The present invention relates to a signal source identifying device for biological information and a signal source identifying method for biological information, both adapted to identify the position of a person-to-be-measured (i.e., a subject), which is a signal source of the biological information.
In recent years, biological information processing devices for monitoring biological information of a person-to-be-measured (such as pulse rate during exercise) have been developed to control the healthcare of the person-to-be-measured.
Usually, the pulse of a human body is detected in a state where a sensor is brought into contact with the human body, such as in a case where a photoelectric pulse sensor or an electrocardiograph is used to detect the pulse of the human body.
For example, a technique of a photoelectric pulse sensor is proposed in which a plurality of light beams each having a different wavelength are irradiated to a hand of a human being from a pulse wave measuring device attached to the hand of the human being, and a pulse wave of the human being is measured (see Patent Document 1). The technique described in Patent Document 1 was developed for the purpose of reducing error caused by irradiating the plurality of light beams each having a different wavelength to different sites in a human body.
Further, since noise components vary depending on different kinds of the exercise performed by the person-to-be-measured, and therefore there is a concern that the pulse rate calculated based on the noise components might be incorrect; thus, a technique is proposed to reduce the influence caused by variation in noise components (see Patent Document 1).
Further, a sensor of a non-contact type cardiopulmonary function monitoring device using a radio wave is proposed (see Patent Document 3).
Patent document 1: Japanese Unexamined Patent Application Publication No. 013-150707
Patent document 2 Japanese Patent No. 5076962
Patent document 3 Japanese Patent No. 3057438
However, a problem with the techniques described in the aforesaid patent documents is that, if a signal source generating the biological information (such as a human body or the like) is placed apart from an electric field type sensor, it will be difficult to accurately identify the position of the signal source.
Another problem is that, since the non-contact sensor disclosed in Patent Document 3 is a Doppler sensor in which a fast Fourier transformation and an arithmetic processing by computer need to be performed, the device will become large in scale and high in cost.
Further another problem is that, since the signal from the non-contact sensor is sent by a radio wave, there is a concern that minute vibrations (such as the vibration caused by an air conditioner, the vibration caused by curtains and/or the like) might be detected to thereby cause malfunction.
An object of the present invention is to provide a signal source identifying device adapted to identify the position of a person-to-be-measured (i.e., a subject), which is a signal source, by using at least two sensors, after reducing the influence of minute vibrations caused by surrounding environment.
To solve the aforesaid problems and achieve the object of the present invention, a signal source identifying device for biological information according to a first embodiment of the present invention includes: a first non-contact sensor which detects a biological information in a non-contact manner; a second non-contact sensor which detects a biological information in a non-contact manner, and which is arranged at a position apart from the first non-contact sensor by a predetermined distance; a first DC offset adjuster which adjusts DC offset after converting a signal outputted from the first non-contact sensor into a digital signal; and a second DC offset adjuster which adjusts DC offset after converting a signal outputted from the second non-contact sensor into a digital signal;
The signal source identifying device for biological information according to the first embodiment of the present invention further includes: a first subtractor which subtracts a signal outputted from the second DC offset adjuster from a signal outputted from the first DC offset adjuster; a first adaptive filter which extracts the signal from the first subtractor as a noise source; and a second subtractor which subtracts the output of the first adaptive filter extracted as the noise source from a signal obtained by converting the signal outputted from the first non-contact sensor into a digital signal.
Further, a signal source identifying method for biological information according to an aspect of the present invention includes the steps of:
(1) performing subtraction processing, with a first subtractor, between a first environmental information and a second environmental information, wherein the first environmental information is associated with a biological information detected by a first non-contact sensor, and the second environmental information is associated with a biological information detected by a second non-contact sensor;
(2) adding a signal outputted from the first subtractor to a first adaptive filter, and extracting the signal as a noise source;
(3) subtracting, with a second subtractor, the signal of the noise source extracted by the adaptive filter from the first environmental information associated with the biological information detected by the first non-contact sensor; and
(4) identifying the position of a subject in accordance with the strength of the signal from the second subtractor.
Further, a signal source identifying device for biological information according to a second embodiment of the present invention includes three non-contact sensors, which are a first non-contact sensor, a second non-contact sensor, and a third non-contact sensor. In the second embodiment, in addition to the first embodiment, subtraction processing between the second environmental information and a third environmental information is performed by a third subtractor, wherein the second environmental information is associated with the biological information detected by the second non-contact sensor, and the third environmental information is associated with a biological information detected by the third non-contact sensor; and a signal outputted from the third subtractor is added to a second adaptive filter, and extracted as a noise source.
Further, in the first embodiment, the signal of the noise source extracted by the second adaptive filter is subtracted from the first environmental information by a fourth subtractor, wherein the first environmental information is obtained from the second subtractor and associated with the biological information detected by the first non-contact sensor. Thereafter, the position of an object-to-be-measured (i.e., the subject) is identified in accordance with the strength of the signal from the fourth subtractor.
With the signal source identifying device for biological information according to the present invention and the signal source identifying method using the device, since signals with the same phase can be emphasized from the signal of the biological information by using a plurality of radio wave-type sensors, it becomes possible to cancel the surrounding environmental noise.
Thus, the disadvantage that the radio wave-type non-contact radio wave sensor is susceptible to the surrounding environmental vibrations can be suppressed, so that the signal source can be identified with extremely high accuracy compared with prior techniques.
[Summary of a Signal Source Identifying Method for Biological Information According to the Present Invention]
A signal source identifying method and a signal source identifying device for biological information according to the present invention will be described below with reference to the attached drawings.
Examples of the radio wave-type non-contact radio wave sensor include a Doppler sensor described in Patent Document 3, a pulse sensor proposed by the inventor of the present invention in another patent application (Patent application No. 2007-217093), and the like. The aforesaid pulse sensor is adapted to irradiate a radio wave to a person-to-be-measured, and detect the change in frequency of the radio wave reflected from or passing through the person-to-be-measured to thereby detect the pulse of the person-to-be-measured. However, the aforesaid radio wave-type sensor uses a radio wave having a VHF (Very High Frequency) band. Since the radio wave having a VHF band expands non-directionally, it was difficult to identify the position of the person-to-be-measured (i.e., a subject), which is a signal source, with a single sensor.
In contrast,
Generally, a radio wave-type non-contact radio wave sensor (such as the sensor A or the sensor B) outputs a stronger signal when the subject X (which is the source of a radio wave) approaches the sensor. In other words, as shown in
On the other hand, as shown in
The signal source identifying device and the signal source identifying method for biological information according to the present invention are made based on the aforesaid principle.
[Configuration of First Embodiment (Signal Source Identifying Device) of the Present Invention]
An embodiment of the signal source identifying device for biological information according to the present invention will be described below with reference to the attached drawings.
First, the configuration of the signal source identifying device for biological information (hereinafter referred to as “signal source identifying device”) of the present embodiment will be described below with reference to
As shown in
The sensor A is connected to an A/D (analog/digital) converter 10, and the A/D converter 10 is connected to an adder 12. The output of the adder 12 is connected to an integrator 14, a subtractor 16 (also referred to as a “first subtractor”), and a delay circuit 17. The output of the A/D converter 10 (i.e., the output of the sensor A) and the output of the integrator 14 are digitally summed by the adder 12. The adder 12 and the integrator 14 constitute a first DC offset adjuster.
The sensor B is connected to an A/D converter 11, and the A/D converter 11 is connected to an adder 13. The output of the adder 13 is connected to an integrator 15 and the subtractor 16. The output of the A/D converter 11 (i.e., the output of the sensor B) and the output of the integrator 15 are digitally summed by the adder 13. The adder 13 and the integrator 15 constitute a second DC offset adjuster.
The subtractor 16 is connected to an adaptive filter 18. The adaptive filter 18 is configured by a FIR filter (Finite Impulse Response) filter 18a and a LMS (Least Mean Square) coefficient adjuster 18b. The output of the adaptive filter 18 is connected to a subtractor 19 (also referred to as a “second subtractor”). The output of the subtractor 19 is connected to the LMS coefficient adjuster 18b, as well as being connected to an output terminal 20.
[Operation of First Embodiment (Signal Source Identifying Device) of the Present Invention]
Next, the operation of the signal source identifying device of the present embodiment will be described below with reference to
Generally, a signal waveform of biological information (such as a pulse waveform, an electrocardiographic waveform or the like) is not vertically symmetric with respect to its reference potential. In other words, coherencies (i.e., the “+” component and the “−” component) are not equal to each other.
The function of the integrators 14, 15 is to make a waveform whose positive (+) component and negative (−) component are not symmetric to become a waveform symmetric in area.
Due to such processing, when performing subtraction processing between the waveform outputted from the sensor A and the waveform outputted from the sensor B, the residual error can be reduced. This is because, when performing subtraction processing between two signals whose area of positive (+) is equal to whose area of negative (−), at least error (such as offset error) can be reduced.
Further, the output of the adder 12 and the output of the adder 13 are supplied to the subtractor 16 where the output of the adder 13 is subtracted from the output of the adder 12. The signal outputted from the subtractor 16 is a kind of noise signal. For example, as shown in
The output signal of the subtractor 16 is supplied to the FIR filter 18a of the adaptive filter 18. Here, the LMS coefficient adjuster 18b performs coefficient adjustment, which depends on the magnitude of the output of the subtractor 19. The output of the adaptive filter 18 is supplied to the subtractor 19 where such output is subtracted from a signal outputted from the delay circuit 17 and depending on the sensor A. As described above, if the distance between the sensor A and the subject X is substantially equal to the distance between the sensor B and the subject X, since the signal from the subtractor 16 becomes a signal of a noise source close to “zero”, even if the output of the LMS adaptive filter 18 is subtracted by the subtractor 19 from the output of the delay circuit 17, which is equivalent to the signal output of the sensor A, the signal outputted from the subtractor 19 to the output terminal 20 will become a signal whose strength is close to that of the signal of the biological information actually obtained from the sensor A.
On the other hand, as shown in
[Configuration and Operation of Second Embodiment (Signal Source Identifying Device) of the Present Invention]
As described above, in the first embodiment of the present invention, two sensors (the sensor A and the sensor B) are used to detect the position of the sensor B as a difference between the output signal from the sensor A and the output signal from the sensor B.
In the example shown in
As shown in
The signal from the third sensor C is converted into a digital signal by the A/D converter 22, and added to the output of the integrator 24 by the adder 23. The adder 23 and the integrator 24 constitute a third DC offset adjuster. Further, in the subtractor 25, the output of the adder 23 is subtracted from the output of the adder 13. The output of the adder 13 is an output obtained by summing the signal obtained by converting the signal from the second sensor B into a digital signal and the output of the integrator 15. Here, the output of the subtractor 25 becomes a value close to “zero” when the signal from the second sensor B and the signal from the second sensor C have the same level. In other words, the output of the subtractor 25 becomes a value close to “zero” when the distance between the sensor B and the subject X is equal to the distance between the sensor C and the subject X. On the other hand, when the distance between the subject X and the sensor B is different from the distance between the subject X and the sensor C, since either one of the sensor B and the sensor C has stronger output than the other, the signal from the subtractor 25 will be supplied to the second adaptive filter 26.
The output of the second adaptive filter 26 is supplied to the subtractor 27 where the output of the second adaptive filter 26 is subtracted from the output of the subtractor 19. Here, if the subject X is located at a position equidistant from each of the three sensors (i.e., the sensor A, the sensor B and the sensor C), since the output of the first subtractor 16 and the output of the third subtractor 25 are each close to “zero”, the output of the first adaptive filter 18 and the output of the second adaptive filter 26 will each be close to “zero”, and therefore the second subtractor 19 and the fourth subtractor 27 will each extract the output of the delay circuit 17 as it is. Thus, the signal of the biological information detected from the first sensor A is extracted to the output terminal 20 as it is.
On the other hand, if the distance of the second sensor B from the subject X is not equal to the distance of the third sensor C from the subject X, a signal of the second sensor B or the third sensor C, whichever is close to the subject, will be outputted from the subtractor 25, and supplied to the fourth subtractor 27 through the adaptive filter 26. As a result, the output of the adaptive filter 25 is subtracted from the signal outputted from the second subtractor 19, so that a signal close to “zero” is outputted to the output terminal 20. In other words, in the embodiment configured by the circuit shown in
In the first embodiment and the second embodiment described above, a LMS adaptive filter is used as the adaptive filter of the present invention; however, the form of the adaptive filter of the present invention is not particularly limited. A filter other than the LMS adaptive filter using a LMS algorithm may also be used as the adaptive filter of the present invention. For example, a filter using a CLMS (Complex Least Mean Square) algorithm, a filter using a NLMS (Normalized Least Mean Square) algorithm or the like may also be used as the adaptive filter of the present invention.
Further, apart from the aforesaid filters using LMS algorithm, an adaptive filter using a Projection algorithm, an adaptive filter using a SHARF (Simple Hyperstable Adaptive Recursive Filter) algorithm, an adaptive filter using a RLS (Recursive Least Square) algorithm, an adaptive filter using a FLMS (Fast Least Mean Square) algorithm, an adaptive filter using a DCT (Discrete Cosine Transform), a SAN (Single Frequency Adaptive Notch) filter, an adaptive filter using a neural network, an adaptive filter using a genetic algorithm or the like may also be used to perform the same processing as that of the adaptive filter of the present invention.
It is to be understood that the present invention is not limited to the embodiments described above, but includes various modifications and applications without departing from the scope of the claims of the present invention.
Number | Date | Country | Kind |
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2015-059286 | Mar 2015 | JP | national |
Filing Document | Filing Date | Country | Kind |
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PCT/JP2016/058900 | 3/22/2016 | WO | 00 |