Biological body state estimation device and computer program

• US 9,622,708 B2
• Filed: 10/28/2011
• Issued: 04/18/2017
• 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
• Primary Examiner(s): Nguyen, Anhtuan T
• Assistant Examiner(s): WOO, JAE KYUN
• Application Number:
  US13/881,871
• Publication Number:
  US 20130225940A1
• Time in Patent Office: 1,999 Days
• Field of Search: 600301, 600481, 600504, 600513, 600519, 600544, 600527, 600500, 600509, 600545, 600372, 607 9, 607 25, 128901
• 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 device to detect a state of a human being is provided. The device 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 a human being and estimates a state of a human being by using the biological signal, comprising:

circuitry configured to;

calculate frequency to determine a time-series waveform of a frequency from a time-series waveform of a biological signal acquired by a biological signal measuring mechanism;

calculate frequency slope time-series analysis to subject the time-series waveform of the frequency of the biological signal to movement calculation to determine a slope of the frequency at each predetermined time window set with a predetermined overlap time, and to output a time-series change in the slope of the frequency acquired at each time window as a frequency slope time-series waveform;

calculate spectrum time-series change to analyze a frequency of the frequency slope time-series waveform, and to determine a time-series change in a power spectrum;

calculate distribution rate waveform to extract 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, for to calculate proportions of three frequency components in time sequence when a sum of power spectrums of the three frequency components is set to 100, and to determine the proportions as distribution rate waveforms; and

locate a waveform change pattern of the three frequency components in the distribution rate waveforms, and determine 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, the circuitry further configured to:

calculate first frequency to pinpoint a zero-crossing point in the time-series waveform of the biological signal obtained by the biological signal measuring mechanism, and to determine the time-series waveform of the frequency of the biological signal by using the zero-crossing point, the zero-crossing point being a point at which a positive of the time-series waveform is switched to a negative,

calculate first frequency slope time-series analysis to subject the time-series waveform of the frequency of the biological signal to the movement calculation to determine the slope of the frequency at each predetermined time window set with the predetermined overlap time, and to output the time-series change in the slope of the frequency acquired at each time window as the frequency slope time-series waveform, and

analyze the frequency of the frequency slope time-series waveform, and determine the time-series change in the power spectrum.

3. The biological body state determination device according to claim 1, the circuitry further configured to:

calculate second frequency to determine a maximum value of the time-series waveform of the biological signal obtained from the biological signal measuring mechanism by smoothing and differentiating the time-series waveform, and determining the time-series waveform of the frequency of the biological signal by using the maximum value,

calculate second frequency slope time-series analysis to subject the time-series waveform of the frequency of the biological signal to the movement calculation to determine the slope of the frequency at each predetermined time window set with the predetermined overlap time, and to output the time-series change in the slope of the frequency acquired at each time window as the frequency slope time-series waveform, and

analyze the frequency of the frequency slope time-series waveform, and determine the time-series change in the power spectrum.

4. The biological body state determination device according to claim 1, circuitry configured to:

determine 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, circuitry configured to:

determine 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

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 a human being and estimates a state of a human being by using the biological signal, causing a computer to perform a process comprising:

determining a time-series waveform of a frequency from a time-series waveform of a biological signal acquired by a biological signal measuring mechanism;

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

analyzing a frequency of the frequency slope time-series waveform, and determining a time-series change in a power spectrum;

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 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 determining the proportions as distribution rate waveforms; and

locating a waveform change pattern of the three frequency components in the distribution rate waveforms, and 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, the process further comprising:

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

subjecting the time-series waveform of the frequency of the biological signal to the movement calculation to determine the slope of the frequency at each predetermined time window set with the predetermined overlap time, and outputting the time-series change in the slope of the frequency acquired at each time window as the frequency slope time-series waveform, and

analyzing the frequency of the frequency slope time-series waveform, and analyzing the time-series change in the power spectrum.

9. The non-transitory computer readable medium according to claim 7, the process further comprising:

determining a maximum value of the time-series waveform of the biological signal obtained from the biological signal measuring mechanism by smoothing and differentiating the time-series waveform, and determining the time-series waveform of the frequency of the biological signal by using the maximum value,

subjecting the time-series waveform of the frequency of the biological signal to the movement calculation to determine the slope of the frequency at each predetermined time window set with the predetermined overlap time, and outputting the time-series change in the slope of the frequency acquired at each time window as the frequency slope time-series waveform, and

analyzing the frequency of the frequency slope time-series waveform, and determining the time-series change in the power spectrum.

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

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

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

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.