The present invention relates to the field of sports equipment, in particular, relates to a human body movement state monitoring method and device.
With the continuous development of social economy, material living standard is gradually improved, and at the same time, health of ones own is more and more concerned, and a variety of sports schemes for fitness are customized for ones own. Therefore, various devices for monitoring sports schemes occur.
Pedometer is a device capable of calculating the walk or run step number of its wearer. However, pedometer merely has a rather single function, which cannot monitor other movement forms and sleeping of a person. There are also some devices capable of monitoring various forms of movement of a person comprehensively, which require the intervention of human operation, and fail to monitor various movement conditions and sleeping conditions of the person automatically, comprehensively, and round-the-clock. Meanwhile, sleeping conditions are very helpful for determining the health conditions of the person, During sleeping, the person may make some abnormal movements such as turning, scratching, scaring, etc. If such abnormal movements occur rather frequently, it indicates that the person's sleep quality is not good enough. Therefore, both the monitoring of person's sleeping conditions and normal movement conditions are helpful for improving one's fitness schemes.
The present invention is aimed to solve the problems existing in the aforesaid prior art, with an object for providing a human body movement state monitoring method and device, the method and device can automatically, comprehensively, round-the-clock, accurately monitor various movement states of a person, thus provide basis for improving one's fitness schemes.
For achieving aforesaid object, one aspect of the present invention provides a human body movement state monitoring method, the method comprising the following steps performed repeatedly:
Preferably, the determining step of the quasi-periodicity of the acceleration signals can comprise:
Further preferably, the step of calculating movement step number according to the acceleration signals can comprise:
counting the effective extreme value points in the low-pass or band-pass filtered acceleration signals having quasi-periodicity, the number of the effective extreme value points being movement step number.
Further preferably, a displacement signal can be obtained by double integral of the acceleration signals on time.
The method of performing pitch detection on the high-pass filtered acceleration signals can comprise one or more of autocorrelation function method, cepstrum method, linear predictive coding method and average magnitude difference function method.
Preferably, performing pitch detection on the high-pass filtered acceleration signals can comprise: attenuating the signals with a filter that attenuates signals with an incrementing degree from low frequency to high frequency; obtaining the autocorrelation function ρ(τ) of the attenuated signals from the following formula:
Wherein, removing the interfering extreme value points from the extreme value points of the acceleration signals comprises: filtering out the interfering extreme value points from the extreme value points of the acceleration signals through a time gap; alternatively, filtering out the interfering extreme value points from the extreme value points of the acceleration signals through a time gap and a magnitude value.
Preferably, the interfering extreme value points may comprise such an extreme value point of the acceleration signals that the time gap between the extreme value point of the acceleration signals and the previous extreme value point of the acceleration signals is less than a predetermined threshold; or the interfering extreme value points may comprise extreme value points of the acceleration signals, whose magnitude values are not maximal, among each group of extreme value points of the acceleration signals with time gaps continuously less than a predetermined threshold.
Preferably, the human body movement state monitoring method also can comprise optionally displaying the total time period of the sleeping state, the total energy of the sleeping state, the total time period of the sleeping abnormal movements, the total time period of the light movement state, the total energy of the light movement state, the total time period of the irregular fierce movement state, the total energy of the irregular fierce movement state, the total time period of the regular fierce movement state, the total energy of the regular fierce movement state and the total step number of movement.
According to another aspect of the present invention, a human body movement state monitoring device is provided, which comprises: a triaxial acceleration sensor, an acceleration signal obtaining unit, a calculating unit, a human body movement state determining unit, a sleeping abnormal movement statistical unit, a sampling time period setting unit, a storage unit, a quasi-periodicity determining unit, and a step counting unit.
The acceleration signal obtaining unit obtains acceleration signals having a set sampling time period from output of the triaxial acceleration sensor worn on a human body, and the calculating unit calculates the energy and average power of the acceleration signals;
the human body movement state determining unit determines a human body movement state according to the average power of the acceleration signals, and if the average power of the acceleration signals is more than a predetermined fierce movement threshold, determines that the human body is in a fierce movement state, if the average power of the acceleration signals is less than a predetermined sleeping threshold, determines that the human body is in a sleeping state, if the average power of the acceleration signals is less than the fierce movement threshold and is more than the sleeping threshold, determines that the human body is in a light movement state;
if the human body movement state determining unit determines that the human body is in the sleeping state, accumulates the time periods of the acceleration signals into the total time period of the sleeping state, accumulates the energy of the acceleration signals into the total energy of the sleeping state, the sleeping abnormal movement statistical unit counts up the time periods of acceleration signals which have intensity more than a predetermined intensity threshold, and accumulates the counted time periods into the total time period of sleeping abnormal movements, the sampling time period setting unit sets the sampling time period of acceleration signal as the sampling time period of the sleeping state, the storage unit stores the total time period of the sleeping state, the total energy of the sleeping state and the total time period of the sleeping abnormal movements;
if the human body movement state determining unit determines that the human body is in the light movement state, accumulates the time periods of the acceleration signals into the total time period of the light movement state, accumulates the energy of the acceleration signals into the total energy of the light movement state, and the sampling time period setting unit sets the sampling time period of acceleration signal as the sampling time period of the light movement state, the storage unit stores the total time period of the light movement state and the total energy of light movement state;
if the human body movement state determining unit determines that the human body is in the fierce movement state, then the quasi-period determining unit determines whether the acceleration signals have quasi-periodicity, and if determining that the acceleration signals do not have quasi-periodicity, then the human body movement state determining unit determines that the human body is in an irregular fierce movement state, and if the quasi-period determining unit determines that the acceleration signals have quasi-periodicity, then the human body movement state determining unit determines that the human body is in a regular fierce movement state;
if the human body movement state determining unit determines that the human body is in the irregular fierce movement state, then accumulates the time periods of the acceleration signals into the total time period of the irregular fierce movement state, accumulates the energy of the acceleration signals into the total energy of the irregular fierce movement state, and the sampling time period setting unit sets the sampling time period of acceleration signals as the sampling time period of the fierce movement state, the storage unit stores the total time period of the irregular fierce movement state and the total energy of the irregular fierce movement state;
if the human body movement state determining unit determines that the human body is in the regular fierce movement state, then accumulates the time periods of the acceleration signals into the total time period of the regular fierce movement state, accumulates the energy of the acceleration signals into the total energy of the regular fierce movement state, and the step counting unit calculates movement step number according to the acceleration signals, and accumulates the movement step number into the total movement step number, the sampling time period setting unit sets the sampling time period of acceleration signal as the sampling time period of fierce movement state, the storage unit stores the total time period of the regular fierce movement state, the total energy of the regular fierce movement state and the movement step number.
Preferably, the human body movement state monitoring device may further comprise a display unit for optionally displaying the total time period of the sleeping state, the total energy of the sleeping state, the total time period of the sleeping abnormal movements, the total time period of the light movement state, the total energy of the light movement state, the total time period of the irregular fierce movement state, the total energy of the irregular fierce movement state, the total time period of the regular fierce movement state, the total energy of the regular fierce movement state and the total step number of movement.
It is known from the above description and practice that the human body movement state monitoring method and device of the present invention can automatically, comprehensively, round-the-clock, accurately monitor various movement states (including sleeping state) of a person, can measure the quality of human sleep quantitatively, measure their movement step number during walking and running accurately, and can measure their movement level and energy consumption conditions quantitatively.
The aforesaid description is merely the summary of technical solution of the present invention, for understanding the technical means of the present invention more clearly, it can be carried out according to the disclosure of specification, and for making aforesaid and other objectives, features and advantages of the present invention more apparent to be understood, embodiments of the present invention are listed as follows.
By reading the detailed description of the preferable embodiment hereinafter, all the other features and advantages will be apparent to the general skilled in the art. The attached drawings are merely for the purpose of demonstrating preferable embodiment, rather than deemed as a limitation of the present invention. Among the attached drawings:
a is a signal graph, demonstrating representative normalized acceleration signals having a predetermined length output from the triaxial acceleration sensor;
b is a signal graph, demonstrating high-pass filtered acceleration signals;
c is a signal graph, demonstrating low-pass filtered acceleration signals;
d is a signal graph, demonstrating an example of extreme value points of the low-pass filtered acceleration signals;
The present invention will be described in details in combination with the attached drawings and specific examples.
In the following description, certain illustrative examples of the present invention are only described by way of illustration. Undoubtedly, one of ordinary skilled in the art may recognize that the examples can be amended by using a variety of different ways without departing from the spirit and scope of the present invention. Accordingly, the attached drawings and descriptions are illustrative in nature, and not intended to limit the protection scope of the claims. In the present specification, the same reference numerals denote the same or similar parts.
The human body movement state monitoring method of the present invention is carried out by using a device having a triaxial acceleration sensor.
As shown in
Therefore, when analyzing the acceleration signals produced during sleeping, sampling length of signal should be relatively long, which not only facilitates for reducing computation amount, improving analyzing speed, but also makes abnormal movements during sleeping separable from the movements during light movements and fierce movements, this is because, since the time of abnormal movements accounts for a relatively small ratio of whole sleeping time, the contribution of abnormal movements of sleeping to the average power is negligible. Similarly, when analyzing the acceleration signals produced during light movements and fierce movements, sampling length should be different, for reducing computation amount, improving analyzing speed and also not enabling corresponding acceleration signals to lose feature.
The reference sign added to each embodiment of the present invention is merely to facilitate demonstrating the operation order of a preferable solution, but does not limit specific operation sequence of each step strictly.
firstly, in step S10, obtaining acceleration signals having a set sampling time period from output of a triaxial acceleration sensor worn on a human body, and calculating the energy and average power of the acceleration signals.
Preferably, the average power P of the acceleration signals can be calculated from the following formula:
subsequently, determining a human body movement state according to the average power of the acceleration signals. For example, in step S20, determining whether the average power of the acceleration signals is more than a predetermined fierce movement threshold, and if the average power of the acceleration signals is more than the predetermined fierce movement threshold, it is determined that the human body is in a fierce movement state (step S30), otherwise, in step S40, determining whether the average power of the acceleration signals is less than a predetermined sleeping threshold, and if the average power of the acceleration signals is less than the predetermined sleeping threshold, it is determined that the human body is in a sleeping state (step S50), if the average power of the acceleration signals is less than the fierce movement threshold and is more than the sleeping threshold, it is determined that the human body is in a light movement state (step S60). Wherein, the fierce movement threshold and the sleeping threshold can be obtained according to experiments, and can be adjusted.
If the human body is in the sleeping state, then in step S55, accumulating the time periods of the acceleration signals into the total time period of the sleeping state, accumulating the energy of the acceleration signals into the total energy of the sleeping state, counting up the time periods of acceleration signals which have intensity more than a predetermined intensity threshold, and accumulating the counted time periods into the total time period of sleeping abnormal movements, and setting the sampling time period of acceleration signals as the sampling time period of the sleeping state, then returning to step S10. It should be noted that, the time period of acceleration signals which has intensity more than a predetermined intensity threshold denotes such a period of time that within this period of time, the intensity size of the acceleration signals is more than the predetermined intensity threshold. This period of time is the time of abnormal movements of sleeping, during which abnormal movements of sleeping such as turning-over, scaring, spasm etc. occur, and through analyzing the ratio of total time period of abnormal movement time of sleeping accounting for total time period of sleeping, sleeping quality can be analyzed quantitatively, and when the ratio is very small, it denotes that the sleeping is deep sleeping, when the ratio is relatively large, it denotes that the sleeping is light sleeping. In addition, the sampling time period of sleeping state can be determined according to experiments, such as 5˜10 minutes.
If the human body is in the light movement state, then in step S65, accumulating the time periods of the acceleration signals into the total time period of the light movement state, accumulating the energy of the acceleration signals into the total energy of the light movement state, and setting the sampling time period of acceleration signals as the sampling time period of the light movement state, then returning to step S10. The sampling time period of light movement state can be determined according to experiment, such as 1 minute.
If the human body is in the fierce movement state, then in step S70 further determining whether the acceleration signals have quasi-periodicity, if the acceleration signals do not have quasi-periodicity, it is determined that the human body is in an irregular fierce movement state (step S80), if the acceleration signals have quasi-periodicity, it is determined that the human body is in a regular fierce movement state (step 90).
Wherein, the determination of the quasi-periodicity of the acceleration signals can comprise the following steps □ to □:
Step □ performing high-pass filtering on the acceleration signals. Since the acceleration signals output from the triaxial acceleration sensor generally comprise DC component, and the existence of the DC component would interfere with the analyzing of acceleration signals, the DC component is removed from the acceleration signals through high-pass filtering.
Step □ performing pitch detection on the high-pass filtered acceleration signals. The acceleration signals may comprise various frequency components corresponding to different body rhythmic movements, such as pitch component, frequency multiplication component and other high frequency components.
There are various methods for pitch detection, e.g., conventional methods in voice signal pitch detection such as autocorrelation function method, cepstrum method, linear predictive coding method, average magnitude difference function method can be used. Preferably, autocorrelation function method can be used.
Specifically, the high-pass filtered acceleration signals are attenuated with a filter that attenuates signal energy with an incrementing degree from low frequency to high frequency, to suppress high frequency component in the acceleration signals, so as to highlight the pitch component in the monoaxial acceleration signals, and reduce the error of obtained pitch.
Then, the autocorrelation function ρ(τ) of the attenuated signals is obtained from the following formula:
wherein a(n) is the No. n value of the attenuated signals, N is the length of the signals, and 1≦n≦N, τ is a delay time, ρ(τ) is normalized autocorrelation function of the signals; calculate the value of τ corresponding to the maximal value of ρ(τ), and the reciprocal of the τ value is the pitch of the signals.
Step □ obtaining extreme value points of the acceleration signals in the low-pass or band-pass filtered acceleration signals and removing interfering extreme value points in the extreme value points of the acceleration signals, so as to obtain effective extreme value points.
In one embodiment of the present invention, the interfering extreme value points may comprise such an extreme value point of the acceleration signals that the time gap between the extreme value point of the acceleration signals and the previous extreme value point of the acceleration signals is less than a predetermined threshold, wherein, the predetermined threshold is far less than the period of the pitch component of monoaxial acceleration signals. In the embodiment, in each group of extreme value points relatively close to each other, only one extreme value point on the leftmost is kept, and the other extreme value points are removed as interfering extreme value points. In this manner, the interfering extreme value points in the extreme value points of the acceleration signals are filtered out through the time gap between the extreme value points of the acceleration signals.
In another embodiment of the present invention, the interfering extreme value points may comprise such extreme value points of the acceleration signals, whose magnitude values are not maximal, among each group of extreme value points of the acceleration signals with time gaps continuously less than a predetermined threshold. In another words, in the embodiment, in each group of extreme value points relatively close to each other, only the extreme value point of the acceleration signals with maximal magnitude value is kept, and the other extreme value points are removed as interfering extreme value points. In this manner, the interfering extreme value points in the extreme value points of the acceleration signals are filtered out through the time gaps between the extreme value points of the acceleration signals and the magnitude values of extreme value points of the acceleration signals.
Step □ calculating time gaps between adjacent effective extreme value points, obtaining a time gap sequence, and calculating differences between adjacent time gaps in the time gap sequence, obtaining a time gap difference sequence, and if each of a continuous predetermined number of time gap differences in the time gap difference sequence is less than a predetermined period threshold, it is determined that the acceleration signals have quasi-periodicity, otherwise, it is determined that the acceleration signals do not have quasi-periodicity.
Returning back to
If the human body is in the regular fierce movement state, then in step S95 accumulating the time periods of the acceleration signals into the total time period of the regular fierce movement state, accumulating the energy of the acceleration signals into the total energy of the regular fierce movement state, calculating movement step number according to the acceleration signals, and accumulating the movement step number into the total movement step number, and setting the sampling time period of acceleration signals as the sampling time period of the fierce movement state, then returning to step S10.
The method of calculating movement step number according to the acceleration signals can comprise: count the effective extreme value points in the low-pass or band-pass filtered acceleration signals having quasi-periodicity, and the number of the effective extreme value points is the movement step number obtained in this step counting process. Furthermore, a displacement signal can be obtained by double integral of the acceleration signals on time, so as to provide reference for actual movement distance to a walker & runner. In addition, it can be distinguished whether it is in situ movements or actual walking & running according to the size of the displacement.
The human body movement state monitoring method of the present invention further comprises optionally displaying the total time period of the sleeping state, the total energy of the sleeping state, the total time period of the sleeping abnormal movements, the total time period of the light movement state, the total energy of the light movement state, the total time period of the irregular fierce movement state, the total energy of the irregular fierce movement state, the total time period of the regular fierce movement state, the total energy of the regular fierce movement state and the total step number of movement. Thus, according to these data, a person's sleeping quality, movement level and energy consumption condition can be known.
Hereinbefore the human body movement state monitoring method of the present invention is described by referring to
The acceleration signal obtaining unit 200 obtains acceleration signals having a set sampling time period from output of the triaxial acceleration sensor 100 worn on a human body, and the calculating unit 300 calculates the energy and average power of the acceleration signals.
The human body movement state determining unit 400 determines a human body movement state according to the average power of the acceleration signals, and if the average power of the acceleration signals is more than a predetermined fierce movement threshold, determines that the human body is in a fierce movement state; if the average power of the acceleration signals is less than a predetermined sleeping threshold, determines that the human body is in a sleeping state; if the average power of the acceleration signals is less than the fierce movement threshold and is more than the sleeping threshold, determines that the human body is in a light movement state;
If the human body movement state determining unit 400 determines that the human body is in the sleeping state, accumulates the time periods of the acceleration signals into the total time period of the sleeping state, accumulates the energy of the acceleration signals into the total energy of the sleeping state; the sleeping abnormal movement statistical unit 500 counts up the time periods of acceleration signals which have intensity more than a predetermined intensity threshold, and accumulates the counted time periods into the total time period of sleeping abnormal movements; the sampling time period setting unit 600 sets the sampling time period of acceleration signals as the sampling time period of the sleeping state; the storage unit 700 stores the total time period of the sleeping state, the total energy of the sleeping state and the total time period of the sleeping abnormal movements.
If the human body movement state determining unit 400 determines that the human body is in the light movement state, accumulates the time periods of the acceleration signals into the total time period of the light movement state, accumulates the energy of the acceleration signals into the total energy of the light movement state, and the sampling time period setting unit 600 sets the sampling time period of acceleration signals as the sampling time period of the light movement state; the storage unit 700 stores the total time period of the light movement state and the total energy of light movement state.
If the human body movement state determining unit 400 determines that the human body is in the fierce movement state, then the quasi-period determining unit 800 determines whether the acceleration signals have quasi-periodicity, and if determining that the acceleration signals do not have quasi-periodicity, then the human body movement state determining unit 400 determines that the human body is in an irregular fierce movement state, and if the quasi-period determining unit 800 determines that the acceleration signals have quasi-periodicity, then the human body movement state determining unit 400 determines that the human body is in a regular fierce movement state.
If the human body movement state determining unit 400 determines that the human body is in the irregular fierce movement state, then accumulates the time periods of the acceleration signals into the total time period of the irregular fierce movement state, accumulates the energy of the acceleration signals into the total energy of the irregular fierce movement state, and the sampling time period setting unit 600 sets the sampling time period of acceleration signals as the sampling time period of the fierce movement state; the storage unit 700 stores the total time period of the irregular fierce movement state and the total energy of the irregular fierce movement state.
If the human body movement state determining unit 400 determines that the human body is in the regular fierce movement state, then accumulates the time periods of the acceleration signals into the total time period of the regular fierce movement state, accumulates the energy of the acceleration signals into the total energy of the regular fierce movement state, and the step counting unit 900 calculates movement step number according to the acceleration signals, and accumulates the movement step number into the total movement step number; the sampling time period setting unit 600 sets the sampling time period of acceleration signals as the sampling time period of fierce movement state; the storage unit 700 stores the total time period of the regular fierce movement state, the total energy of the regular fierce movement state and the movement step number.
Preferably, the human body movement state monitoring device 1000 may further comprise a display unit 950 for optionally displaying the total time period of the sleeping state, the total energy of the sleeping state, the total time period of the sleeping abnormal movements, the total time period of the light movement state, the total energy of the light movement state, the total time period of the irregular fierce movement state, the total energy of the irregular fierce movement state, the total time period of the regular fierce movement state, the total energy of the regular fierce movement state and the total step number of movement.
Hereinbefore the human body movement state monitoring method and device according to the present invention are described by referring to attached drawings in an illustrative way. However, one skilled in the art should understand that, for the human body movement state monitoring method and device of the present invention, various modifications can be made without departing from the content of the present invention. Hence, the protection scope of the present invention should be determined by the content of appended claims.
It should be noted that:
The example of each component in the present invention can be achieved by hardware, or achieved by software module operating on one or more processors, or achieved in a combination thereof. Those skilled in the art should understand that, some or all functions of some or all components according to the example of the present invention can be achieved by using micro-processor or digital signal processor (DSP) in practice. The present invention can also be implemented as a program for carrying out part or all equipment or device in the described method herein (for example, computer program and computer program product). The program implementing the present invention as such can be stored on the computer readable medium, or may be having a form of one or more signals. Such a signal can be downloaded from internet website, or provided on a carrier signal, or provided in any other forms.
For example,
It should be noted that the aforesaid examples are for explaining the present invention rather than limiting the present invention, and those skilled in the art can design alternative example without departing from the scope of appended claims. In the claims, any reference symbol located between parentheses should not be construed as limitation to claims. Word “comprise” does not exclude the existence of element or step not defined in the claims. The present invention can be implemented through hardware containing various different elements and through suitably programmed computer. In the device claim listing several devices, several of these devices can be specifically implemented by one same hardware item.
In the description provided herein, numerous specific details are described. However, it can be understood that, the examples of the present invention can be carried out without these specific details. In some examples, well-known methods, structures and techniques are not disclosed in details, so as not to blur the understanding of the present specification. The terms used in the present specification are mainly selected for the purpose of readability and instruction, rather than selected for explaining or limiting the subject matter of the present invention.
Number | Date | Country | Kind |
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201310754081.X | Dec 2013 | CN | national |
Filing Document | Filing Date | Country | Kind |
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PCT/CN2014/001178 | 12/25/2014 | WO | 00 |