39;s mass not attributed to fat, and is typically measured directly or calculated from a patient&#39;s body-mass index. 
         
         [0051]     In another alternative first step  126  estimates REE using the Harris-Benedict equation: 
        for men 
 
 REE= 13.75* BM+ 500.3* H− 6.78*Age+66.5 
    for women 
 
 REE= 9.56* BM+ 185* H− 4.68*Age+665.1 
       
 
         [0054]     In yet another alternate first step  127 , REE calculated as described above is modified using recording time (RT), i.e.: 
 
 REE′=REE *(1440 −RT) 
 
         [0055]     Once REE is determined, the algorithm  120  uses a second step  128  to estimate DIT using TEE and the equation: 
 
DIT=0.1*TEE 
 
         [0056]     Alternatively, DIT is calculated by estimating the macronutrient composition of the subject&#39;s diet. This is done using the following equation for the second step  130  of the algorithm  120 : 
 
 DIT= 0.025*fat El − 0.07*carbohydrate El+ 0.275*protein El  
 
 During a third step  132  the algorithm uses TEE (described above with reference to  FIG. 4   a ) or PAEE (described above with reference to  FIG. 4   b ). For example, in one part of the third step  133 , TEE is determined as described above, and then combined with the first and second steps to determine DEE  142   a . In an alternate step  134 , PAEE is determined using calibration information that describes the relationship between both PA and HR and VO 2  as described above. Once REE (step  1 ), DIT (step  2 ), PAEE (step  3 ) or TEE (step  3 ) are determined, the algorithm  120  uses a fourth step  142   a,b  to determine DEE: 
 
 DEE=REE+DIT+PAEE  
 
or 
 
 DEE=REE+DIT+TEE  
 
         [0057]     Methods for processing optical and electrical waveforms to determine blood pressure without using a cuff are described in the following co-pending patent applications, the entire contents of which are incorporated by reference: 1) CUFFLESS BLOOD-PRESSURE MONITORING DEVICE AND ACCOMPANYING WIRELESS, INTERNET-BASED SYSTEM (U.S. Ser. No 10/709,015; filed Apr. 7, 2004); 2) CUFFLESS SYSTEM FOR MEASURING BLOOD PRESSURE (U.S. Ser. No. 10/709,014; filed Apr. 7, 2004); 3) CUFFLESS BLOOD PRESSURE MONITORING DEVICE AND ACCOMPANYING WEB SERVICES INTERFACE (U.S. Ser. No. 10/810,237; filed Mar. 26, 2004); 4) VITAL-SIGN MONITORING DEVICE FOR ATHLETIC APPLICATIONS (U.S. Ser. No.; filed Sep. 13, 2004); 5) CUFFLESS BLOOD PRESSURE MONITORING DEVICE AND ACCOMPANYING WIRELESS MOBILE DEVICE (U.S. Ser. No. 10/967,511; filed Oct. 18, 2004); and 6) BLOOD PRESSURE MONITORING DEVICEING DEVICE FEATURING A CALIBRATION-BASED ANALYSIS (U.S. Ser. No. 10/967,610; filed Oct. 18, 2004); 7) PERSONAL COMPUTER-BASED VITAL SIGN MONITORING DEVICE (U.S. Ser. No. 10/906,342; filed Feb. 15, 2005); and 8) PATCH SENSOR FOR MEASURING BLOOD PRESSURE WITHOUT A CUFF (U.S. Ser. No. 10/906,315; filed Feb. 14, 2005).  
         [0058]     Still other embodiments are within the scope of the following claims.