as stated above , oximeter detectors are subject to a variety of interfering signals . currently the largest source of error in the electronics of a pulse oximeter arises from capacitive coupling in the patient cable between the led wires and the detector wires . on the rising and falling edges of the led voltage an impulse current appears in the detector lines due to this capacitive coupling . for example , it has been determined that the error in measured photo current due to such impulse currents can be up to around 71 pa , for example , out of a batch of 17 new cables . older cables that have been worn will have compromised shields that could result in a much larger error . fig1 shows a block diagram explaining the influences of the main interfering sources in oximeter systems . generally , an oximeter sensor comprises a red led and ir led whose emitted light is passed through a patient &# 39 ; s tissue . a detector receives these signals but also receives some ambient light as shown on the left side of fig1 . node 110 simulates a summing point within the photo detector or detectors of an oximeter system . thus , the photo detector produces a signal 120 which comprises the red component , the ir component , and an ambient light component . node 130 simulates the summing point of capacitive cable transient signals introduced into the detector signal . thus , output signal 140 now comprises in addition to the signals mentioned above , the cable transient signals . signal 140 is then fed into filter 150 comprising a transfer function h ( s ). the output signal of filter 150 is then fed to an analog - to - digital - converter 160 . fig2 shows exemplary signal curves for each signal component as shown in fig1 as well as the composite signal . for each red and ir signal pulse , according to an embodiment , 8 samples p 1 . . . 8 are taken as indicated on the bottom x - axis . during the time frame p 1 . . . 8 , the ambient light , shown as the dotted line which can be dominated by components of the 50 hz / 60 hz power line signals , is approximated by a linear line as shown in the top curve between points x 1 and x 2 . the transient pulses caused by the rising and falling edges of the red and ir signals are shown as signals w 1 , w 2 , w 3 , and w 4 . next follows the red signal and then the ir signal . the bottom curve represents the composite signal as it is fed to the filter 150 . this composite signal represents a sum of the above signals . this signal is then sampled by an analog - to - digital converter 160 as indicated at the bottom line of fig2 . as shown in fig2 , 8 samples are produced for each red and ir pulse . however , according to other embodiments , more than eight samples can be generated which will improve performance . the composite signal which is filtered by filter 150 and sampled by analog - to - digital - converter 160 comprises the component signals as discussed with respect to fig3 . thus , each component signal is first filtered before it is sampled by analog - to - digital converter 160 . the filter is used for anti - aliasing and to help eliminate out of band noise . thus , the filter 150 has a transfer function of h ( s ) that spreads out the composite signal in the time domain . since the filter 150 is a linear system , each of the components can be analyzed by assuming they have all gone through the filter independently . the result is that an impulse will have energy spread across all the sample periods . fig3 shows an exemplary output signal from signal filter 150 to which a series of periodic pulses w 1 is fed . the respective sample points p 1 . . . 8 produced by the analog - to - digital - converter 160 resulting from the pulses w 1 fed to filter 150 are shown in fig3 by the vertical lines ending with a crossbar . the magnitude of the sample at each sampling point is , thus , a function of the magnitude of the impulse w 1 and the impulse response of the system . since the time between the impulse w 1 and the sample time is constant , the size of the sample at p 1 is a constant times the magnitude of the impulse . this results in : the results for the red and ir components of the composite signal can be represented in a similar way , as a constant representing the impulse response at that time multiplied by the current . this results in : the component of the signal representing the ambient light can be approximated for a sample period ( p 1 . . . . p 8 ) by a linear approximation a n between points x 1 and x 2 as shown in fig4 , wherein point x 1 is associated with sample time p 1 and x 2 is associated with sample time p 8 . a new approximation a n + 1 follows for the next eight samples as indicated in fig4 . the terms for ambient light only can , thus , be represented as : the magnitude of the sample for the composite signal is the sum of all components . for instance : p 1 = 1 · x 1 + 0 · x 2 + k 1 · w 1 + k 7 · w 2 + k 5 · w 3 + k 3 · w 4 + c 1 · r + b 5 · i the whole system can , thus , be represented in matrix form as : after measuring samples p 1 , p 2 , p 3 . . . p 8 , the individual components of the composite signal can be isolated by solving the system of equations . in practice only the red and ir components need to be solved as the other components are usually of no interest . this can be done by only computing the results for the bottom two rows of the system . the matrix of coefficients is a constant determined by the impulse response of the system . to solve the matrix for the red and ir components , the inverse of the matrix only needs to be computed once for a particular front end filter 150 , which can be done at start - up if a variable filter design is used or during the design of the system if the system uses a constant filter . also an adaptive filter might be used . then , the computation has to be performed after each adaptation . as a result , the cable transients w can be eliminated from the signal on a real time basis . stray capacitances in the cable will no longer be an issue . this also allows a front end to be designed with a much tighter anti - aliasing filter which will reduce noise and interference . as mentioned above , a better performance can be achieved by increasing the number of samples per red and ir measuring period . this oversampling will result in an over determined system that can be solved by using a pseudo - inverse to the constant matrix which gives a result that is a least squares fit to the sampled data . in general more over sampling will result in a more accurate measurement . according to a further embodiment , the same technique can be used for more than two wavelength signals . this may also result in an over determined system that can be solved with a pseudo - inverse . the above described concept is not limited to the error signals discussed , i . e ., the ambient light signal and the cable transients . other known error sources can be included in the matrix as discussed above . fig5 shows an example of a system for solving the matrix equations . the data stream generated by the analog - to - digital converter 160 is fed to a matrix 410 . separate equations 420 and 430 for the red signal and for the ir signal are computed to solve the matrix and generate the respective component signals for the red and ir signals without the external error signals introduced to the signal fed to the analog - to - digital converter 160 . the system shown can be easily implemented in a digital signal processor , microcontroller , or application specific integrated circuit ( asic ). the invention , therefore , is well adapted to carry out the objects and attain the ends and advantages mentioned , as well as others inherent therein . while the invention has been depicted , described , and is defined by reference to particular preferred embodiments of the invention , such references do not imply a limitation on the invention , and no such limitation is to be inferred . the invention is capable of considerable modification , alteration , and equivalents in form and function , as will occur to those ordinarily skilled in the pertinent arts . the depicted and described preferred embodiments of the invention are exemplary only , and are not exhaustive of the scope of the invention . consequently , the invention is intended to be limited only by the spirit and scope of the appended claims , giving full cognizance to equivalents in all respects .
a method for processing an analog composite signal in a system has the steps of receiving a composite signal with at least one first signal component and at least one interfering signal component ; filtering the composite signal with a filter having a transfer function h ; sampling the filtered composite signal in periodic intervals wherein each periodic interval has n samples ; forming a matrix equation representing the composite signal wherein the matrix equation has a signal vector with the at least first one signal component and the at least one interfering signal component and a matrix comprising weighted coefficients ; solving the matrix equation to determine the at least one signal component ; outputting the at least one signal component .