Abstract:
A thermometer includes a processing unit configured to receive a plurality of timed apart temperature readings from first and second sensors and a processor calculates heat flux value, Q, and obtains values of the heat flux vs. temperature (Q vs. Ts.) as the temperature approaches a steady state. The processor empirically predicts the steady state temperature of the sensor Ts, using the peak value of the values of Q vs. Ts. 
     The processor may also empirically calculate a bias value as a function of the peak value of Q vs. Ts. The bias value represents the difference between the temperature reading (Ts) at steady state and core temperature of the subject and is added to the steady state temperature to arrive at core. The thermometer probe may include one or more additional sensors for obtaining physiological readings from the subject other than temperature and the processing unit is configured to use empirical formulas to calculate the bias value using the physiological readings which may include blood perfusion, pulse rate and the bio-impedance of the subject.

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
       [0001]    This application claims the priority of U.S. Provisional Application 61/912,201 filed Dec. 5, 2013, the entire disclosure of which is incorporated herein by reference. 
     
    
     BACKGROUND OF THE INVENTION 
       [0002]    The present invention relates to thermometry and more particularly to thermometers that are more accurate and faster acting. Thermometers may be classified as invasive, where the thermometer is placed in a body cavity such as the rectum, under arm or mouth or non-invasive where the thermometer does not enter the body cavity but at most, contact&#39;s the subject&#39;s skin. Non-invasive thermometers are growing in popularity both because of their ease of use and gentleness to the subject. A common type of non-invasive thermometer includes a probe with a heat conducting membrane designed to be placed against the skin of a subject&#39;s temple, behind the ear or other body surface. An early version of such a thermometer utilized a probe to obtain temperature readings at the measuring site and an algorithm to utilize parameters derived form the measured temperature to correct a fixed bias to a reasonable proximation and clinically accepted value of the subject&#39;s core temperature, that is the temperature of blood flowing in the pulmonary artery. An improvement on this thermometer is disclosed in U.S. Pat. No. 7,597,668 to Yarden wherein a deep tissue temperature, that is, the local temperature below the skin surface at the measuring site that is the source of heat to the probe is calculated utilizing parameters derived from the measured temperatures and an algorithm is utilized to correct the calculated deep tissue temperature to core. Non-invasive temperature measurement of a deep tissue is challenging. One can measure it with commonly acceptable accuracy using a well insulated contact temperature sensor attached to the external surface above the deep tissue. When the temperature sensor is reaching to its equilibrium, the temperature value at steady state is approaching to the deep tissue temperature value and is a good representation of it. However, in some thermometers, the steady state value of the temperature sensor can be calculated within a shorter time than required to reach equilibrium. This calculation is called prediction, i.e. the thermometer is predicting the steady state value of the sensor before it reaches to the steady state and might be determined using prediction algorithms such as described in U.S. Pat. No. 4,866,621 and U.S. Pat. No. 4,592,000. 
         [0003]    Once the local temperature (which is the steady state value of a surface temperature sensor) is determined, further algorithms are used to correct the local temperature to core. 
         [0004]    Other non-invasive thermometers utilize IR sensors to determine the surface temperature at a measuring site along with an algorithm to convert parameters derived from the measured surface temperatures to core temperature. That is, the local or steady state value of the skin temperature is measured and then corrected to reflect the core body temperature. Such a thermometer, for example, is disclosed in U.S. Pat. No. 6,292,685 to Pompei. 
         [0005]    An assumption in the algorithms of exiting non-invasive thermometers for converting parameters derived from temperature measurements at the measuring site to core temperature is that physiological factors other than the subject&#39;s temperature are the same or closely similar for all subjects, regardless of age, skin tone, weight, etc. That is, the assumption is that the relationship between the steady state temperature at the measuring site and a subject&#39;s core temperature is only thermal. However, it has been found that other physiological characteristics of the subject&#39;s anatomy come into play, such as the thermal conductivity, thermal impedance and blood perfusion of the subject&#39;s skin and tissue at the measuring site. 
         [0006]    In view of the above it is a principal object of the present invention to provide an improved thermometer capable of more accurately and/or more rapidly determine the steady state temperature at a measuring site. 
         [0007]    A further object is to provide such a thermometer that is able to rapidly calculate core temperature from the temperature and other non-temperature physiological parameters obtained preferably but not necessarily at the measuring site. 
       SUMMARY OF THE INVENTION 
       [0008]    The above and other beneficial objects and advantages are attained in accordance with the present invention by providing a thermometer comprising a probe having a surface for contacting a subject. The housing contains a first sensor proximal the contact surface and a second sensor spaced apart from the first sensor and distal said contact surface. The thermometer further includes a processing unit configured to receive a plurality of timed apart temperature readings from the first and second sensors to calculate a value of the difference between the temperature readings from the first sensor (Ts) and the second sensor (Tr) at each time interval. The difference being representative of the heat flux (Q) flowing from the subject to the probe while temperature readings are being taken. The processing unit uses the readings to determine the peak value of Q vs. Ts and empirically calculates a bias value as a function of Q and Ts at the peak. The bias value representing the difference between the temperature reading from the first sensor (Ts) when the first sensor will reach a steady state temperature and a core temperature of the subject. The bias value is added to the value of reading from the first sensor (Ts) when the first sensor will reach a steady state temperature to arrive at the subjects core temperature. In further embodiment of the present invention , the peak value of Q vs. Ts is used to predict the steady state value of the temperature sensor Ts. 
         [0009]    In addition to the temperature sensor, the probe may include one or more additional sensors for obtaining physiological readings from the subject other than temperature. The processing unit is configured to use empirical formulas to calculate the bias value using the physiological readings which may include blood perfusion, pulse rate and the bio-impedance of the subject. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0010]    In the accompanying drawings: 
           [0011]      FIG. 1A  is a representative view of a heat flux thermometer temperature probe; 
           [0012]      FIG. 1B  is a representative view of an alternative heat flux thermometer temperature probe; 
           [0013]      FIG. 1C  is a representative view of another alternative heat flux thermometer temperature probe; 
           [0014]      FIG. 1D  is a representative view of another alternative heat flux thermometer temperature probe; 
           [0015]      FIG. 2A  is a plot of heat flux vs. temperature for a first subject; 
           [0016]      FIG. 2B  is a plot of heat flux vs. temperature for a second subject; 
           [0017]      FIG. 3  is a plot of time constant vs. peak values of the Q vs. Ts curve for several subjects 
           [0018]      FIG. 4  is a representative view of a thermometer probe utilizing patient impedance; 
           [0019]      FIG. 5  depicts the circuit of the probe of  FIG. 4 ; 
           [0020]      FIG. 6  is a representative plot of PPG voltage values vs. time; 
           [0021]      FIG. 7  is a representative view of a thermometer probe utilizing blood perfusion; 
           [0022]      FIG. 8  is a representative view of a continuous monitoring thermometer; 
           [0023]      FIG. 9  is a representative view of a continuous monitoring thermometer utilizing bio-impedance; and 
           [0024]      FIG. 10  s a representative view of a continuous monitoring thermometer utilizing PPG. 
       
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
       [0025]    The probe  10  of a non-invasive thermometer such as that described in the aforementioned Yarden Pat. No. 7,597,668 is depicted in  FIG. 1A . The probe  10  comprises a housing  12  in which two sensors,  14  and  16  which respectively obtain temperatures Ts and Tr are located. The sensors may be thermistors, RTD&#39; s (Resistance Temperature Detectors) or the like (hereinafter collectively referred to as “thermistors”) which are separated by air or by an insulator  18 . Ts is obtained from sensor  14  proximate to a membrane  20  closing the tip of the probe and hence comes closer the subject&#39;s skin while Tr is the temperature obtained from sensor  16  remote from the membrane  20  and hence becomes further from the subject&#39;s skin when the thermometer is positioned on a subject&#39;s forehead or other location on the subject&#39;s skin. The output of the probe sensors is connected to a processing unit (not shown) which is configured to determine various parameters that are used to ultimately obtain and display a representation of the core temperature of the subject to which the thermometer is applied. The sensors  14  and  16  are lined up generally (but not necessarily) perpendicular to the patient&#39;s skin at the measuring site when the thermometer is used and hence the temperature difference Ts and Tr as measured by sensors  14  and  16  is proportional to the heat flux Q between the subject and the probe  10 . Alternative probe constructions are depicted in  FIGS. 1B-1D  where the sensors are offset from one another. 
         [0026]      FIGS. 2A and 2B  are curves plotting heat flux, Q vs. temperature Ts during the temperature rise time. As can be seen, the curve is a generally linear line with a peak followed by a curved drop of the line. The curves  2 A and  2 B are from two subjects whose local temperatures and core temperatures were independently determined. For curve  2 A the difference between the local temperature and core temperature (hereafter referred to as the “Bias”) was 3.25° C. while for the curve  2 B the Bias was 4.2° C. 
         [0027]    τ is a time constant determined by the conductivity of tissue divided by density and heat capacity.  FIG. 3  is a plot of peak values of the Q vs. Ts curve for various different subjects. Through testing it was found that the peak point has a correlation to the Bias for different subject and that subjects having skin with good conductivity and relatively low thermal resistance have a higher Q vs. Ts peak than subjects with skin with a relatively high thermal resistance. That is, the values on the right hand side of  FIG. 3  are higher than those on the left. The steady state value of Ts (i.e. at equilibrium) might be determined using prediction algorithms such as described in U.S. Pat. No. 4,866,621 and U.S. Pat. No. 4,592,000. 
         [0028]    From the above, an improved algorithm the processor utilizes for local to core correction includes the following steps: 
         [0029]    Record the temperatures Ts and Tr 
         [0030]    Calculate Q repeatedly for the temperatures Ts and Tr 
         [0031]    Calculate Ts at equilibrium (steady state) 
         [0032]    Determine the peak values of Ts and Q 
         [0033]    Calculate the Bias using an empirical formula Bias=F(Ts, Q) PEAK    
         [0034]    Since T core =Ts (at equilibrium)+Bias 
         [0035]    (1) T core =F(Ts (at equilibrium), (Ts, Q) PEAK ) where F is a function which can be expressed as an empirically derived polynomial or any power of its arguments to determine the core temperature. 
         [0036]    While the invention has been described above in relation to a conduction thermometer, it is also applicable to an IR thermometer in which case Ts at equilibrium would be replaced by Tskin, the local skin temperature as measured by the IR sensor so that the formula the processor utilizes for calculating T core  becomes 
         [0037]    T core =F((Tskin, (Tskin, Q) PEAK ) 
         [0038]    It has also been found through clinical testing that a correlation may be drawn between the Q-Ts peak and the steady state value of Ts for a conductive thermometer. Thus, the steady state value may be predicted relatively quickly by performing the following steps: 
         [0039]    1. Record the Ts and Tr temperatures from the proximal and distal sensors  14  and  16  over a relatively short time (on the order of a few seconds) in the case of a forehead or oral thermometer; 
         [0040]    2. Calculate Q; 
         [0041]    3. Determine the peak values of Ts and Q 
         [0042]    4. Find the peak point: Ts-peak, Q-peak 
         [0043]    5. Use an empirical formula derived from the clinical testing to calculate Ts (at equilibrium)=F(Ts, Q)|peak 
         [0044]    F being a function the processor utilizes derived empirically such as a polynomial with powers of Ts-peak and Q-peak raised to powers and empirically derived coefficients based on clinical testing. 
         [0045]    An implicit form of the formula (1), makes use of the fact that Ts at equilibrium can be predicted as a function of the peak value of Q vs. Ts, hence the prediction of Ts as well as the bias are calculated in one step using the formula: 
         [0046]    T core =F((Ts, Q) PEAK ) where F is a function which can be expressed as an empirically derived polynomial or any power of its arguments to determine the core temperature directly. 
         [0047]    In the case of a non-invasive conductive thermometer, local temperature is the deep tissue temperature, represented by the steady state temperature Ts, or the skin temperature in the case of an IR thermometer and core temperature, that is the Bias, as previously discussed 
         [0048]    The difference between the local and the core temperatures is related to the thermal properties of the subject at the measuring area. Thermal conductivity, in turn, may be correlated to electrical conductivity which, in turn, may be correlated to the subjects bio-impedance at the measuring site. Impedance has a DC component and an AC component. The latter being the resistance and the former being the frequency domain ratio of alternating current to voltage. That is, the total impedance Z may be determined by the following formula 
         [0000]      Z=R+iX 
         [0049]    Where R is the resistance, i=and iX is the frequency dependent component of the impedance. 
         [0050]    By applying an alternating voltage or current to the measuring site at different frequencies and measuring the voltage, the impedance may be determined. Typically the frequency for biological tissue impedance measurement ranges between 100 Hz and 100 K HZ. To avoid the possibility of the body of a subject exhibiting different compliance at different frequencies impedance measurement should be taken at different frequencies and the corresponding impedance should be used as an input of a multi-variable function to determine the Bias according to the formula 
         [0000]      Bias=F(a 1 *Z 1  . . . , an*Zn)
 
         [0051]    Where a 1  . . . , an are empirically derived parameters and Z 1  . . . , Zn are the measured tissue impedance values at the applied frequencies. An algorithm the processor utilizes for local to core temperature correction taking advantage of bio-impedance may thus include the following steps: 
         [0052]    1. Record the Ts and/or Tr from the sensors proximate and distal the measuring site; 
         [0053]    2. Calculate Ts (at equilibrium) using a prediction algorithm; 
         [0054]    3. Measure the tissue bio-impedance at the measuring site or in another suitable body site; 
         [0055]    4. Use the formula Bias=F(a 1 *Z 1  . . . , an*Zn) to calculate Bias 
         [0056]    5. Calculate Tcore using the formula T core =Ts (at equilibrium)+Bias 
         [0057]    Where ai . . . , an are empirically derived parameters and Z 1  . . . , Zn are the measured tissue impedance for n applied frequencies respectively. 
         [0058]    The steady state value of Ts (i.e. at equilibrium) might be determined using prediction algorithms such as described in U.S. Pat. No. 4,866,621 and U.S. Pat. No. 4,592,000. 
         [0059]    The Bias may be obtained based on the bio-impedance and the measured temperatures Ts and Tr using the function Bias=F(a 1 *Z 1  . . . , an*Zn, g 1  (Ts), g 2  (Tr)) where gi and g 2  are empirically derived functions of Ts and Tr and Tcore may be derived using the formula 
         [0000]      T core =Ts (at equilibrium)+Bias. 
         [0060]    Thus, Tcore may be derived using the formula 
         [0000]      T=Ts (at equilibrium), (a 1 *Z 1  . . . , an*Zn), g 1  (Ts), g 2  (Tr))
 
         [0061]    Where F, g 1 , g 2  are functions that can be a polynomial or any powers of their arguments which can be derived empirically from clinical testing. 
         [0062]      FIG. 4  depicts a thermometer probe  20  comprising a metal plate  22  on which a temperature sensor  24  and a two set of electrodes  26 ,  28  are mounted. As shown in  FIG. 5 , the electrodes  26 ,  28  apply a test signal in the form of a frequency-modulated current from the generator  30  across a section of tissue of the subject  32  which the meter  34  measures to obtain the tissues&#39; response to the applied current to obtain values from which the bio-impedance may be derived and applied as previously described. Whether the temperature sensor  24  is conductive or an IR sensor, the portion of the probe containing the electrodes  26 ,  28  must be in contact with the subject or in a separate sensor contacting the subject to obtain the bio-impedance. 
         [0063]    A factor that affects the temperature at the measuring site is the amount of blood flowing to the site or blood perfusion. The higher the blood perfusion the higher the local temperature and hence the lower the Bias. Thus, the Bias may be expressed as a function of perfusion, or 
         [0064]    Bias=F(B pf ) where B pf  is a parameter representing the blood perfusion rate. 
         [0065]    A measurement of the blood flow may be obtained using a photoplethysmogram (PPG) to obtain a signal representative of the blood flow in the tissue at the measuring site. The PPG signal may be divided into an AC and a DC component with the AC component being synchronous with heart beat and correlating directly to blood flow while the DC component establishes a baseline reflecting the total blood volume of the tissue at rest as shown in  FIG. 6  and Bpf may be derived from the AC and DC components. The Bias may be calculated based on blood perfusion and the measured temperatures Ts and Tr and the function for Bias calculation would take the form 
         [0066]    Bias=F(B pf ), h 1 (Ts), h 2 (Tr) 
         [0067]    Where hi and h 2  are empirically derived functions of Ts and Tr. 
         [0068]    A representative probe  40  for making use of blood perfusion in establishing a patient&#39;s temperature is depicted in  FIG. 7 . The probe  36  includes a base plate  38  to which at least one temperature sensor  40  is mounted along with an LED  42  and photo detector  44 . The LED  42  and photo detector  44  serve to obtain PPG measurement by measuring the portion of the light emitted by the LED that is absorbed by the tissue to obtain a voltage output as depicted in  FIG. 6 . The PPG probe may be a transmitter type probe where the LED and photo-detector are on opposite sides of the tissue to be measured as shown in  FIG. 7  or of the reflective type (not sown) where the LED and photodetector are on the same side of the tissue. 
         [0069]    As shown in  FIG. 6  the PPG graph is an indicator of pulse rate. There is a known correlation between pulse rate and temperature generally on the order of each degree C. of temperature increase causing an increase of approximately 10 beats per minute. Therefore better accuracy of a temperature reading may be obtained knowing the pulse rate and a Bias calculation taking into account the pulse rate would take the following form 
         [0070]    Bias=F(Pulse rate) 
         [0071]    Where F(Pulse rate) is an empirically derived formula the processor utilizes for correlating the predicted temperature of a subject to the subject&#39;s pulse rate. 
         [0072]    The calculation may also take into account blood perfusion so that the calculation would take the form 
         [0073]    Bias=F(Bpf, Pulse) 
         [0074]    So that the final core temperature calculation the processor utilizes would take the form 
         [0075]    T core =F(Ts (at equilibrium), Bpf, Pulse) 
         [0076]    Where F is a function that can be a polynomial or any power of its argument and can be derived empirically. 
         [0077]    While the present invention has heretofore been described in connection with a conventional thermometer that measures temperature at a given time, it also applies to a continuous monitoring thermometer.  FIG. 8  is a cross sectional view of a patch thermometer  50  for continuous monitoring of the temperature of a patient. The thermometer  50  comprises a skin sensor layer  52  containing one or more sensors  54  and a remote sensor layer  56  containing an equal number but not necessarily of remote sensors  58  separated by an insulator  60 . An adhesive layer  62  on the front of the patch is provided to enable the probe to be attached to the subject. The patch thermometer  50  is designed to be kept in place for extended period of time and hence the skin layer will reach equilibrium, Ts (at equilibrium) at some point while the patch thermometer is in place and before the patch thermometer is removed. However, since Ts (at equilibrium) is not the core temperature Tcore, it needs to be calculated by determining the Bias and adding that to the local temperature, Ts (at equilibrium). 
         [0078]    The Q vs. T method previously described for establishing Bias may be utilized with some minor modification. To obtain the peak values, the skin sensor readouts at the beginning of the session (during the first 10-30 seconds of any temperature change, prior to sensor  54  reaching Ts (at equilibrium)) must be obtained since once steady state is attained there are no longer any peaks. Once the peaks are obtained the algorithm for obtaining Bias is as previously described with some further minor modifications. Thus an algorithm for obtaining Bias of a continuous monitoring thermometer would include the following steps 
         [0079]    1. Calculate Ts_avg and Tr_avg by averaging Tsi and Tri, respectively; 
         [0080]    2. Calculate Q, which is a function of Ts_avg-Tr_avg; 
         [0081]    3. Obtain values of Q vs. Ts_avg  4 . Find the peak point: Ts_avg-peak, Q-peak (Q,-T-spot) 
         [0082]    5. Use an empirical formula to calculate Bias, Bias=F(Ts_avg, Q)|peak 
         [0083]    Where Tsi and Tri are the i sensors of the first and second layers  52 ,  56 , respectively. The core temperature is obtained by adding the Bias to the equilibrium temperature according to the relation 
         [0084]    T core =Ts-avg (at equilibrium)+Bias 
         [0085]    Rather than using average values of Tsi and Tri the maximal values of the various Tsi and Tri readings or any other combination thereof, may be used in the above algorithm in place of Ts_avg and Tr_avg, respectively. 
         [0086]      FIG. 9  is a continuous temperature measurement patch  62  utilizing bio-impedance. The patch is similar to  FIG. 4  except that there are multiple skin and remote sensors  64  designed to be kept in place on a subject over an extended period of time along with electrodes  66 ,  68 . The alternatives described in connection with the single probe  20  are likewise applicable and the core temperature is derived as heretofore described. 
         [0087]    Similarly  FIG. 10  depicts a PPG based correction continuous measurement thermometer  70 . In this case, the patch contains temperature sensors  72 , LED  74  and photo-detector  76  which operate as previously described to obtain PPG and pulse information which may be used to derive the Bias as before under the formula 
         [0000]      Bias=F(B pf ), h 1 (Ts), h 2 (Tr). 
         [0088]    Thus in accordance with the above, the aforementioned objects and advantages are effectively attained. Although preferred embodiments of the invention have been disclosed and described, it should be understood that this invention is not limited thereby and the scope is to be determined by the following claims.