JP2011212383A - Biological information processor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a biological information processor capable of easily specifying a living body frequency.SOLUTION: The biological information processor includes: an acquisition part 210 for acquiring signals having biological information; an analysis part 220 for frequency-analyzing the signals and calculating a plurality of spectrum values corresponding to a plurality of frequencies; a weighting part 230 for executing weighting processing to the plurality of spectrum values on the basis of a frequency band assumed to present biological activity; and a specifying part 240 for specifying one of the plurality of frequencies as the living body frequency on the basis of the plurality of spectrum values after the weighting processing executed by the weighting part. The weighting part 230 evaluates the weight of a first spectrum value belonging to the frequency band to be larger than the weight of second spectrum values excluding the first spectrum value from the plurality of spectrum values.

Description

  The present invention relates to a biological information processing apparatus and the like.

  The biological information measuring device measures biological information such as a human pulse rate, blood oxygen saturation, body temperature, heart rate, and the like, and an example of the biological information measuring device is a pulse meter that measures the pulse rate. Since the heart rate normally matches the pulse rate (biological information in a broad sense), the pulse rate can be used instead of the heart rate. In other words, a pulse meter that measures the pulse rate as an example of the biological information measuring device is sometimes called a heart rate monitor. In addition, a biological information measuring device such as a pulse meter may be incorporated in an electronic device such as a clock, a mobile phone, a pager, or a personal computer, or may be combined with an electronic device.

  The biological information measuring device includes a biological information detector that detects biological information. The biological information detector includes, for example, a light emitting element that emits light toward a detection target portion of a subject to be inspected (user), and a detection target. And a light receiving element that receives light having biological information from the part. The biological information measuring device further includes a biological information measuring unit that measures biological information from a light reception signal (a signal having biological information in a broad sense) generated by the light receiving element, and the biological information measuring unit includes, for example, a pulse rate A pulse rate calculation circuit (in a broad sense, a biological information processing apparatus) that calculates (biological information in a broad sense) is included.

  Patent Document 1 discloses a pulse meter (biological information measuring device in a broad sense), and the light receiving element of the pulse meter (for example, the light receiving element 21 in FIG. 2B of Patent Document 1) is a detected part (for example, The reflected light (for example, the reflected light L2 in FIG. 2B of Patent Document 1) at the blood vessel K in FIG. 2B of Patent Document 1 is directly received.

  The pulse measurement device 1 (biological information processing device in a narrow sense) of Patent Document 1 extracts a first signal component in a first frequency range centered on a light emission frequency from a light reception signal at a light receiving element 21. 52 and a low-pass filter unit 53 that extracts a second signal component in a second frequency range lower than the pulsation frequency from the light reception signal at the light receiving element 21. The first signal component includes a pulsation component and a body motion component (in a narrow sense, the frequency spectrums f1 and f2 in FIG. 7A of Patent Document 1), and the second signal component is a body motion component and external light L3. The resulting noise component (in a narrow sense, the frequency spectrum f3 and f4, f5 and f6 in FIG. 7A of Patent Document 1) is included. The pulse measuring device 1 of Patent Literature 1 includes an arithmetic processing unit 60 that specifies the frequency spectrum f2 (f3) included in the first signal component and the second signal component as a body motion spectrum. The arithmetic processing unit 60 specifies the frequency spectrum f1 included in the first signal component but not included in the second signal component as the pulsation spectrum, and improves the detection accuracy of the biological information.

JP 2008-220722 A

  FIG. 7A of Patent Document 1 represents a plurality of spectrum values corresponding to a plurality of frequencies calculated by frequency analysis of a light reception signal from the light receiving element 21 and corresponds to a frequency (pulsation spectrum f1) exhibiting pulsation. The spectral value is larger than other spectral values. However, in an exercise state such as when a person walks, the spectrum value of the frequency f1 may be relatively small, for example, when there is a lot of noise caused by outside light. Further, even after the spectrum value of the body motion spectrum f2 is removed or reduced, the spectrum value with respect to the frequency f2 may become relatively large. In such a case, it becomes difficult to specify that the frequency f1 is a pulsation spectrum (biological frequency in a broad sense).

  According to some aspects of the present invention, a biological information processing apparatus capable of easily specifying a biological frequency can be provided.

One aspect of the present invention is an acquisition unit that acquires a signal having biological information;
Analyzing the frequency of the signal and calculating a plurality of spectral values corresponding to a plurality of frequencies;
A weighting unit for performing a weighting process on the plurality of spectrum values based on a frequency band assumed to exhibit a biological activity;
A specifying unit that specifies one of the plurality of frequencies as a biological frequency based on the plurality of spectrum values after the weighting process is performed by the weighting unit;
The weighting unit evaluates the weight of the first spectrum value belonging to the frequency band to be larger than the weight of the second spectrum value excluding the first spectrum value from the plurality of spectrum values. Related to the biological information processing apparatus.

  According to one aspect of the present invention, since the weight of the first spectral value belonging to the frequency band assumed to exhibit biological activity (eg, pulse, heartbeat, walking, etc.) is increased, the first spectral value is Compared to the second spectrum value belonging to another frequency band such as a body motion spectrum or a noise spectrum, it becomes relatively large. Here, the number of first spectrum values depends on the frequency band, and only one weight of one first spectrum value may be increased, and a plurality of weights of a plurality of first spectrum values is increased. You may let them.

  For example, the specifying unit specifies the frequency of the spectrum value that is the largest value as the biological frequency, and thus the specifying unit sets the frequency of the first spectral value as the biological frequency (for example, the number of pulse vibrations per second, 1 second). The number of beats per beat, the number of walks per second, etc.) can be easily specified. In addition, when there are a plurality of first spectrum values, the specifying unit may specify the frequency of the first spectrum value, which is the largest value among the plurality of first spectrum values, as a biological frequency, for example. Good.

In one embodiment of the present invention, the biological information processing apparatus includes:
You may further contain the memory | storage part which memorize | stores the at least 1 biological frequency identified in the past by the said specific part.

  Thus, the biological information processing apparatus can store biological frequencies specified in the past. In addition, you may memorize | store the biometric frequency log | history by continuing the memory | storage of all or one part of the biofrequency specified in the past. Even when the storage unit stores only one biological frequency, the one biological frequency can be reflected in the content or technique of the weighting process. Specifically, a frequency band that is assumed to exhibit biological activity may be determined based on one biological frequency stored in the storage unit. Moreover, you may determine the weight (weighting coefficient) of a 1st spectrum value based on one biological frequency memorize | stored in a memory | storage part. In addition, it may be determined whether to stop the weighting process based on one biological frequency stored in the storage unit.

In one embodiment of the present invention, the storage unit may store at least two biological frequencies.
The weighting unit may determine a change tendency of the at least two biological frequencies based on the at least two biological frequencies stored in the storage unit, and obtain a determination result.

  Thus, when the storage unit stores two or more biological frequencies, at least two biological frequency change trends (for example, an increasing tendency, a decreasing tendency, a constant tendency) based on at least two biological frequencies stored in the storage unit. Etc.). The frequency band may be determined in consideration of the change tendency of the biological frequency, or the weight (weight coefficient) of the first spectrum value may be determined.

  In the aspect of the invention, the weighting unit may determine the frequency band based on the determination result.

  In this way, it is possible to more accurately determine the frequency band that is assumed to exhibit the biological activity in consideration of the change tendency of the biological frequency.

In one aspect of the present invention, when the determination result indicates an increasing tendency of the at least two biological frequencies, the weighting unit includes the newest biological frequency of the at least two biological frequencies as the frequency band. In addition, at least one high frequency side higher than the newest biological frequency of the plurality of frequencies may be set,
When the determination result indicates a decreasing tendency of the at least two biological frequencies, the weighting unit includes, as the frequency band, the newest biological frequency of the at least two biological frequencies, and the frequency of the plurality of frequencies. At least one low frequency side frequency lower than the newest biological frequency may be set.

  Thus, the frequency band can be set more appropriately according to the change tendency of the biological frequency. That is, when the change tendency of the biological frequency is an increasing tendency, the next biological frequency is likely to be shifted to the higher frequency side than the previous biological frequency or the same as the previous frequency. This frequency can be set as a frequency band that is assumed to exhibit life activity. On the other hand, if the change tendency of the biological frequency is a decreasing tendency, the next biological frequency is likely to be shifted to a lower frequency side than the previous biological frequency or the same as the previous frequency, the previous frequency) and The frequency on the low frequency side can be set as a frequency band that is assumed to exhibit life activity.

  In the aspect of the invention, the weighting unit may determine the weight of the first spectrum value based on the determination result.

  As described above, the weight (weighting coefficient) of the first spectrum value can be set more appropriately according to the change tendency of the biological frequency. For example, when the change tendency of the biological frequency is an increasing tendency or a decreasing tendency, the biological frequency is distributed over a plurality of frequencies, and the spectral distribution of the biological frequency is dispersed. In such a case, the weight (weighting coefficient) of the first spectrum value may be increased to make it easier to specify the biological frequency.

  In one aspect of the present invention, the newest biological frequency among the at least one biological frequency stored in the storage unit is not separated from a frequency assumed to exhibit body movement by a given frequency band. In this case, the weighting unit may stop the weighting process, and the specifying unit may specify the biological frequency based on the plurality of spectrum values calculated by the analyzing unit.

  Thus, when the previous biological frequency (for example, the pulse frequency per second, the heartbeat frequency per second, the walking frequency per second, etc.) approaches the frequency assumed to exhibit body motion, The weighting unit can be invalidated when the biological frequency is specified. In other words, it is possible to prevent the spectrum value of the frequency assumed to exhibit body movement from being erroneously increased by the weighting unit.

In one embodiment of the present invention, the biological information processing apparatus includes:
You may further include the conversion part which converts the said biological frequency specified by the said specific part into a pulse rate or a heart rate.

  Thus, a biological information processing apparatus (a pulse meter or a heart rate meter in a narrow sense) that converts a biological frequency into a pulse rate or a heart rate [bpm] (biological information in a broad sense) can be provided.

The structural example of the biometric information processing apparatus of this embodiment. Two examples of signals generated in a pulse sensor. 3A and 3B show the results of frequency analysis of two signal examples generated in the pulse sensor. The specific structural example of the biological information processing apparatus of FIG. 5 is a flowchart illustrating an operation example of the biological information processing apparatus in FIG. 4. 6A and 6B are explanatory diagrams of weighting processing. The flowchart showing the specific example of a weighting process. FIGS. 8A and 8B are explanatory diagrams of weighting processing when the change tendency of the biological frequency shows an increasing tendency. FIG. 9A and FIG. 9B are explanatory diagrams of weighting processing when the change tendency of the biological frequency shows a decreasing tendency. 3 shows another specific configuration example of the biological information processing apparatus of FIG. 11A and 11B are explanatory diagrams of weighting processing using a signal processing unit. FIGS. 12A and 12B are explanatory diagrams of weighting processing using the signal processing unit when the change tendency of the biological frequency shows an increase tendency. FIGS. 13A and 13B are explanatory diagrams of weighting processing using the signal processing unit when the biological frequency change tendency shows a decreasing tendency. Explanatory drawing of the signal which an acquisition part acquires. FIGS. 15A and 15B are external views of electronic devices including a biological information processing apparatus.

  Hereinafter, this embodiment will be described. In addition, this embodiment demonstrated below does not unduly limit the content of this invention described in the claim. In addition, all the configurations described in the present embodiment are not necessarily essential configuration requirements of the present invention.

1. 1. Biological Information Processing Device 1.1 Basic Configuration FIG. 1 shows a configuration example of a biological information processing device of this embodiment. As illustrated in FIG. 1, the biological information processing apparatus includes an acquisition unit 210, an analysis unit 220, a weighting unit 230, and a specifying unit 240. The acquisition unit 210 acquires a signal having biological information.

  The range of the biological information includes, for example, a pulse rate, a heart rate, and a step number. A biological information measuring device that measures a pulse rate (biological information in a broad sense) can be referred to as a pulse meter, and the biological information processing device can be incorporated into a pulse meter, for example. A light-emitting element in which a pulse meter (biological information detector in a broad sense) emits light toward a detected part of a subject (user) and a light-receiving element that receives reflected light having biological information from the detected part , The acquisition unit 210 applied to the pulsometer acquires a light reception signal generated in the light receiving element. The acquisition unit 210 may be a sensor unit that generates a signal having biological information or an input unit that inputs a signal having biological information, and further includes an A / D conversion circuit that performs A / D conversion on the signal having biological information. You may have. The acquisition unit 210 can output a signal having biological information for 16 seconds (waveform data having biological information in a broad sense) to the analysis unit 220, for example.

  When the detection site (for example, blood vessel) is inside the test object, the light emitted from the light emitting element travels inside the test object and diffuses or scatters in the epidermis, dermis, and subcutaneous tissue. Thereafter, the light emitted from the light emitting element reaches the detection site and is reflected by the detection site. The reflected light at the detection site diffuses or scatters in the subcutaneous tissue, dermis and epidermis, and then travels toward the light receiving element. Note that light emitted from the light-emitting element is partially absorbed by blood vessels. Therefore, due to the influence of blood flow changes such as pulsation, the absorption rate in the blood vessels changes, and the amount of reflected light at the detection site also changes. In this way, the biological information (for example, the pulse rate) is reflected in the reflected light at the detection site, and thus in the received light signal generated in the light receiving element.

  The biological information processing apparatus acquires a light reception signal (a signal having biological information in a broad sense) generated by the light receiving element by the acquisition unit 210, and analyzes analysis or processing for extracting biological information from the signal having biological information. This is performed by the unit 220. The analysis unit 220 performs frequency analysis on a signal having biological information and calculates a plurality of spectrum values corresponding to a plurality of frequencies. The analysis unit 220 performs frequency analysis of a signal having biological information (a signal generated in a sensor element such as a light receiving element in a narrow sense) by, for example, a fast Fourier transform (a diffusion Fourier transform in a broad sense).

  Based on the result of the frequency analysis, the analysis unit 220 is a graph as shown in FIG. 7A of Patent Document 1 (the horizontal axis represents the frequency and the vertical axis represents the spectrum value corresponding to the frequency). You may represent the distribution of a spectrum. In this specification, one line represented by a specific frequency (for example, frequency f1) in FIG. 7A of Patent Document 1 is referred to as a spectrum, and each of the plurality of spectra has a horizontal axis component (frequency ) And a vertical axis component (spectral value).

  The weighting unit 230 performs a weighting process on a plurality of spectrum values obtained by the analysis unit 220 based on a frequency band that is assumed to exhibit life activity (for example, a pulse, a heartbeat, and walking). The weighting unit 230 evaluates the weight of the first spectrum value belonging to the frequency band assumed to exhibit life activity to be greater than the weight of the second spectrum value excluding the first spectrum value from the plurality of spectrum values. To do. Since the weight of the first spectrum value belonging to the frequency band assumed to exhibit a biological activity (for example, pulse, heartbeat, walking, etc.) is increased, the first spectrum value may be a body motion spectrum, a noise spectrum, or the like. Compared with the second spectral value belonging to the frequency band of, the frequency becomes relatively large.

  Here, when the weighting process of the weighting unit 230 is applied to the graph (spectral distribution) shown in FIG. 7A of Patent Document 1, the frequency f1 is set as a frequency band that is assumed to exhibit life activity. Then, the weight (weight coefficient) of the frequency f1 is set to, for example, twice, and the weight (weight coefficient) of the other frequencies is set to, for example, 1 time. When such weighting processing is performed, only the spectrum value (vertical component) of the frequency f1 in the graph shown in FIG. 7A of Patent Document 1 is doubled (not shown). When the spectrum value of the frequency f1 is doubled, for example, the graph (spectral distribution) shown in FIG. That is, the frequency f1 can be specified as the pulse frequency (biological frequency in a broad sense) only by the graph (spectral distribution) shown in FIG. 7A of Patent Document 1 to which the weighting process of the weighting unit 230 is applied. Become.

  The weighting unit 230 increases the first first spectral value belonging to the frequency band assumed to exhibit the biological activity, while the other spectral value (second second) not belonging to the frequency band assumed to exhibit the biological activity. The spectral value of The weighting unit 230 generally predicts a pulse frequency (biological frequency in a broad sense) and increases a spectrum value belonging to the predicted frequency. Using this principle, the biological information processing apparatus can easily specify the biological frequency. Although the setting method of the frequency band assumed to exhibit the biological activity will be described later, an arbitrary prediction method can be used. For example, the frequency band may be set based on the biological frequency specified in the past.

  Note that the number of first spectrum values depends on the frequency band to be predicted, and the weighting unit 230 may increase only one weight of one first spectrum value, and may include a plurality of first spectrum values. A plurality of weights may be increased. When applying the weighting process of the weighting unit 230 to the example of FIG. 7A of Patent Document 1, the spectrum value of the frequency f1 is doubled and two spectrum values adjacent to the frequency f1 (high frequency side frequency) And the spectrum value of the frequency on the low frequency side) may be doubled. That is, three frequencies (frequency f1 and two frequencies around it) may be set as the frequency band assumed to exhibit life activity.

  Based on the plurality of spectrum values after the weighting process is performed by the weighting unit 230, the specifying unit 240 determines one of the plurality of frequencies (corresponding to the horizontal axis component) obtained by the analysis unit 220 as a living body. Specify as frequency. For example, the specifying unit 240 can specify the frequency of the spectrum value that is the largest value as the biological frequency. Therefore, the specifying unit 240 easily specifies, for example, the frequency of the first spectrum value as a biological frequency (for example, the pulse frequency per second, the heartbeat frequency per second, the walking frequency per second, etc.). be able to.

  In addition, when there are a plurality of first spectrum values, the specifying unit 240 specifies, for example, the frequency of the first spectrum value, which is the largest value among the plurality of first spectrum values, as the biological frequency. Also good. When the weighting process of the weighting unit 230 and the process of the specifying unit 240 are applied to the example of FIG. 7A of Patent Document 1, spectrum values belonging to three frequencies (frequency f1 and two frequencies around it) are doubled. Even so, the spectrum value of the frequency f1 shows the largest value, and the frequency f1 can be specified as the pulse frequency (biological frequency in a broad sense).

  Various processes known to those skilled in the art at the time of the present application can be adopted as the process (identification method) of the identification unit 240. Therefore, in this specification, the detailed description of the specifying unit 240 is omitted, and only the simplest process (specifying method) will be described as an example.

  In the example of FIG. 1, the biological information processing apparatus is configured by the analysis unit 220, the weighting unit 230, and the specifying unit 240. However, the analysis unit 220, the weighting unit 230, and the specifying unit 240 may be a DSP or a gate array, for example. An ASIC can be used. Moreover, you may comprise all or one part of the analysis part 220, the weighting part 230, and the specific | specification part 240 with a computer (a device containing a process part and a memory | storage part in a broad sense). The processing unit is, for example, an MPU (Micro Processing Unit). The storage unit is a work area of the processing unit (in a narrow sense, all or part of the analysis unit 220, the weighting unit 230, and the specifying unit 240), and the storage unit is, for example, a memory or an HDD (hard disk drive). Etc. The biological information processing apparatus can include, for example, an information storage medium (a computer-readable medium) that stores programs, data, and the like. Examples of the information storage medium include a memory card and an optical disk. The processing unit can perform various processes based on an information storage medium or a program stored in the storage unit. That is, the information storage medium or the storage unit may store a program for causing the computer to function as all or part of the analysis unit 220, the weighting unit 230, and the specifying unit 240.

1.2 Background of the Invention FIG. 2 shows two signals (waveform data) generated in a pulse sensor, where a detected portion of one signal is a blood vessel of a finger, and a detected portion of another signal is The blood vessels of the wrist. As shown in FIG. 2, the level of the signal generated in the pulse sensor for the wrist blood vessel is lower than the level of the signal generated in the pulse sensor for the finger blood vessel. This is because the ratio of the artery to the vein is high near the finger, while the ratio of the artery to the vein is low near the wrist.

  Also, as shown in FIG. 2, the period of the signal generated in the pulse sensor for the wrist blood vessel is more unstable than the period of the signal generated in the pulse sensor for the finger blood vessel. This is due to the fact that the swinging of the arm associated with exercise such as walking and jogging has a greater effect on the blood flow in the blood vessels near the wrist where the ratio of arteries to veins is low as a periodic external force.

  3A and 3B show the results of frequency analysis of two signals (waveform data) generated in the pulse sensor, and FIG. 3A corresponds to the blood vessel of the finger. (B) corresponds to the blood vessel of the wrist. In the example of FIGS. 3A and 3B, the upper part shows input data (waveform data) as shown in FIG. 2, and the lower part is shown in FIG. Output data (distribution of multiple spectra). In the examples of FIGS. 3A and 3B, the input data is waveform data in the range of 0 to 16 [sec], and the output data corresponds to the frequency in the range of 0 to 4 [Hz]. Multiple spectral values.

  As shown in FIG. 3A, according to the result of the frequency analysis of the signal generated in the pulse sensor for the finger blood vessel, the spectrum value of the frequency (pulse frequency) fHR1 representing the pulse is the largest and sharp. A nice pulse spectrum appears. Further, the spectrum value of the frequency fHR2 which is twice the pulse frequency fHR1 is also larger than the adjacent spectrum value, and a sharp double pulse spectrum appears. The spectrum value of the frequency (body motion frequency) fBM1 and the spectrum value of the frequency fBM2 that is twice the body motion frequency fBM1 exhibiting the swing of the arm due to exercise such as walking and jogging are larger than the adjacent spectrum values and are clear. A body motion spectrum and a diploid body motion spectrum appear. In such a case, the pulse frequency fHR1 can be easily specified.

  As shown in FIG. 3B, according to the result of frequency analysis of the signal generated in the pulse sensor for the wrist blood vessel, the spectrum value of the body motion frequency fBM1 is the largest, and a clear body motion spectrum is obtained. Appears. Further, the spectrum value of the frequency fBM2 which is twice the body motion frequency fBM1 is also larger than the adjacent spectrum value, and a double body motion spectrum appears. However, the spectrum value of the pulse frequency fHR1 is smaller than the spectrum value of the body motion frequency fBM1 or the spectrum value of the frequency fBM2 that is twice the body motion frequency fBM1. The spectrum value of the pulse frequency fHR1 is slightly larger than the adjacent spectrum value. Therefore, according to the result of frequency analysis of the signal generated in the pulse sensor for the wrist blood vessel, noise including body motion noise corresponding to the frequency fBM1 and the frequency fBM2 (corresponding to other frequencies excluding the pulse frequency fHR1). Noise) is dominant.

  In the example of FIG. 3B, even if body motion noise is removed or reduced, a clear pulse spectrum does not appear. In such a case, it is difficult to specify the pulse frequency fHR1. In other words, the frequency fHR1 may be specified as the pulse frequency, or the frequency fN1 or fN2 presenting noise may be erroneously specified as the pulse frequency.

  Further, as in the example of FIG. 7A of Patent Document 1, the spectrum value of the frequency f1 is not always large, and there is a large individual difference in the blood vessel structure of the wrist, and the spectrum value of the frequency f1 is The present inventor has recognized that it becomes smaller as in the example of FIG. 3B accompanying the present specification. As a result of considering the above circumstances, the present inventor has recognized that the pulse frequency fHR1 can be easily specified by increasing the spectrum value of the pulse frequency fHR1 of FIG.

1.3 First Configuration Example FIG. 4 shows a specific configuration example of the biological information processing apparatus of FIG. In the example of FIG. 4, the weighting unit 230 is embodied, but a specific configuration example of the biological information processing apparatus is not limited to FIG. Moreover, the same code | symbol is attached | subjected about the structure same as the structural example mentioned above, and the description is abbreviate | omitted. In addition, in the example of FIG. 4, the biological information processing apparatus includes a storage unit 250. The storage unit 250 is, for example, a memory, an HDD (hard disk drive), or the like, and can also be called a work area of the specifying unit 240. Further, as described above, the storage unit 250 may also include all or part of the work area functions of the analysis unit 220 and the weighting unit 230.

  In the example of FIG. 4, the storage unit 250 stores the biological frequency specified by the specifying unit 240. The memory | storage part 250 may memorize | store the biometric frequency log | history by continuing the memory | storage of all or one part of the biofrequency specified in the past. In the example of FIG. 4, the storage unit 250 stores at least one biological frequency specified in the past by the specifying unit 240, and the weighting unit 230 reflects at least one biological frequency in the content or method of the weighting process. Can do.

  Specifically, based on one biological frequency stored in the storage unit 250, the weighting unit 230 (in a narrow sense, the determination unit 232) may determine a frequency band that is assumed to exhibit biological activity. Further, based on one biological frequency stored in the storage unit 250, the weighting unit 230 (in the narrow sense, the determination unit 232) may determine the weight (weighting coefficient) of the first spectrum value. In addition, based on one biological frequency stored in the storage unit 250, the weighting unit 230 (in the narrow sense, the determination unit 232) determines whether or not to stop the weighting process, that is, the frequency band determination unit 234 and the weighting factor increase. Whether to invalidate the function of the unit 236 may be determined.

  The weighting unit 230 (decision unit 232 in a narrow sense) can perform not only the above-described determination process but also other determination processes. The acquisition unit 210, the analysis unit 220, and the specification unit 240 (biological information processing device in a broad sense) can perform various determination processes as necessary.

1.4 First Operation Example FIG. 5 is a flowchart showing an operation example of the biological information processing apparatus of FIG. Hereinafter, an operation example of the biological information processing apparatus will be described with reference to FIG. 5 and the like, but the operation example of the biological information processing apparatus is not limited to FIG. 4 and FIG. Also, some of the operations described below can be omitted, and other operations can be added to the operations described below.

  In the example of FIG. 5, the acquisition unit 210 determines whether or not a signal having biological information for 16 seconds (in a narrow sense, waveform data having biological information) has been acquired (step S11). In order for the analysis unit 220 to perform frequency analysis on a signal having biological information, a signal having biological information for a given period is required. The given period can be determined by the sampling frequency and the number of sampling points in step S12 described later. For example, if the sampling frequency is 16 [Hz] and the number of sampling points is 256, the predetermined period is the number of sampling points / sampling frequency = 256/16 = 16 [sec].

  In the example of FIG. 5, for example, when a signal having biological information for 16 seconds has not been acquired, the acquisition unit 210 waits for the passage of time until a signal having biological information for 16 seconds can be acquired (step S <b> 11). ). When receiving the signal having biological information for 16 seconds, the analysis unit 220 performs frequency analysis on the signal (waveform data) having biological information for 16 seconds (step S12). The analysis unit 220 obtains the result of frequency analysis (a plurality of spectrum values corresponding to frequencies in the range of 0 to 4 [Hz]) as shown in FIG. 3B, for example.

  In the example of FIG. 5, the weighting unit 230 (decision unit 232 in a narrow sense) determines whether or not the immediately preceding biological frequency is separated from the body motion frequency (step S13). Here, it is assumed that the storage unit 250 stores at least one biological frequency. When a plurality of biological frequencies are stored in the storage unit 250, the weighting unit 230 (in a narrow sense, the determination unit 232) indicates that the latest biological frequency among the plurality of biological frequencies stored in the storage unit 250 is the body motion. It is determined whether or not it is away from the frequency by a given frequency band (step S13).

  As described above, the weighting unit 230 increases the spectrum value of the pulse frequency fHR1 in FIG. 3B, and the specifying unit 240 easily specifies the pulse frequency fHR1 (biological frequency in a broad sense). Can do. However, if the weighting unit 230 erroneously increases the spectrum value of the body motion frequency fBM1 in FIG. 3B, the specifying unit 240 erroneously sets the body motion frequency fBM1 to a pulse frequency (in a broad sense, a biological frequency). Will be specified as. Therefore, step S13 can be executed in order to avoid such an erroneous process.

  Here, it is assumed that the result of frequency analysis (a plurality of spectrum values corresponding to frequencies in the range of 0 to 4 [Hz]) shown in FIG. 3B is the result of the previous frequency analysis. In this case, the result of the next frequency analysis (the result of the current frequency analysis performed in step S12) is the current pulse frequency (biological frequency in a broad sense) is the pulse frequency fHR1 (in a broad sense) shown in FIG. Is expected to exist in the vicinity of the immediately preceding biological frequency). Further, the current body motion frequency is expected to be present in the vicinity of the body motion frequency fBM1 (immediate body motion frequency) shown in FIG. Here, it is assumed that the current body motion frequency matches the body motion frequency fBM1 (immediate body motion frequency) shown in FIG. In this case, the weighting unit 230 (in the narrow sense, the determination unit 232) determines that the immediately preceding biological frequency (the pulse frequency fHR1 illustrated in FIG. 3B) is the current body motion frequency (the body motion illustrated in FIG. 3B). It is determined whether or not the frequency fBM1) is more than ± 3 spectra, for example (step S13). Considering the relationship shown in the example of FIG. 3B, the frequency fHR1 is separated from the frequency fBM1 by nine spectra, so that step S14 can be performed.

  On the other hand, as a result of performing Step S13, if the immediately preceding biological frequency is not separated from the current body motion frequency by more than ± 3 spectra, for example, Step S14 may be performed without performing Step S14. it can. That is, the weighting unit 230 stops the weighting process in step S14, and the specifying unit 240 specifies the biological frequency based on the result of the current frequency analysis performed in step S12 (step S15). Thus, when the immediately preceding biological frequency is close to the body motion frequency due to the presence of step S13, the execution of step S14 can be avoided.

  In the example of FIG. 5, the weighting unit 230 (in the narrow sense, the determination unit 232, the frequency band determination unit 234, and the weighting factor increase unit 236) performs weighting processing based on the history of past biological frequencies (step S14). Here, it is assumed that the storage unit 250 stores at least one biological frequency. When a plurality of biological frequencies are stored in the storage unit 250, the weighting unit 230 (in a narrow sense, the determination unit 232) can determine a change tendency of at least two biological frequencies, and the determination result is used as a weighting process. It can be reflected. That is, when a plurality of biological frequencies are stored in the storage unit 250, a plurality of weighting processing methods can be prepared, and an appropriate weighting processing method can be selected in accordance with the change tendency of the biological frequency. When only one biological frequency is stored in the storage unit 250, one weighting processing method may be adopted regardless of the change tendency of the biological frequency. Even if a plurality of biological frequencies are stored in the storage unit 250, one weighting processing method may be adopted regardless of the tendency of the biological frequency to change.

  6A and 6B are diagrams for explaining the weighting process, and FIG. 6A shows an example of a result of the current frequency analysis in which step S12 of FIG. 5 is performed, FIG. 6B shows an example of the result of the increased frequency analysis performed in step S14 of FIG. In FIG. 6A, five representative spectra are shown at frequencies f15, f21, f29, f44 and f59. The result of the frequency analysis indicates a frequency in the range of, for example, 0 to 4 [Hz]. For example, if the sampling frequency is 16 [Hz] and the number of sampling points is 256, the frequency resolution is the sampling frequency / number of sampling points. = 16/256 = 0.0625 [Hz]. In other words, one spectrum has a width of 0.0625 [Hz]. Here, it is assumed that the frequency f21 (21st spectrum) indicates the immediately preceding biological frequency. The weighting unit 230 (in a narrow sense, the frequency band determining unit 234) determines the spectrum of the 21st spectrum (immediately before the biological frequency f21) ±, for example, one spectrum as the frequency band assumed to exhibit the biological activity ( Step S14 in FIG. That is, the weighting unit 230 (in a narrow sense, the frequency band determining unit 234) determines the frequency band from the 20th spectrum to the 22nd spectrum.

  Next, the weighting unit 230 (in a narrow sense, the weighting factor increasing unit 236) sets the weight (weighting factor) of the first spectrum value belonging to the frequency band (frequency f20 to f22) to, for example, “5”, As shown in FIG. 6B, the first spectrum value is increased five times (step S14 in FIG. 5). The weight (weight coefficient) of the second spectrum value that does not belong to the frequency band (frequencies f20 to f22) remains, for example, “1” (step S14 in FIG. 5).

  As described in the examples of FIGS. 6A and 6B, the weighting processing method for determining the last biological frequency ± for example, one spectrum is independent of the change tendency of the biological frequency. It can apply to the result of the present frequency analysis which implemented step S12 of (step S14). Note that a spectrum corresponding to ± 2 biological frequencies immediately before may be predicted as a frequency band assumed to exhibit biological activity (step S14).

  In step S14 in the example of FIG. 5, one weighting processing method may be adopted regardless of the change tendency of the biological frequency. Alternatively, one weighting processing method may be selected from a plurality of weighting processing methods in accordance with the change tendency of the biological frequency. Below, the example which considers the change tendency of a biological frequency is demonstrated.

  FIG. 7 is a flowchart showing a specific example of step S14 in FIG. In the example of FIG. 7, the weighting unit 230 (decision unit 232 in a narrow sense) determines a change tendency of at least two biological frequencies based on at least two biological frequencies stored in the storage unit 250, and the determination result Is obtained (step S21).

  Here, it is assumed that the change tendency of the biological frequency is determined based on the newest biological frequency and the second newest biological frequency among the biological frequencies stored in the storage unit 250. For example, when the second newest biological frequency is the 21st spectrum as a result of the frequency analysis as shown in FIG. 6A, and the newest biological frequency is also the 21st spectrum, the change tendency of the biological frequency Is a certain trend. For example, when the second newest biological frequency is the 20th spectrum and the newest biological frequency is the 21st spectrum, the changing tendency of the biological frequency is increasing. For example, when the second newest biological frequency is the 22nd spectrum and the newest biological frequency is the 21st spectrum, the changing tendency of the biological frequency is decreasing.

  Further, here, it is assumed that the trend of change in the biological frequency is determined based on the newest biological frequency, the second newest biological frequency, and the third newest biological frequency among the biological frequencies stored in the storage unit 250. You can also For example, when the second newest biological frequency is higher than the third newest biological frequency and the newest biological frequency is higher than the second newest biological frequency, the changing tendency of the biological frequency is increasing. For example, when the second newest biological frequency is lower than the third newest biological frequency and the newest biological frequency is lower than the second newest biological frequency, the changing tendency of the biological frequency is decreasing. For example, in other cases, the changing tendency of the biological frequency is a constant tendency.

  In the example of FIG. 7, based on the determination result of step S21, the weighting unit 230 (in a narrow sense, the frequency band determining unit 234) determines a frequency band that is assumed to exhibit life activity (step S22). If the change tendency of the biological frequency is a constant tendency, for example, a frequency band (a spectrum corresponding to the previous biological frequency ± 1) as shown in FIG. 6B is determined. If the change tendency of the biological frequency is an increasing tendency, for example, a spectrum corresponding to +2 biological frequencies immediately before is determined as a frequency band assumed to exhibit biological activity. If the change tendency of the biological frequency is a decreasing tendency, for example, a spectrum corresponding to -2 biological frequencies immediately before is determined as a frequency band assumed to exhibit biological activity.

  8A and 8B are diagrams for explaining the weighting process when the change tendency of the biological frequency shows an increase tendency, and FIG. 8A performs Step S12 of FIG. FIG. 8B shows an example of the result of the increased frequency analysis performed in steps S22 and S23 of FIG. 7 (step S14 of FIG. 5). In FIG. 8A, three representative spectra are shown at frequencies f23, f28 and f45. Here, it is assumed that the 27th spectrum indicates the immediately preceding biological frequency. If the change tendency of the biological frequency is an increasing tendency, for example, as a frequency band assumed to exhibit biological activity, a frequency band as shown in FIG. 8B (27th spectrum (immediate biological frequency f27) to 29th spectrum) is determined (step S22 in FIG. 7).

  9A and 9B are diagrams for explaining the weighting process when the change tendency of the biological frequency shows a decreasing tendency, and FIG. 9A performs Step S12 of FIG. 9B shows an example of the result of the current frequency analysis, and FIG. 9B shows an example of the result of the increased frequency analysis in which steps S22 and S23 of FIG. 7 (step S14 of FIG. 5) are performed. In FIG. 9A, five typical spectra are shown at frequencies f14, f25, f29, f43 and f58. Here, it is assumed that the 26th spectrum indicates the immediately preceding biological frequency. If the change tendency of the biological frequency is a decreasing tendency, for example, as a frequency band assumed to exhibit a biological activity, a frequency band (24th spectrum to 26th spectrum (the immediately preceding spectrum) as shown in FIG. 9B) is used. The biological frequency f26) is determined (step S22 in FIG. 7).

  In the example of FIG. 7, based on the determination result of step S21, the weighting unit 230 (in a narrow sense, the weighting factor increasing unit 236) weights the first spectral value belonging to the frequency band assumed to exhibit biological activity ( (Weighting coefficient) is increased (step S23). If the change tendency of the biological frequency is constant, for example, as shown in FIG. 6B, the first spectrum value belonging to the frequency band (frequency f20 to f22) is increased five times. If the change tendency of the biological frequency is an increasing tendency, for example, as shown in FIG. 8B, the first spectrum value belonging to the frequency band (frequency f27 to f29) is multiplied by 5 × 1.5 = 7.5 times. To increase. That is, if the change tendency of the biological frequency is an increasing tendency, the change tendency of the biological frequency is further increased from 5 times that is a constant tendency. If the change tendency of the biological frequency is a decreasing tendency, for example, as shown in FIG. 9B, the first spectrum value belonging to the frequency band (frequency f24 to f26) is 5 × 1.5 = 7.5 times. To increase. That is, if the change tendency of the biological frequency is a decreasing tendency, the change tendency of the biological frequency is further increased from 5 times that is a constant tendency.

  Note that step S22 in FIG. 7 may be modified. In other words, regardless of the determination result of step S21, the weighting unit 230 (in a narrow sense, the frequency band determination unit 234) always uses, for example, FIG. 6B as a frequency band assumed to exhibit a biological activity. A frequency band (a spectrum corresponding to the immediately preceding biological frequency ± 1) may be determined. Even in such a case, if the change tendency of the biological frequency is an increasing tendency, for example, the weighting unit 230 (in a narrow sense, the weighting factor increasing unit 236), the example of FIG. You may change to The first spectrum value belonging to the frequencies f26 and f27 may be increased five times, and the first spectrum value belonging to the frequency f28 may be increased 5 × 1.5 = 7.5 times (step S23). Further, if the change tendency of the biological frequency is a decreasing tendency, for example, the weighting unit 230 (in a narrow sense, the weighting factor increasing unit 236) may change the example of FIG. 9B as follows. The first spectrum value belonging to the frequency f25 may be increased 5 × 1.5 = 7.5 times, and the first spectrum value belonging to the frequencies f26 and f27 may be increased five times (step S23).

  Further, step S23 in FIG. 7 may be modified. In other words, regardless of the determination result of step S21, the weighting unit 230 (in a narrow sense, the weighting factor increasing unit 236) always uses the first spectrum value belonging to the frequency band assumed to exhibit biological activity, for example, You may increase 5 times. If the change tendency of the biological frequency is an increasing tendency, as shown in FIG. 8B, for example, a frequency band (frequency f27 to f29) is set in step S23, and then the frequency band (frequency f27 to f29) is set. The first spectral value belonging to may be increased by a factor of five. If the change tendency of the biological frequency is a decreasing tendency, for example, as shown in FIG. 9B, a frequency band (frequency f24 to f26) is set in step S23, and then the frequency band (frequency f24 to f26) is set. The first spectral value belonging to f26) may be increased by a factor of five.

  As described above, step S14 of FIG. 5 can also implement steps S22 and S23 of FIG. 7, and can also perform modifications of steps S22 and S23 of FIG. Although various methods can be used as the method of implementing step S14 in FIG. 5, the main points of step S22 will be described below.

  When the increase of at least two biological frequencies stored in the storage unit 250 is indicated by the execution of step S21, the frequency band determined by the frequency band determination unit 234 is the newest biological frequency of at least two biological frequencies. (Step S22). In addition, this frequency band is at least one higher than the newest biological frequency among a plurality of frequencies (for example, a range of 0 to 4 [Hz]) as a result of the current frequency analysis performed in step S12 of FIG. The frequency on the high frequency side is included (step S22).

  When the reduction frequency of at least two biological frequencies stored in the storage unit 250 is shown by performing step S21, the frequency band determined by the frequency band determination unit 234 is the newest biological frequency of at least two biological frequencies. (Step S22). In addition, this frequency band is at least one lower than the newest biological frequency among a plurality of frequencies (for example, a range of 0 to 4 [Hz]) as a result of the current frequency analysis performed in step S12 of FIG. The frequency on the high frequency side is included (step S22).

  Thus, the frequency band can be set more appropriately according to the change tendency of the biological frequency. That is, when the change tendency of the biological frequency is an increasing tendency, the next biological frequency is likely to be shifted to the higher frequency side than the previous biological frequency or the same as the previous frequency. This frequency can be set as a frequency band that is assumed to exhibit life activity. On the other hand, if the change tendency of the biological frequency is a decreasing tendency, the next biological frequency is likely to be shifted to a lower frequency side than the previous biological frequency or the same as the previous frequency, the previous frequency) and The frequency on the low frequency side can be set as a frequency band that is assumed to exhibit life activity.

  In the example of FIG. 5, the specifying unit 240 specifies the current biological frequency (step S15). For example, in the example of FIG. 6B, in the state where the frequency f21 (the 21st spectrum) indicates the immediately preceding biological frequency, the specifying unit 240 sets the frequency of the spectrum value that is the largest value as the current biological frequency. f21 is specified (step S15). For example, in the example of FIG. 8B, in the state where the frequency f27 (the 27th spectrum) indicates the immediately preceding biological frequency, the specifying unit 240 sets the frequency of the spectrum value that is the largest value as the current biological frequency. f28 is specified (step S15). For example, in the example of FIG. 9B, in the state where the frequency f26 (the 26th spectrum) indicates the immediately preceding biological frequency, the specifying unit 240 sets the frequency of the spectrum value that is the largest value as the current biological frequency. f25 is specified (step S15).

  In the example of FIG. 5, the storage unit 250 updates the history of the biological frequency (step S16). Specifically, the storage unit 250 stores the biological frequency specified in step S15, and the most recently stored biological frequency becomes the immediately preceding biological frequency.

  In the example of FIG. 5, the biological information processing apparatus determines whether to stop the processes in steps S11 to S16 (step S17). For example, when the user presses a stop button (not shown), the biological information processing apparatus stops the processes in steps S11 to S16. In other words, the biological information processing apparatus repeats the processes of steps S11 to S16 until a stop button (not shown) is pressed by the user. Alternatively, the biological information processing apparatus may repeat the processes of steps S11 to S16 for, for example, 6 minutes (given period in a broad sense), and after steps S11 to S16 have elapsed after the given period. The process may be automatically canceled.

1.5 Second Configuration Example FIG. 10 shows another specific configuration example of the biological information processing apparatus of FIG. In the example of FIG. 10, the weighting unit 230 is embodied as in the example of FIG. 4, but a specific configuration example of the biological information processing apparatus is not limited to FIG. 10. Moreover, the same code | symbol is attached | subjected about the structure same as the structural example mentioned above, and the description is abbreviate | omitted. In addition, in the example of FIG. 10, the biological information processing apparatus includes an additional configuration such as a conversion unit 260. The biological information processing apparatus may omit a part of the additional configuration. The acquisition unit 210 and the analysis unit 220 in FIG. 1 are referred to as a first acquisition unit and a first analysis unit, respectively, in the example of FIG.

  In the second configuration example shown in FIG. 10, as an additional configuration, for example, a first sensor unit 200 and a second sensor unit 300 are also included, and two sensors (for example, a combination of a pulse sensor and an acceleration sensor) are included. Etc.). In the second configuration example, a second acquisition unit 310 and a second analysis unit 320 corresponding to the second sensor unit 300 can also be included. Although a detailed description of these additional configurations will be described later, the presence of the second sensor unit 300 can identify a body motion spectrum (noise in a broad sense) and remove or reduce it. Thereby, the specific | specification part 240 can specify a biological frequency more correctly.

  In the example of FIG. 10, the biological information processing apparatus includes a conversion unit 260 that converts the biological frequency specified by the specifying unit 240 into a pulse rate or a heart rate (biological information in a broad sense). As described above, the frequency resolution in the example of FIG. 6B is, for example, sampling frequency / number of sampling points = 16/256 = 0.0625 [Hz]. The pulse rate or heart rate is generally represented by the number of beats per minute [bpm]. Therefore, the conversion unit 260 increases the biological frequency specified by the specifying unit 240, for example, 60 times. Specifically, when the 21st spectrum is the current biological frequency, the conversion unit 260 calculates 21 × 0.0625 × 60 = 78.75 [bpm as the pulse rate or heart rate based on the biological frequency f21. ] Is calculated. Note that the conversion unit 260 may round off the pulse rate or a number (fractional number) after the decimal point of the heart rate. Alternatively, if the fractional value is less than 0.5, the conversion unit 260 may round down the figure. .

  Note that the conversion unit 260 may calculate, for example, the number of steps as the biological information. The number of steps is generally represented by the total number of steps in the measurement period. For example, when the step frequency is specified based on the signal for 16 seconds and the measurement period is 16 × N [sec], the conversion unit 260 may, for example, (first step frequency + second time) as the number of steps in the measurement period. Step frequency +... + Nth step frequency) × 16. When the conversion unit 260 calculates the number of steps, the biological information processing apparatus can be called a pedometer, and when the conversion unit 260 calculates the pulse rate or heart rate, the biological information processing apparatus is called a pulse meter or heart rate monitor. be able to.

  As shown in the example of FIG. 10, the biological information processing apparatus can include a display unit 270 that displays the pulse rate or heart rate (biological information in a broad sense) converted by the conversion unit 260. The display unit 270 can be configured by a liquid crystal panel, an LED panel, or the like, for example. The pulse rate or heart rate (biological information in a broad sense) converted by the conversion unit 260 may be stored in the storage unit 250, and the pulse rate or heart rate (in a broad sense) stored in the storage unit 250. , Biological information) may be read by an external device (not shown).

  As illustrated in the example of FIG. 10, the biological information processing apparatus can include an input unit 280 configured with, for example, operation buttons, a touch panel, and the like. The input unit 280 inputs user operation information. When the biometric information processing apparatus includes, for example, operation buttons such as an effective button and an invalid button as the input unit 280, the process of the biometric information processing apparatus (for example, the processing of the weighting unit 230) is performed when the user presses the effective button. Can be activated. Further, when the user presses the invalid button, the process of the biological information processing apparatus (for example, the process of the weighting unit 230) can be invalidated.

  As shown in the example of FIG. 10, the biological information processing apparatus can include a signal processing unit 290. For example, as shown in FIG. 6A, the spectrum distribution includes not only the pulse spectrum (frequency f21) but also the body motion spectrum (frequency f15), diploid motion spectrum (frequency f29), and triploid which are noises. A dynamic spectrum (frequency f44) and a tetraploid dynamic spectrum (frequency f59) are included. Therefore, the biological information processing apparatus can remove or reduce the body motion spectrum by including the signal processing unit 290.

  The signal processing unit 290 can be configured by an adaptive filter such as an FIR filter, for example. The signal processing unit 290 inputs the first signal acquired by the first acquisition unit 210 and the second signal acquired by the second acquisition unit 310 to an adaptive filter, and a filter in which noise is removed or reduced Generate an output signal. 5, the first analysis unit 220 in FIG. 10 can perform frequency analysis on the filter output signal from the signal processing unit 290.

  FIG. 11A and FIG. 11B are diagrams for describing weighting processing using the signal processing unit 290 of FIG. FIG. 11A shows an example of the result of the current frequency analysis in which step S12 of FIG. 5 using the signal processing unit 290 is performed, while FIG. 6A does not use the signal processing unit 290. An example of the result of the current frequency analysis in which step S12 of FIG. FIG. 11B shows an example of the result of the increased frequency analysis in which step S14 of FIG. 5 using the signal processing unit 290 is performed, while FIG. 6B does not use the signal processing unit 290. 5 shows an example of the result of the increased frequency analysis in which step S14 of 5 is performed.

  As shown in FIG. 11A, the spectrum value of the frequency f15 (body motion spectrum) is greatly reduced by the signal processing unit 290. In the example of FIG. 11B, the first spectrum value belonging to the frequency band (frequencies f20 to f22) is increased, for example, twice.

  FIGS. 12A and 12B are diagrams for explaining the weighting process using the signal processing unit 290 of FIG. 10 when the change tendency of the biological frequency shows an increasing tendency. 12A shows an example of the result of the current frequency analysis in which step S12 of FIG. 5 using the signal processing unit 290 is performed, while FIG. 8A does not use the signal processing unit 290. An example of the result of the current frequency analysis in which step S12 of FIG. FIG. 12B shows an example of the result of the increased frequency analysis in which step S14 of FIG. 5 using the signal processing unit 290 is performed, while FIG. 8B does not use the signal processing unit 290. 5 shows an example of the result of the increased frequency analysis in which step S14 of 5 is performed.

  As shown in FIG. 12A, the spectrum value of the frequency f23 (body motion spectrum) is greatly reduced by the signal processing unit 290. In the example of FIG. 12B, the first spectrum value belonging to the frequency band (frequencies f27 to f29) is increased by 2 × 1.5 = 3 times, for example.

  FIGS. 13A and 13B are diagrams for explaining the weighting process using the signal processing unit 290 of FIG. 10 when the change tendency of the biological frequency shows a decreasing tendency. FIG. 13A shows an example of the result of the current frequency analysis in which step S12 of FIG. 5 using the signal processing unit 290 is performed, while FIG. 9A does not use the signal processing unit 290. An example of the result of the current frequency analysis in which step S12 of FIG. FIG. 13B shows an example of the result of the increased frequency analysis in which step S14 of FIG. 5 using the signal processing unit 290 is performed, while FIG. 9B does not use the signal processing unit 290. 5 shows an example of the result of the increased frequency analysis in which step S14 of 5 is performed.

  As shown in FIG. 13A, the spectrum value of the frequency f14 (body motion spectrum) is greatly reduced by the signal processing unit 290. In the example of FIG. 13B, the first spectrum value belonging to the frequency band (frequencies f24 to f26) is increased by 2 × 1.5 = 3 times, for example.

  FIG. 14 is an explanatory diagram of signals acquired by the first acquisition unit 210. The first acquisition unit 210 acquires, for example, a signal having biological information for 16 seconds (waveform data having pulse information in a broad sense). As illustrated in FIG. 14, the first acquisition unit 210 acquires the first waveform data in the range of 0 to 16 [sec], and then captures the second to Mth waveform data every 4 seconds. it can. When a plurality of adjacent waveform data (for example, the first waveform data and the second waveform data) have common data (for example, waveform data of 4 to 16 [sec]), for example, the pulse rate is changed every 4 seconds. It can be measured. The second acquisition unit 310 can also acquire a signal for 16 seconds, for example, every 4 seconds.

  As shown in FIG. 14, when a plurality of adjacent waveform data have common data, the pulse spectrum obtained by the analysis unit 220 may not be a clear spectrum. For example, if the user starts jogging and the pulse rate or heart rate is rising, the pulse frequency will also increase. Therefore, when the pulse frequency (biological frequency in a broad sense) shows an increasing tendency, the pulse spectrum obtained by the analysis unit 220 may be dispersed into, for example, two spectra. When the pulse spectrum is dispersed into a plurality of spectra, each of the plurality of spectra may have a small spectral value. In such a case, it is difficult for the specifying unit 240 to specify the pulse spectrum. In order to avoid this, in step S23 of FIG. 7, the weight of the first spectral value belonging to the frequency band assumed to exhibit the biological activity according to the change tendency of the pulse frequency (biological frequency in a broad sense). The magnification of (weighting factor) can be changed. As described above, the weight (weighting factor) of the first spectrum value when the change tendency of the biological frequency shows an increase tendency or a decrease tendency is the first spectrum value when the change tendency of the biological frequency shows a constant tendency. For example, 1.5 times the weight (weighting factor).

  As shown in the example of FIG. 10, the biological information processing apparatus can include a first sensor unit 200. The first sensor unit 200 can be configured with a biological sensor such as a pulse sensor. In addition, the biological information processing apparatus can include the second sensor unit 300. The second sensor unit 300 can be configured by a body motion sensor such as an acceleration sensor that detects acceleration of three axes (X axis, Y axis, and Z axis), for example. The second acquisition unit 310 synchronizes with the acquisition timing of the pulse signal (first signal) of the first acquisition unit 210, for example, a body motion signal (second signal) such as an acceleration signal for 16 seconds. Can be acquired.

  A body motion signal (second signal) such as an acceleration signal acquired by the second acquisition unit 310 can be used not only by the signal processing unit 290 but also by the second analysis unit 320. The second analysis unit 320 performs frequency analysis on the body motion signal. The second analysis unit 320 performs frequency analysis on a signal having body motion information (for example, an acceleration signal generated in the acceleration sensor) by, for example, fast Fourier transform (diffusion Fourier transform in a broad sense). Thereby, the 2nd analysis part 320 can calculate a body motion spectrum. The body motion spectrum can be used in step S13 of FIG.

2 Electronic equipment A biological information measuring device (biological information processing device in a broad sense) such as a pulsometer may be incorporated in an electronic device such as a clock, a mobile phone, a pager, a personal computer, or combined with an electronic device Good. A part of the biological information processing device, for example, the first analysis unit 220, the second analysis unit 320, the weighting unit 230, the specifying unit 240, the storage unit 250, the conversion unit 260, and the like of FIG. You may comprise with the MPU (Micro Processing Unit) of the electronic device to incorporate.

  15A and 15B are external views of a wristwatch (electronic device in a broad sense) including the biological information processing apparatus of FIG. As shown in FIG. 15A, a wristwatch (in a broad sense, a wrist-worn biological information processing device) is a list that can attach a wristwatch to an arm (a wrist in a narrow sense) of a subject (user). A band 150 may further be included. In the example of FIG. 15A, the biological information is a pulse rate, for example, “72”. The wristwatch also indicates the time (for example, 8:15 am). Further, as shown in FIG. 15B, for example, an opening is provided in the back cover of the wristwatch, and the opening corresponds to, for example, the first sensor unit 200 (in a narrow sense, a pulse sensor) in FIG. In the example of FIG. 15B, the wristband 150 and the like are omitted.

  Although the present embodiment has been described in detail as described above, it will be easily understood by those skilled in the art that many modifications can be made without departing from the novel matters and effects of the present invention. Accordingly, all such modifications are intended to be included in the scope of the present invention. For example, a term described with a different term having a broader meaning or the same meaning at least once in the specification or the drawings can be replaced with the different term in any part of the specification or the drawings.

150 wristbands, 200 first sensor section,
210 acquisition unit (first acquisition unit), 220 analysis unit (first analysis unit),
230 weighting unit, 232 determination unit, 234 frequency band determination unit,
236 weight coefficient increasing unit, 240 specifying unit, 250 storage unit, 260 conversion unit,
270 display unit, 280 input unit, 290 signal processing unit,
300 second sensor unit, 310 second acquisition unit, 320 second analysis unit

Claims (8)

An acquisition unit for acquiring a signal having biological information;
Analyzing the frequency of the signal and calculating a plurality of spectral values corresponding to a plurality of frequencies;
A weighting unit for performing a weighting process on the plurality of spectrum values based on a frequency band assumed to exhibit a biological activity;
A specifying unit that specifies one of the plurality of frequencies as a biological frequency based on the plurality of spectrum values after the weighting process is performed by the weighting unit;
The weighting unit evaluates the weight of the first spectrum value belonging to the frequency band to be larger than the weight of the second spectrum value excluding the first spectrum value from the plurality of spectrum values. Living body information processing apparatus. In claim 1,
The biological information processing apparatus further comprising a storage unit that stores at least one biological frequency specified in the past by the specifying unit. In claim 2,
The storage unit stores at least two biological frequencies,
The biological information processing apparatus, wherein the weighting unit determines a change tendency of the at least two biological frequencies based on the at least two biological frequencies stored in the storage unit, and obtains a determination result thereof. In claim 3,
The biological information processing apparatus, wherein the weighting unit determines the frequency band based on the determination result. In claim 4,
When the determination result indicates an increasing tendency of the at least two biological frequencies, the weighting unit includes, as the frequency band, the newest biological frequency of the at least two biological frequencies and the plurality of frequencies. Setting at least one frequency on the high frequency side higher than the newest biological frequency;
When the determination result indicates a decreasing tendency of the at least two biological frequencies, the weighting unit includes, as the frequency band, the newest biological frequency of the at least two biological frequencies, and the frequency of the plurality of frequencies. A biological information processing apparatus, wherein at least one low frequency side frequency lower than the newest biological frequency is set. In claim 3,
The biological information processing apparatus, wherein the weighting unit determines a weight of the first spectrum value based on the determination result. In claim 2,
When the newest biological frequency among the at least one biological frequency stored in the storage unit is not separated from a frequency assumed to exhibit body movement by a given frequency band, the weighting unit The biological information processing apparatus characterized in that the execution of the process is stopped, and the identification unit identifies the biological frequency based on the plurality of spectrum values calculated by the analysis unit. In claims 1 to 7,
The biological information processing apparatus further comprising a conversion unit that converts the biological frequency specified by the specifying unit into a pulse rate or a heart rate.

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