BIOLOGICAL BODY STATE ESTIMATION DEVICE AND COMPUTER PROGRAM

• US 20130225940A1
• Filed: 10/28/2011
• Published: 08/29/2013
• Est. Priority Date: 10/29/2010
• Status: Active Grant

• Current Assignee: Delta Tooling Co., Ltd. (Delta Kogyo Company Limited)
• Original Assignee: Delta Tooling Co., Ltd. (Delta Kogyo Company Limited)
• Inventors: Fujita, Etsunori, Ogura, Yumi, Nobuhiro, Yoshika
• Granted Patent: US 9,622,708 B2
• Time in Patent Office: Days
• US Class Current: 600/300
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/18 for vehicle drivers or machine operators
• CPC Class Codes: A61B 5/6893 Cars
• CPC Class Codes: A61B 5/7235 Details of waveform analysis A61B5/349 takes precedence

Abstract

A technique for grasping a state of a human being. The technique determines a time-series waveform of a frequency from a time-series waveform of a biological signal acquired from an upper body of a human being, and determines time-series waveforms of a frequency slope and frequency variation to analyze these frequencies. Upon analyzing the frequencies, it determines power spectrums of frequencies corresponding to a preset functional adjustment signal, fatigue reception signal, and activity adjustment signal, and then determines a state of the human being from a time-series change in each power spectrum. Dominant degrees of the functional adjustment signal and activity adjustment signal are compared as distribution rates thereof, in addition to a degree of progress of fatigue, to determine a state of the human being, for example a relaxed state, fatigued state, prominent state of sympathetic nervous, prominent state of parasympathetic nervous.

Claims

1. A biological body state estimation device which acquires a biological signal from an upper body of the human being and estimates a state of a human being by using the biological signal, comprising:

frequency calculating means for determining a time-series waveform of a frequency from a time-series waveform of a biological signal acquired by the biological signal measuring means;

frequency slope time-series analysis calculating means for subjecting the time-series waveform of the frequency of the biological signal acquired by the frequency calculating means to movement calculation for determining a slope of the frequency at each predetermined time window set with a predetermined overlap time, and for outputting a time-series change in the slope of the frequency acquired at each time window as a frequency slope time-series waveform;

spectrum time-series change calculating means for analyzing a frequency of the frequency slope time-series waveform acquired by the frequency slope time-series analysis calculating means, and for determining a time-series change in a power spectrum;

distribution rate waveform calculating means for extracting frequency components corresponding to a preset functional adjustment signal, fatigue reception signal and activity adjustment signal from the time-series change in the power spectrum acquired by the spectrum time-series change calculating means, for calculating proportions of the three frequency components in time sequence when a sum of power spectrums of the three frequency components is set to 100, and for determining the proportions as distribution rate waveforms; and

determining means for locating a waveform change pattern of the three frequency components in the distribution rate waveforms acquired by the distribution rate waveform calculating means, and for determining a state of a human being by comparing the located waveform change pattern with correlative data between a waveform change pattern and a state of a human being which the correlative data is stored in a storage unit in advance.

2. The biological body state estimation device according to claim 1, wherein

the frequency calculating means includes first frequency calculating means for pinpointing a zero-crossing point in the time-series waveform of the biological signal obtained by the biological signal measuring means, and for determining the time-series waveform of the frequency of the biological signal by using this zero-crossing point, the zero-crossing point being a point at which a positive of the time-series waveform is switched to a negative,

the frequency slope time-series calculating means includes first frequency slope time-series analysis calculating means for subjecting the time-series waveform of the frequency of the biological signal acquired by the first frequency calculating means to the movement calculation for determining the slope of the frequency at each predetermined time window set with the predetermined overlap time, and for outputting the time-series change in the slope of the frequency acquired at each time window as the frequency slope time-series waveform, and

the spectrum time-series change calculating means is configured to analyze the frequency of the frequency slope time-series waveform acquired by the first frequency slope time-series analysis calculating means, and to determine the time-series change in the power spectrum.

3. The biological body state determination device according to claim 1, wherein

the frequency calculating means includes second frequency calculating means for determining a maximum value of the time-series waveform of the biological signal obtained from the biological signal measuring means by smoothing and differentiating the time-series waveform, and determining the time-series waveform of the frequency of the biological signal by using this maximum value,

the frequency slope time-series calculating means includes second frequency slope time-series analysis calculating means for subjecting the time-series waveform of the frequency of the biological signal acquired by the second frequency calculating means to the movement calculation for determining the slope of the frequency at each predetermined time window set with the predetermined overlap time, and for outputting the time-series change in the slope of the frequency acquired at each time window as the frequency slope time-series waveform, and

the spectrum time-series change calculating means is configured to analyze the frequency of the frequency slope time-series waveform acquired by the second frequency slope time-series analysis calculating means, and to determine the time-series change in the power spectrum.

4. The biological body state determination device according to claim 1, wherein

the determining means determines a time zone in which the functional adjustment signal and the fatigue reception signal are opposite in phase to be a period during which a sleepiness-related phenomenon emerges, as the waveform change pattern of the distribution rate waveform.

5. The biological body state determination device according to claim 4, wherein

the determining means determines a time zone in which the functional adjustment signal and the fatigue reception signal are opposite in phase and the distribution rate of the activity adjustment signal is equal to or higher than a predetermined distribution rate to be a period during which a predictive phenomenon of falling asleep emerges, as the waveform change pattern of the distribution rate waveform.

6. The biological body state determination device according to claim 1, wherein

for use in the distribution rate waveform calculating means, a frequency of the functional adjustment signal is 0.0017 Hz, a frequency of the fatigue reception signal is 0.0035 Hz, and a frequency of the activity adjustment signal is 0.0053 Hz.

7. A non-transitory computer readable medium to be set in a biological body state estimation device which acquires a biological signal from an upper body of the human being and estimates a state of a human being by using the biological signal, causing a computer to perform:

a frequency calculating step of determining a time-series waveform of a frequency from a time-series waveform of a biological signal acquired by the biological signal measuring means;

a frequency slope time-series analysis calculating step of subjecting the time-series waveform of the frequency of the biological signal acquired in the frequency calculating step to movement calculation for determining a slope of the frequency at each predetermined time window set with a predetermined overlap time, and of outputting a time-series change in the slope of the frequency acquired at each time window as a frequency slope time-series waveform;

a spectrum time-series change calculation step of analyzing a frequency of the frequency slope time-series waveform acquired in the frequency slope time-series analysis calculating step, and of determining a time-series change in a power spectrum;

a distribution rate waveform calculation step of extracting frequency components corresponding to a preset functional adjustment signal, fatigue reception signal and activity adjustment signal from the time-series change in the power spectrum acquired in the spectrum time-series change calculating step, of calculating proportions of the three frequency components in time sequence when a sum of power spectrums of the three frequency components is set to 100, and of determining the proportions as distribution rate waveforms; and

a determining step of locating a waveform change pattern of the three frequency components in the distribution rate waveforms acquired in the distribution rate waveform calculating step, and of determining a state of a human being by comparing the located waveform change pattern with correlative data between a waveform change pattern and a state of a human being which the correlative data is stored in a storage unit in advance.

8. The non-transitory computer readable medium according to claim 7, wherein

the frequency calculating step includes a first frequency calculation step of pinpointing a zero-crossing point in the time-series waveform of the biological signal obtained by the biological signal measuring means, and for determining the time-series waveform of the frequency of the biological signal by using this zero-crossing point, the zero-crossing point being a point at which a positive of the time-series waveform is switched to a negative,

the frequency slope time-series calculating step includes a first frequency slope time-series analysis calculation step of subjecting the time-series waveform of the frequency of the biological signal acquired in the first frequency calculating step to the movement calculation for determining the slope of the frequency at each predetermined time window set with the predetermined overlap time, and of outputting the time-series change in the slope of the frequency acquired at each time window as the frequency slope time-series waveform, and

the spectrum time-series change calculation step is configured to analyze the frequency of the frequency slope time-series waveform acquired in the first frequency slope time-series analysis calculating step, and to determine the time-series change in the power spectrum.

9. The non-transitory computer readable medium according to claim 7, wherein

the frequency calculating step includes a second frequency calculation step of determining a maximum value of the time-series waveform of the biological signal obtained from the biological signal measuring means by smoothing and differentiating the time-series waveform, and determining the time-series waveform of the frequency of the biological signal by using this maximum value,

the frequency slope time-series calculating step includes a second frequency slope time-series calculating step of subjecting the time-series waveform of the frequency of the biological signal acquired in the second frequency calculating step to the movement calculation for determining the slope of the frequency at each predetermined time window set with the predetermined overlap time, and of outputting the time-series change in the slope of the frequency acquired at each time window as the frequency slope time-series waveform, and

the spectrum time-series change calculation step is configured to analyze the frequency of the frequency slope time-series waveform acquired in the second frequency slope time-series analysis calculating step, and to determine the time-series change in the power spectrum.

10. The non-transitory computer readable medium according to claim 8, wherein

in the determining step, a time zone in which the functional adjustment signal and the fatigue reception signal are opposite in phase is determined to be a period during which a sleepiness-related phenomenon emerges, as the waveform change pattern of the distribution rate waveform.

11. The non-transitory computer readable medium according to claim 10, wherein

in the determining step, a time zone in which the functional adjustment signal and the fatigue reception signal are opposite in phase and the distribution rate of the activity adjustment signal is equal to or higher than a predetermined distribution rate is determined to be a period during which a predictive phenomenon of falling asleep emerges, as the waveform change pattern of the distribution rate waveform.

12. The non-transitory computer readable medium according to claim 7, wherein

for use in the distribution rate waveform calculating step, a frequency of the functional adjustment signal is 0.0017 Hz, a frequency of the fatigue reception signal is 0.0035 Hz, and a frequency of the activity adjustment signal is 0.0053 Hz.