Abstract:
A method and apparatus for reducing motion artifact and spurious noise effects when computing estimates of values representative of at least one physiological parameter of a subject. For motion, measured motion values are compared with a motion threshold and the taking of physiological measurements used for computing the physiological parameter estimate values are either suspended until a measured motion value is under the threshold or a correction function is applied to the physiological measurements, the correction function being based on the measured motion values. As for spurious noise, physiological measurements taken while emitters are turned off are subtracted from physiological measurements taken while emitters are turned on in order to eliminate outside noise contamination.

Description:
TECHNICAL FIELD 
       [0001]    The present invention relates to a method and apparatus for the reduction of spurious effects on physiological measurements. More specifically, the present invention relates to a method and apparatus for the reduction of motion artifact and spurious noise effects on physiological measurements. 
       BACKGROUND 
       [0002]    There is a great potential for applying optical technologies to biology, medicine and sports to track various physiological parameters or states and provide real time information to the user or to medical personnel. While many studies have shown this great potential, very few concrete products using optical technologies have been developed or marketed. Some of the reasons for this are the difficulty to isolate a signal of interest from the various interferences that come from the external environment, the fact that the measurements must be made in a continuous manner on a constantly moving subject and to the variable nature of the human body itself. 
         [0003]    The elastic nature of human tissue complicates the taking of optical measurements when a subject is in motion since tissue compression and expansion instantly affect the optical properties of the tissue while the signal of interest remains fairly constant. 
         [0004]    A complication that comes with the use of portable measurement devices is that the nature and the sources of the noises are constantly changing. Noise sources are present in both the measurement device itself and the external environment. Electrical noises from AC lines or surrounding electronic devices are obvious noise sources. Optical noise coming from the sun or from artificial lights may migrate into the skin and through the optical sensors. Both the electric and the optical noises may vary over time and with the motion of the subject. 
         [0005]    In the present specification, there is described a method and apparatus designed to overcome the above-described limitations. 
       SUMMARY 
       [0006]    The present invention relates to a method for reducing motion artifact when computing estimates of values representative of at least one physiological parameter of a subject, comprising the steps of measuring a motion value and comparing the motion value with a motion threshold. If the compared motion value is lower than the motion threshold then taking at least one physiological measurement, estimating the values representative of the at least one physiological parameter by applying a mathematical model to the at least one physiological measurement and providing the estimate of the values representative of the at least one physiological parameter. 
         [0007]    The present invention also relates to a method for reducing motion artifact when computing estimates of values representative of at least one physiological parameter of a subject, comprising the steps of repeatably measuring a motion value and comparing each motion value with a motion threshold. If the compared motion value is lower than the motion threshold then taking at least one physiological measurement, estimating the values representative of the at least one physiological parameter by applying a mathematical model to the at least one physiological measurement and providing the estimates of the values representative of the at least one physiological parameter. If not, after a predetermined number of consecutive compared motion values that are higher than the motion threshold then providing a warning to the subject. 
         [0008]    The present invention further relates to a method for reducing motion artifact when computing estimates of values representative of at least one physiological parameter of a subject, comprising the steps of measuring a motion value, taking at least one physiological measurement, applying a correction function to the at least one physiological measurement, the correction function being based on the measured motion value, estimating the values representative of the at least one physiological parameter by applying a mathematical model to the at least one corrected physiological measurement and providing the estimates of the values representative of the at least one physiological parameter. 
         [0009]    The present invention further still relates to a method for reducing spurious noise when computing estimates of values representative of at least one physiological parameter of a subject, comprising the steps of generating a probing signal comprising at least one wavelength, propagating the probing signal from a propagation point, measuring reflectance values of the probing signal for a subset of the at least one wavelength from at least two distances from the propagation point, shutting off the probing signal for the subset of the at least one wavelength, measuring a shut-off reflectance value from the at least two distances from the propagation point, computing adjusted reflectance values by subtracting the shut-off reflectance values from the reflectance values, estimating the values representative of the at least one physiological parameter by applying a mathematical model to adjusted reflectance values and providing the estimates of the values representative of the at least one physiological parameter. 
         [0010]    The present invention also relates to an apparatus implementing the above described methods. 
         [0011]    The foregoing and other objects, advantages and features of the present invention will become more apparent upon reading of the following non restrictive description of illustrative embodiments thereof, given by way of examples only with reference to the accompanying drawings. 
     
    
     
       BRIEF DESCRIPTION OF THE FIGURES  
         [0012]    Non-limitative illustrative embodiments of the invention will now be described by way of examples only with reference to the accompanying drawings, in which: 
           [0013]      FIG. 1  which is labeled “Prior Art”, is a block diagram showing an apparatus for the monitoring of skin parameters; 
           [0014]      FIG. 2  is a block diagram showing an apparatus for the monitoring of skin parameters similar to  FIG. 1  but with a motion sensor; 
           [0015]      FIG. 3  is a flow diagram of an algorithm for the monitoring of skin parameters; 
           [0016]      FIG. 4  is a flow diagram of an algorithm for the monitoring of skin parameters with motion artifact reduction; 
           [0017]      FIG. 5  is a flow diagram of an algorithm for setting a motion threshold; 
           [0018]      FIG. 6  is a flow diagram of an alternative algorithm for the monitoring of skin parameters with motion artifact reduction; 
           [0019]      FIG. 7  is a flow diagram of an algorithm for setting a motion correction factor; 
           [0020]      FIG. 8  is a flow diagram of an algorithm for the monitoring of skin parameters with spurious noise reduction; 
           [0021]      FIG. 9  is a flow diagram of an algorithm for the monitoring of skin parameters with motion artifact reduction and spurious noise reduction; 
           [0022]      FIG. 10  shows integrating amplifier waveforms; and 
           [0023]      FIG. 11  shows transimpedance amplifier waveforms. 
       
    
    
     DETAILED DESCRIPTION  
       [0024]    Generally stated, a method and apparatus according to an illustrative embodiment of the present invention provide means to reduce the adverse effects of environmental conditions such as motion artifact and spurious noise effects on physiological measurements used to compute estimates of physiological parameters, for example skin parameters. 
         [0025]    Referring to  FIG. 1 , an example of a monitoring apparatus  100  estimates skin parameters such as, for example, chromophore concentrations and scattering coefficient is illustrated. The monitoring apparatus  100  uses N light sources (or emitters)  102 , each generating a light beam at respective predetermined wavelengths λ 1  to λ N , coupled to a N×1 optical coupler  104  in order to generate a probing light beam  105  comprising all of the N wavelengths of the N individual light sources  102 . The number of light sources  102 , and thus wavelengths, as well as their power levels, may vary depending on the application. 
         [0026]    The probing light beam  105  then goes through a 1×2 optical coupler  106  that provides the probing light beam  105  to both a light source monitor  108  and to an emitter collimating optic  110 . The emitter collimating optic  110 , advantageously positioned in direct contact with the skin, propagates the probing light beam  105  into the dermis  112  of the skin. The probing light beam  105  is then attenuated and scattered into a number of reflected beams  111  by various scatterers  113  and chromophores  115 , which are present in the dermis. The attenuated and reflected beams  111  are then received by receiver collimating optics  114 , providing optical signals I 1  to I M  to photodetectors  116 . Each of the receiver collimating optics  114  is positioned at a distance away from the emitter collimating optic  110  that is different from that of the other receiver collimating optics  114 . The number of receiver collimating optics  114  may vary according to the application. A temperature sensor  120  provides a signal indicative of the temperature of the skin. 
         [0027]    An Analog to Digital Converter (ADC)  118  then converts the analog signals from the light source monitor  108 , the photodetectors  116 , as amplified by amplifiers  117 , and the temperature sensor  120  into digital signals which are provided to a micro-controller  122 . The micro-controller  122  includes an algorithm that controls the operations of the apparatus and performs the monitoring of certain clinical states, and may also perform estimations of certain biological or physiological parameters such as, for example, chromophore concentrations and scattering coefficient, which will be further described below. The results of the monitoring and estimations are then given to the wearer of the monitoring apparatus  100  by either setting a visual, audio and/or mechanical alarm, when a certain clinical state is detected, of displaying the result via alarm/display  124 . The micro-controller  122  may also be connected to an input/output  126  through which data such as, for example, a reference blood glucose level may be provided to the monitoring apparatus  100  or through which data such as, for example, chromophore concentrations and scattering coefficient may be provided from the monitoring apparatus  100  to other devices. It is to be understood that the input/output  126  may be any type of interface such as, for example, an electrical, infrared (IR) or a radio frequency (RF) interface. 
         [0028]    An example of an algorithm that may be executed by the micro-controller  122  is depicted by the flow chart shown in  FIG. 3 . The steps composing the algorithm are indicated by blocks  206  to  220 . 
         [0029]    At block  206  the algorithm starts by propagating light comprising one or more wavelengths into the skin, the wavelengths being selected according to the application of interest such that variations on light reflectance values at the input of the receiver collimating optics  114  may be observed as a function the variation of some estimated parameters. 
         [0030]    At block  208 , the diffuse light reflectance is measured at two or more distances from the source of the propagated light of block  206 . The diffuse light reflectance measurements are advantageously taken simultaneously for all distances, the longer the time interval between each measurement, the less precise the algorithm results may become. The distances, as well as their values, are selected according to the application. The more distances are used, the more precise the diffuse light reflectance model becomes, but also the more computation intensive it becomes and more expensive becomes the associated estimation apparatus  100 . 
         [0031]    At block  214 , which is optional, the skin temperature is measured. 
         [0032]    Then, at block  216 , the algorithm computes estimates of the desired physiological parameters using the reflectance measurements, and skin temperature if measured, and displays those estimates at block  218  using display/alarm  124 . The algorithm may further detect clinical conditions using the estimated parameter values, in which case block  218  may also activate an alarm using display/alarm  124 . It is to be noted that the parameter estimates and/or detection of clinical conditions may also be provided to another device for further processing using input/output  126 . Following which, at block  220 , the whole algorithm is repeated if continuous monitoring is desired, otherwise the algorithm ends. 
         [0033]    Various environmental conditions may affect the photodetectors  116  readings of the reflected beams  111  received by receiver collimating optics  114 , which readings are used at block  216  to compute estimates of the desired physiological parameters. One such condition is movement of the wearer of the device, which may cause motion artifacts between the apparatus and the skin and/or the skin and the underlying tissues. A second condition is spurious noise present in the reflected beam  111 , such as caused by ambient lighting, to which possible electrical offsets from the photodetectors  116  or amplifiers  117  may be added. 
       Motion Artifact Reduction 
       [0034]    In order to reduce motion artifact caused by, for example, relative movement between the skin and the monitoring device  100  or skin structure deformation, the monitoring device  100  illustrated in  FIG. 1  may be modified by adding a motion sensor  121  resulting in the monitoring device  100 ′ illustrated in  FIG. 2 . The motion sensor  121 , which may be, for example, an accelerometer, a pressure sensor or a combination of both and may be advantageously positioned in contact with the skin. It is to be understood that in the case where the motion sensor  121  is, for example, an accelerometer, it may be positioned at another location within or on the monitoring device  100 ′. 
         [0035]    The ADC  118  then converts the analog signals from the motion sensor  121 , into a digital signal which is supplied to the micro-controller  122 . The micro-controller  122  algorithm, which controls the operations of the apparatus and performs various computations and estimations according to the applications, then takes into account the information provided by the motion sensor  121 . 
         [0036]    The algorithm previously depicted by the flow chart shown in  FIG. 3  may be modified to take into account this new information resulting in the algorithm depicted by the flow chart shown in  FIG. 4 . The steps composing the algorithm are indicated by blocks  202  to  220 . 
         [0037]    At block  202  the algorithm starts by measuring the motion of the monitoring device  100 ′. To that end, many current off the shelf accelerometers and/or pressure sensors may be used for motion sensor  121 . Then, at block  204 , the algorithm verifies if the measured motion is inferior to a preset threshold value, if so it goes to block  206  and proceeds as per the previous description of the algorithm of  FIG. 3 , if not, the algorithm goes back to block  202 . 
         [0038]    Alternatively, in case where the wearer of the monitoring apparatus  100 ′ is in constant movement above the predetermined motion threshold, a timer or a counter may be added to the algorithm in order to set an alarm to warn the wearer to stand still for a certain period of time in order for the apparatus to proceed with an estimation of the desired physiological parameters. 
         [0039]    The value of the threshold used at block  204  may be set according to theoretical values or may alternatively be set by the algorithm depicted by the flow chart shown in  FIG. 5 . The steps composing the algorithm are indicated by blocks  302  to  314 . 
         [0040]    At block  302  the algorithm starts by computing initial estimates of the desired physiological parameters using, for example, the algorithm depicted by the flow chart shown in  FIG. 3 . At block  304 , the algorithm measures the initial motion value of the monitoring apparatus  100 ′ and at block  306 , sets the motion threshold value to that measured initial value. 
         [0041]    Then, at block  308 , incremental movement is applied to the monitoring apparatus  100 ′, following which estimates of the desired physiological parameters are computed at block  310  and a new motion value is measured at block  312 . 
         [0042]    The algorithm then compares the current parameters estimates to the previous estimates in order to determine if there is a significant difference. If there is a significant difference then the algorithm terminates and returns the value of the motion threshold, if not, the algorithm goes back to block  306  where the motion threshold is set to the current motion value and proceeds to repeat blocks  308  to  314 . 
         [0043]    The above described motion artifact reduction technique may be used with many other types of measurement apparatuses such as, for example, Oximeters or any other measurement apparatus susceptible to motion. 
         [0044]    An alternative algorithm to the algorithm depicted by the flow chart shown in  FIG. 4  is depicted by the flow chart shown in  FIG. 6 . The steps composing the algorithm are indicated by blocks  202  to  220 . 
         [0045]    At block  202  the algorithm starts by measuring the motion of the monitoring device  100 ′. Then, at block  206 , the algorithm propagates light comprising one or more wavelengths into the skin, the wavelengths being selected according to the application of interest such that variations on light reflectance values at the input of the receiver collimating optics  114  may be observed as a function the variation of some estimated parameters. 
         [0046]    At block  208 , the diffuse light reflectance is measured at two or more distances from the source of the propagated light of block  206 . The diffuse light reflectance measurements are advantageously taken simultaneously for all distances, the longer the time interval between each measurement, the less precise the algorithm results may become. The distances, as well as their values, are selected according to the application. The more distances are used, the more precise the diffuse light reflectance model becomes, but also the more computation intensive it becomes and more expensive becomes the associated estimation apparatus  100 ′. 
         [0047]    At block  209  the algorithm applies a motion correction function to the light reflectance measurements made at block  208 . The motion correction function is based on the measured motion and is applied in order to compensate for the variation in the measured light reflectance due to the movements of the wearer of the monitoring apparatus  100 ′. 
         [0048]    At block  214 , which is optional, the skin temperature is measured. 
         [0049]    Then, at block  216 , the algorithm computes estimates of the desired physiological parameters, using the corrected reflectance measurements, and skin temperature if measured, and displays those estimates at block  218  using display/alarm  124 . The algorithm may further detect clinical conditions using the estimated parameter values, in which case block  218  may also activate an alarm using display/alarm  124 . It is to be noted that the parameter estimates and/or detection of clinical conditions may also be provided to another device for further processing using input/output  126 . Following which, at block  220 , the whole algorithm is repeated if continuous monitoring is desired, otherwise the algorithm ends. 
         [0050]    The motion correction function used at block  209  may be set using the algorithm depicted by the flow chart shown in  FIG. 7 . The steps composing the algorithm are indicated by the blocks  302  to  316 . 
         [0051]    At block  302  the algorithm starts by measuring the light reflectance by propagating light comprising one or more wavelengths into the skin, the wavelengths being selected according to the application of interest such that variations on light reflectance values at the input of the receiver collimating optics  114  may be observed as a function the variation of some estimated parameters. The diffuse light reflectance is measured at two or more distances from the source of the propagated light. The diffuse light reflectance measurements are advantageously taken simultaneously for all distances, the longer the time interval between each measurement, the less precise the algorithm results may become. The distances, as well as their values, are selected according to the application. At block  304 , the algorithm measures the initial motion value of the monitoring apparatus  100 ′ and at block  307 , stores the light reflectance measurements as well as the initial motion value. 
         [0052]    Then, at block  308 , incremental movement is applied to the monitoring apparatus  100 ′, following which light reflectance is measured at block  310  and a new motion value is measured at block  312 . 
         [0053]    The algorithm then compares, at block  314 , the measured motion value to a motion threshold. The motion threshold may be set, for example, to a value that is superior to any motion value that may be generated during normal use by a wearer of the monitoring apparatus  100 ′. If the measured motion value is above the motion threshold, then the algorithm goes to block  316  where a motion correction function is computed using the stored light reflectance measurements and associated measured motion values and then terminates. If the measured motion value is not above the motion threshold, the algorithm goes back to block  307  where the current light reflectance measurements and measured motion value are stored, and proceeds to repeat blocks  308  to  314 . 
         [0054]    It should be understood that the computation of the motion correction function may be done using any suitable numerical analysis method such as, for example, cubic splines or linear regressions. It should be further understood that if, for example, both an accelerometer and a pressure censor are used, that the threshold may have two components or a single combined component. Furthermore, in the case where the threshold has more than one component, either or all of the measured motion values components may be required to be above or below each corresponding threshold component. 
       Spurious Noise Reduction 
       [0055]    The photodetectors  116  converts the optical signal to an electrical current that will be amplified by amplifiers  117 . Two commonly used amplifier technologies are the integrating amplifier and the transimpedance amplifier.  FIGS. 10 and 11  show integrating amplifier waveforms and transimpedance amplifier waveforms, respectively, for a given λi. 
         [0056]    Referring to  FIG. 10 , when a signal is emitted by the light sources  102 , a first waveform  32  is perceived from the photodetectors  116  using integrating amplifiers. The waveform  32  comprises signal  36 , noise  37  and electrical offset  38  components. When no signal is emitted by the light sources  102 , a second waveform  34  is perceived from the photodetectors  116 , which waveform  34  comprises noise  37  and electrical offset  38  components. The noise  37  component is due, for example, to external lighting conditions which diffuse additional light within the skin and integrated electrical offsets. As for the electrical offset  38  component, it is mainly due to charge transfer during the switching of the integrator and integrator amplifier voltage offsets. 
         [0057]    As may be observed, the undesired first waveform  32  components, i.e. the noise  37  and the electrical offset  38  components, may be measured separately from the signal  36  component by taking measurements when the light sources  102  are turned off, i.e. when there is no signal  36  component in the waveform detected by the photodetectors  116 . 
         [0058]    The signal  36  component may then be recuperated from the first waveforms  32  by subtracting the slope  35  of the second waveform  34  from the slope  33  of the first waveform  32 , thus subtracting the noise  37  and the electrical offset  38  components. The slopes  33 ,  35  may be determined using, for example, least square fitting. 
         [0059]    Similarly for photodetectors  116  using transimpedance amplifiers, as shown in  FIG. 11 , when a signal is emitted by the light sources  102 , a first waveform  42  is perceived by the photodetectors  116 , which waveform  42  comprises signal  46 , noise  47  and electrical offset  48  components. When no signal is emitted by the light sources  102 , a second waveform  44  is perceived by the photodetectors  116 , which waveform  44  comprises noise  47  and electrical offset  48  components. 
         [0060]    As may be observed, the undesired first waveform  42  components, i.e. the noise  47  and the electrical offset  48  components, may be measured separately from the signal  46  component by taking measurements when the light sources  102  are turned off, i.e. when there is no signal  46  component in the waveform detected by the photodetectors  116 . 
         [0061]    The signal  46  component may then be recuperated from the first waveforms  42  by subtracting the intensity value  45  of the second waveform  44  from the intensity value  43  of the first waveform  42 , thus subtracting the noise  47  and the electrical offset  48  components. 
         [0062]    The algorithm previously depicted by the flow chart shown in  FIG. 3  may be modified in order to reduce spurious noise present in the reflected beam  111 , and possible electrical offsets from the photodetectors  116 , resulting in the algorithm depicted by the flow chart shown in  FIG. 8 . The steps composing the algorithm are indicated by blocks  206  to  220 . 
         [0063]    At block  206  the algorithm starts by propagating light comprising one or more wavelengths into the skin, the wavelengths being selected according to the application of interest such that variations on light reflectance values at the input of the receiver collimating optics  114  may be observed as a function the variation of some estimated parameters. 
         [0064]    At block  208 , the diffuse light reflectance is measured at two or more distances from the source of the propagated light of block  206 . The diffuse light reflectance measurements are advantageously taken simultaneously for all distances, the longer the time interval between each measurement, the less precise the algorithm results may become. The distances, as well as their values, are selected according to the application. The more distances are used, the more precise the diffuse light reflectance model becomes, but also the more computation intensive is becomes and more expensive becomes the associated estimation apparatus  100 . 
         [0065]    At block  210 , all light sources are turned off so that no light is emitted by the monitoring apparatus  100 . The algorithm then measures, at block  212 , the diffuse light reflectance as per block  208 , providing a measurement of the spurious noise and possible electrical offsets for each wavelength. 
         [0066]    At block  214 , which is optional, the skin temperature is measured. 
         [0067]    Then, at block  216 , the algorithm computes adjusted reflectance measurement values by subtracting the measurements taken at block  212  from the measurements taken at block  208 , as described above, computes estimates of the desired physiological parameters using the adjusted reflectance measurement values, and skin temperature if measured, and displays those estimates at block  218  using display/alarm  124 . The algorithm may further detect clinical conditions using the estimated parameter values, in which case block  118  may also activate an alarm using display/alarm  124 . It is to be noted that the parameter estimates and/or detection of clinical conditions may also be provided to another device for further processing using input/output  126 . Following which, at block  220 , the whole algorithm is repeated if continuous monitoring is desired, otherwise the algorithm ends. 
         [0068]    It should be noted that the time during which the diffuse light reflectance is measured, with either the light sources  102  emitting or off, should be kept as small as possible so that the spurious ambient light may not vary substantially between the measurement with the light sources  102  emitting and off. 
         [0069]    The above described spurious noise reduction technique may be used with many other types of measurement apparatuses such as optical measurement apparatuses, for example fiber optics Optical Loss Test Sets (OLTS), or Radio Frequency (RF) measurement apparatuses. 
       Motion Artifact Reduction and Spurious Noise Reduction 
       [0070]    Furthermore, both of the above-described techniques may be combined into a single algorithm depicted by the flow chart shown in  FIG. 9 . The steps composing the algorithm are indicated by blocks  202  to  220 , all of which have been previously described in detail. 
         [0071]    Further still, it should be noted that the repetition rate of the samples or the integration period taken for the purpose of the diffuse light reflectance measurements, for a given wavelength, may be chosen so as to be a multiple of the frequency of a parasitic signal, such as, for example, AC line interference. Thus, when the measurements are averaged over a certain number of periods, the effects of the parasitic signal cancel out. For example, an AC line parasitic signal may have a frequency of 60 Hz, so the repetition rate or the integration period of the samples may then be set to 18.75 Hz such that when the measurements are averaged over five periods, this corresponds to 16 periods at 60 Hz. Similarly, averaging the measurements over six periods corresponds to 16 periods at 50 Hz. The two may also be combined such that averaging the measurements over 30 periods corresponds to 96 periods at 60 Hz and 80 periods at 50 Hz, thus canceling out both the 50 Hz and 60 Hz parasitic signals. Of course, the repetition rate or the integration period of the samples may be selected so as to cancel parasitic signals at other frequencies. 
         [0072]    Although the present invention has been described by way of non-limitative illustrative embodiments and examples thereof, it should be noted that it will be apparent to persons skilled in the art that modifications may be applied to the present illustrative embodiments without departing from the scope of the present invention.