CN104042191A - Wrist watch type multi-parameter biosensor - Google Patents
Wrist watch type multi-parameter biosensor Download PDFInfo
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- CN104042191A CN104042191A CN201410324829.7A CN201410324829A CN104042191A CN 104042191 A CN104042191 A CN 104042191A CN 201410324829 A CN201410324829 A CN 201410324829A CN 104042191 A CN104042191 A CN 104042191A
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Abstract
The invention discloses a wrist watch type multi-parameter biosensor and relates to a self-adaptive detection method for physiological parameters and a multi-parameter intelligent monitoring wrist watch by the adoption of the method. The method comprises the steps that (1) human physiological parameter signals are collected; (2) the human physiological parameter signals are subjected to self-adaptive wavelet decomposition, and feature predictors and updaters are selected point by point in the decomposition process; (3) waveform analysis is conducted, interference signals in the decomposed signals are eliminated, and human physiological parameter signals without interference are obtained. The monitoring wrist watch comprises a base body, wherein the base body is provided with a central processing unit, a physiological parameter sensor used for collecting the human physiological parameter signals and various other sensors. The central processing unit processes data by the adoption of a self-adaptive wavelet decomposition method to obtain the human physiological parameter signals without interference. The wrist watch type multi-parameter biosensor effectively solves the problem of instability caused by large contact resistance generated when a daily wearing mode is adopted. The wrist watch type multi-parameter biosensor is convenient to use and can collect various human physiological signals, movement signals, environment signals and the like in real time.
Description
Technical field
The present invention relates to a kind of self-adapting detecting method of physiological signal, also relate to a kind of multi parameter intallingent monitoring wrist-watch of adopting in this way, be mainly used in the detection to human physiology parameter.
Background technology
Raising along with living standard and health perception, people wish to understand at any time the health of oneself, Wearable biological sensing system arises at the historic moment thus, but the Wearable biological sensing system under prior art is often very clumsy, volume is large, need special bundling belt to fix, affected the daily life of user, also affect attractive in appearance and social communication user.For the facility on using and attractive in appearance, the sensor (sensing device) that can gather various required human physiology parameter/signals is arranged on the Wearable sensing device of wrist-watch shape, formation can gather the monitoring wrist-watch of various human physiological parameter/signal at any time, this monitoring wrist-watch on user image-tape general wristwatch one belt transect, just can gather at any time and obtain corresponding physiological parameter/signal (for example can detect pulse), contribute to make the health of user real time monitoring self, very easy to use.
But, if user is worn over this monitoring wrist-watch that is provided with some sensors in wrist, the pulse wave signal that monitoring obtains tends to be subject to the impact of the external world or user self interference factor, bring difficulty to the extraction of pulse wave, cause pulse wave measurement to be difficult to accurately even make a mistake, for the monitoring of other physiological signals, also have similar problem.Therefore, eliminate and disturb, improving signal quality is to need one of problem of emphasis solution in this parameter intelligent monitoring watch design, only has effectively and solves these problems, and can make this monitor mode have actual use value.
Interference effect mainly comprises: (1) motion artifact: the athletic meeting of detected person's health causes the factors such as blood engorgement situation, optical path length to change, thereby makes measurement result cannot correctly reflect the truth of tester's pulse wave.By detected person's muscle jitter and people, be that the displacement causing easily causes pulse wave baseline drift, also may cause the variation of venous blood and be mistaken as is that the arterial blood of pulsation changes and the calculation deviation that causes.Because the formation mechanism of motion artifact cannot be processed with traditional wave filter it, to the rejecting of motion artifact, be therefore also a Focal point and difficult point in pulse wave Monitoring System for a long time; (2) baseline drift: in the acquisition process of pulse wave, the baseline drift producing due to people's respiratory movement and health displacement must overcome.Unstable and the respiration wave of amplifying circuit is the main cause that causes baseline drift.The frequency of baseline drift is 0.15-0.3Hz; (3) myoelectricity disturbs: muscle contraction produces the signal of microvolt level, can think the instantaneous burst of zero-mean band limit Gaussian noise, and its peak value is generally 20% left and right of pulse signal, and frequency range is in 0-10KHz left and right.It is overlapping that myoelectricity disturbs with pulse wave frequency, therefore, sometimes very serious to the interference of pulse signal.
Summary of the invention
In order to overcome the above-mentioned defect of prior art, the invention provides a kind of self-adapting detecting method of physiological parameter, a kind of monitoring of the multi parameter intallingent for Real-time Collection human body physiological parameter/signal wrist-watch that adopts the method to carry out information processing is also provided, this monitoring wrist-watch not only can gather human body physiological parameter/signal, and can eliminate or reduce the impact of interfering signal, obtain the higher waveform/parameter of quality.
The technical solution adopted in the present invention:
A self-adapting detecting method for physiological parameter, comprises the steps:
(1) gather human physiology parameter signal;
(2) described human physiology parameter signal is carried out to adaptive wavelet decomposition;
(3) carry out waveform analysis, eliminate the interfering signal composition in signal (detail signal d and/or approximation signal S) after decomposing, obtain the human physiology parameter signal of eliminating after disturbing,
In described step (2), comprise following steps:
(2.1) subdivision: signal sequence is divided into 2 parts by strange, even sample, wherein
Strange sample sequence X
p={ X
2k+1, k ∈ Z}, even sample sequence X
e={ X
2k, k ∈ Z};
(2.2) prediction: introduce predictive operator P, with
for even sample
estimated value
, definition detail signal d=
-
=
-
;
(2.3) upgrade: introduce and promote operator U, derive approximation signal s=X
e+ d/2=
.
A kind of multi parameter intallingent monitoring wrist-watch, comprise matrix, described matrix is provided with central processing unit and for gathering the physiological parameter sensors of human physiology parameter signal, described physiological parameter sensors connects described central processing unit by physiological parameter data Acquisition Circuit, described central processing unit adopts the self-adapting detecting method of any one physiological signal disclosed by the invention to carry out self-adapting detecting to the physiological parameter signals from described physiological parameter sensors, eliminate the interfering signal composition in signal after decomposing, obtain the human physiology parameter signal of eliminating after disturbing.
Beneficial effect of the present invention: the wavelet transformation that (1) adopts is to take Second Generation Wavelet Transformation SGWT(second generation wavelet transform) be basis, with matched signal, be characterized as and mark, a kind of adaptive wavelets transform method of signatures to predict device and renovator is selected in pointwise, and this method is that traditional wavelet method cannot realize; (2) autocorrelation coefficient of signal can descriptive analysis signal feature and variation tendency, getting different interval autocorrelation coefficients is index, according to its size, on each yardstick, convert one by one optimum prediction device and the renovator of sample, can make variation tendency and the local feature of wavelet function adaptation signal; (3) compare with Traditional Wavelet noise reduction, the adaptive wavelets transform based on SGWT not only can be removed noise effectively, and the local feature of locking signal effectively, is conducive to the extraction of physiology signal feature.It is easy to use that the present invention has solved the instability problem causing that daily wearing mode contact resistance is large effectively, meet the daily custom of wearing of people, can not increase burden or sense of discomfort because of monitoring, can Real-time Collection various human physiological signal, motor message and ambient signal etc., make user can understand at any time the physical condition of oneself, also has in addition remote functionality, each supplemental characteristic can be dealt into service centre for analyzing, management and storage, and can with intelligent television, Set Top Box, panel computer, the combined network communications such as common computer, for family, individual's health records, management and analysis.The self-adapting detecting method of physiological parameter of the present invention, conventionally can be for date processing and the detection of human physiology parameter signal, eliminate as much as possible interfering signal, also can be for date processing and the detection of other similar signal, according to applicant's experiment, this description background technology partly proposes to relate to the various interfering signals of pulse wave signal, applies after method processing of the present invention, can eliminate more than at least 85%.
Accompanying drawing explanation
Fig. 1 is structural representation of the present invention;
Fig. 2 is the operation principle schematic diagram of a kind of filtering mode of the present invention;
Fig. 3 is a kind of schematic diagram of concrete occupation mode;
Fig. 4 is workflow of the present invention and principle schematic;
Fig. 5 is the adaptive wavelet decomposition and reconstruction schematic diagram the present invention relates to.
The specific embodiment
Referring to Fig. 1-5, the self-adapting detecting method of physiological parameter provided by the invention comprises the steps:
(1) gather human physiology parameter signal;
(2) described human physiology parameter signal is carried out to adaptive wavelet decomposition;
(3) carry out waveform analysis, eliminate the interfering signal composition in signal (detail signal d and/or approximation signal S) after decomposing, obtain the human physiology parameter signal of eliminating after disturbing,
In described step (2), comprise following steps:
(2.1) subdivision: signal sequence is divided into 2 parts by strange, even sample, wherein
Strange sample sequence X
p={ X
2k+1, k ∈ Z}, even sample sequence X
e={ X
2k, k ∈ Z};
(2.2) prediction: introduce predictive operator P, with
for even sample
estimated value
, definition detail signal d=
-
=
-
;
(2.3) upgrade: introduce and promote operator U, derive approximation signal s=X
e+ d/2=X
e+ U (d).
Conventionally, described waveform analysis is the feature of the interfering signal that causes according to the feature of physiological parameter signals and each related interference factors, for each, decompose postamble sequence (each detail signal sequence and approximation signal sequence) and analyze relevant wave character, identify signal sequence after the decomposition relevant to interfering signal or signal characteristic parameter and with physiological parameter signals relevant signal sequence or signal characteristic parameter, on this basis interfering signal is removed.
For removing the mode of interfering signal, can adopt prior art or other suitable technology of any suitable.For example, the interfering signal filtering by the mode of threshold value is set, interference factor being caused in signal reconstruction, or directly extract the decomposition postamble sequence relevant to physiological parameter signals and carry out signal reconstruction, or extract the decomposition postamble sequence being caused by interference factor and inversely add in primary signal.This description has been introduced the feature that is mixed in several interfering signals main in pulse wave signal in background technology, by these features, contribute to judgement and identification to decompose the signal sequence causing because of interference factor in postamble sequence or the signal component being caused by interference factor (forming a part for signal sequence), under technology, people have also carried out certain experiment and research to the relevant some main interfering signal of the various physiological signals with the present invention relates to now, provided the wave character (frequency for example of these interfering signals, amplitude etc.), make thus to carry out correlation Waveform Analysis according to prior art and become possibility, related content is repeated no more here.Equally, for the adaptive wavelet the present invention relates to, decompose and reconstructing method (Second Generation Wavelet Transformation), include but not limited to predictive operator/prediction matrix, promote operator/lifting matrixes and the threshold setting that need to carry out for filtering etc., the content that improves to some extent, limits and innovate except the present invention and because of the needs in statement, also repeats no more here.
For example, described detail signal d has embodied the radio-frequency component in primary signal, how by interference factor, to be caused, and approximation signal s has embodied the low-frequency component of primary signal, mainly comprised physiological parameter signals, thus can be according to the spectrum signature of physiological signal and interfering signal and other wave characters, in restructuring procedure by interfering signal filtering, under prior art, a kind of common filtering mode is in restructuring procedure, to decomposed, postamble sequence arranges certain threshold value, the corresponding signal value under this threshold value that is less than causing because of interference factor is replaced with to zero, reconstruct mode thus can be eliminated most of interfering signal.For some wave character with the visibly different decomposition postamble sequence of wave character of the physiological parameter signals that detects or for negligible decomposition postamble sequence in reality, can directly reject (or assignment is zero), or only extract the decomposition postamble sequence relevant to physiological parameter signals and carry out signal reconstruction, can eliminate thus the impact of corresponding interference factor.
Preferably, according to the needs of reality detection/filtering, can carry out multilamellar decomposition to primary signal, the detail signal forming after one deck decomposes is decomposed again, until the requirement that the resolution obtaining after decomposing and wave character are enough to meet identification interfering signal and realize filtering.
Preferably, in order to embody better the variation of local feature, can be provided with many group predictor (predictive operator) and renovator (lifting operator), according to the correlation detection between figure signal and adjacent signals (when calculating corresponding signal predictive value or calculating corresponding signal renewal value used adjacent signals) and the local feature of analytic signal, thereby optimum prediction device (predictive operator) and the renovator (lifting operator) of determining each conversion sample on each yardstick, adopt described optimum prediction device and best renovator computational details signal d and approximation signal s.
Forecast period selects the different predictor of following 2 kinds of support Intervals as candidate predictor, for following (2, the 2) interpolating wavelet transform of the little employing of degree of association:
The improvement algorithm that the employing best interpolation that degree of association is large is estimated, determines detail signal d and approximation signal s in the following manner.
Introduce autocorrelation coefficient C
2and C (k)
6(k), described autocorrelation coefficient C
2and C (k)
6(k) adopt following manner to calculate:
Work as C
2(k)>=0 and C
6(k)>=C
2(k) time, the dependency between sample is stronger, conventionally can select following (6,6) interpolating wavelet:
，N=6；
，?N=6；
Wherein P=[1 1111 1]/6, U=[1 1111 1]/12;
Work as C
2(k)>=0 and C
6(k) <C
2(k), time, select following (4,2) interpolating wavelet transform:
，N=4；
，?N=2；
Wherein P=[1 11 1]/4, U=[1 1]/4;
Work as C
2(k) during <0, the dependency between sample a little less than, select following (2,2) interpolating wavelet transform:
Thus, according to the big or small pointwise of signal autocorrelation coefficient, select Predictor and updater, make the wavelet function local feature of matched signal best.Wavelet function and the scaling function of this wavelet transformation on each yardstick is no longer unique, but has wavelet function and the scaling function of cluster the best, and it has the ability of adaptation signal feature.
According to waveform analysis, can extract the decomposition postamble sequence being caused by interference factor inversely add (the subtraction end that for example adds computing circuit) in original physiologic parameter signal, make final signal there is no these interfering signals, can solve thus the signal that this multi parameter intallingent monitoring wrist-watch gathers and be difficult for stable specific question.Thus, the interfering signal composition in the rear signal of described elimination decomposition specifically can comprise the steps:
(3.1) the original physiologic parameter signal gathering is carried out to described adaptive wavelet decomposition, to decomposing postamble sequence, carry out waveform analysis, the original waveform feature that identification is relevant;
(3.2) introduce disturbing wave wave character, described disturbing wave wave character can obtain by following any one or various ways: (a) interfering signal being produced by interference factor is carried out to the adaptive wavelet identical with step (3.1) and decompose, waveform analysis is carried out in decomposition postamble sequence to disturbing wave, identifies relevant disturbing wave wave character: (b) according to the feature of interference factor by analysis or experiment obtain relevant disturbing wave wave character;
(3.3) the disturbing wave wave character of the original waveform feature obtaining in above-mentioned steps (3.1) and above-mentioned steps (3.2) introducing is analysed and compared, according to analyses and comparison result, from the decomposition postamble sequence of original physiologic parameter signal, identify and extract the interfering signal sequence causing because of interference factor;
(3.4) extracted interfering signal sequence inversion is added in primary signal, the interfering signal composition being caused by interference factor in counteracting and filtering primary signal thus.
According to prior art, can derive wavelet function and scaling function according to predictor P and renovator U.
Referring to Fig. 1-5, multi parameter intallingent monitoring wrist-watch provided by the invention comprises matrix, described matrix is provided with central processing unit and for gathering the physiological parameter sensors of human physiology parameter signal, described physiological parameter sensors connects described central processing unit by physiological parameter data Acquisition Circuit, described central processing unit adopts the self-adapting detecting method of any one physiological signal disclosed by the invention to carry out self-adapting detecting to the physiological parameter signals from described physiological parameter sensors, obtains filtered human physiology parameter signal.Conventionally, for gathering any physiological parameter signals with wave form varies, all can adopt the self-adapting detecting method of any one physiological signal disclosed by the invention to process.
Described physiological parameter sensors can comprise following any one or multiple sensors: EGC sensor, pressure transducer, heart rate sensor, blood oxygen transducer, blood glucose sensor and pulse wave sensor, by the date processing to pulse wave signal, can obtain a plurality of physiological parameters such as carrying out blood pressure, heart rate, pulse frequency.
On described matrix, can also be provided with for gathering the motion sensor of people's motor message, described motion sensor connects described central processing unit by exercise data acquisition circuit, and described central processing unit also can adopt the self-adapting detecting method of any one physiological signal disclosed by the invention to the processing mode of described people's motor message.
Described motion sensor can comprise following any one or multiple sensors: acceleration transducer, gyroscope, meter step sensor, fall signal transducer and geomagnetic sensor, utilize acceleration transducer can carry out moving state identification, meter step, motion tracking, sleep monitor, the action recognition of raising one's hand, fall detection and horizontal survey etc.; Utilize gyroscope can carry out azimuth detection etc.; Utilize geomagnetic sensor can carry out the measurements such as azimuthal orientation; By special-purpose meter step sensor and the signal transducer of falling, can realize meter step and fall signals collecting and warning.
On described matrix, can also be provided with the position sensor for collection position signal, described position sensor connects described central processing unit by placement data acquisition circuit, and described central processing unit also can adopt the self-adapting detecting method of any one physiological signal disclosed by the invention to the processing mode of described ambient signal.
Described position sensor can comprise following any one or multiple sensors: gps signal receptor and dipper system locating signal receiver, utilize gps signal receptor and dipper system locating signal receiver to position by receiving the framing signal of respective satellite navigation system.
On described matrix, can also be provided with for gathering the environment parameter sensing device of ambient signal, described environment parameter sensing device connects described central processing unit by environmental data collecting circuit, and described central processing unit also can adopt the self-adapting detecting method of any one physiological signal disclosed by the invention to the processing mode of described ambient signal.
Described environment parameter sensing device can comprise following any one or multiple sensors: temperature sensor, humidity sensor, baroceptor, UV sensor, gas composition sensor and optical sensor, utilize temperature, humidity, air pressure, uitraviolet intensity, gas componant and the concentration of these sensors in can testing environment and light sensation identification etc.
On described matrix, can also be provided with human-computer interaction device, voice output and image display device, described human-computer interaction device, voice output and image display device are all connected with described central processing unit, for carrying out output and the demonstration of artificial input and sound and image, described human-computer interaction device comprises button output device and/or touch-screen input device.
On described matrix, can also be provided with telecommunication circuit, described telecommunication circuit is connected with described central processing unit, for outside communicating by letter.
Described telecommunication circuit can comprise following any one or multiple telecommunication circuit: bluetooth communication circuit, WiFi telecommunication circuit, Mobile Communication Circuit and usb circuit, for carrying out communicating by letter of suitable way with external equipment, utilize USB can with local device (mobile terminal, PDA, notebook, computer, the relevant peripheral hardware such as intelligent television, Set Top Box) carry out wired interconnected, utilize bluetooth and WiFi can with local device carry out wireless interconnected, for family, individual health control, analysis.Utilize WiFi, mobile communication private network, mobile communication public network (2G, 3G, 4G), each supplemental characteristic can be dealt into long distance monitoring center.
The profile of described matrix is wrist-watch shape, is provided with watchband.
Described central processing unit can comprise signal input module, amplify synthesis module, signal output module, real-time analysis and prediction module and signal acquisition module, described signal input module is for the original data signal of receipt source corresponding data Acquisition Circuit, access the normal phase input end of described amplification synthesis module, described amplification synthesis module is to amplifying synthetic from positive terminal and end of oppisite phase input, form the output signal of certain amplification, and export by signal output module, conventionally can adopt operational amplifier, described signal acquisition module is for gathering the output of described amplification synthesis module, described real-time analysis and prediction module are carried out analysis and prediction according to the signal from described signal acquisition module, generate the interfering signal of approaching most and send into the inverting input of described amplification synthesis module, to offset the interfering signal in described original data signal.
The work process of described real-time analysis and prediction module is: first waveform morphology is analyzed, determine waveform morphology character, carry out signal templates correlation analysis simultaneously, waveform morphology analysis result and template analysis result are sent into small echo batten generation unit, by the interference small echo batten (interfering signal sequence) approaching most, send into noise cancellation, by adopting adaptive morphology analysis and adaptive wavelet, analyze, make system can pass through adaptive wavelet analyses and prediction interfering signal, thereby eliminate, disturb, and do not make distorted signals, adopt at present the mode of analog or digital filtering, all make signal produce distortion and delay, while is filtering noise completely.
Claims (10)
1. a self-adapting detecting method for physiological parameter, comprises the steps:
(1) gather human physiology parameter signal;
(2) described human physiology parameter signal is carried out to adaptive wavelet decomposition;
(3) carry out waveform analysis, eliminate the interfering signal composition in signal after decomposing, obtain the human physiology parameter signal of eliminating after disturbing,
In described step (2), comprise following steps:
(2.1) subdivision: signal sequence is divided into 2 parts by strange, even sample, wherein
Strange sample sequence X
p={ X
2k+1, k ∈ Z}, even sample sequence X
e={ X
2k, k ∈ Z};
(2.2) prediction: introduce predictive operator P, with
for even sample
estimated value
, definition detail signal d=
-
=
-
;
(2.3) upgrade: introduce and promote operator U, derive approximation signal s=X
e+ d/2=
.
2. the self-adapting detecting method of physiological parameter as claimed in claim 1, is characterized in that primary signal to carry out multilamellar decomposition.
3. the self-adapting detecting method of physiological parameter as claimed in claim 2, is characterized in that deriving wavelet function and scaling function according to predictor P and renovator U.
4. the self-adapting detecting method of the physiological parameter as described in claim 1,2 or 3, it is characterized in that being provided with many group predictive operators and promote operator, according to the local feature of the correlation detection between figure signal and adjacent signals and analytic signal, the optimum prediction operator of determining each conversion sample on each yardstick promotes operator, adopts described optimum prediction device and best renovator computational details signal d and approximation signal s.
5. the self-adapting detecting method of physiological parameter as claimed in claim 4, is characterized in that forecast period selects the different predictor of following 2 kinds of support Intervals as candidate predictor, for following (2, the 2) interpolating wavelet transform of the little employing of degree of association:
The improvement algorithm that the employing best interpolation that degree of association is large is estimated, determines detail signal d and approximation signal s in the following manner,
Introduce autocorrelation coefficient C
2and C (k)
6(k), described autocorrelation coefficient C
2and C (k)
6(k) adopt following manner to calculate:
Work as C
2(k)>=0 and C
6(k)>=C
2(k) time, the dependency between sample is stronger, conventionally can select following (6,6) interpolating wavelet:
，N=6；
，?N=6；
Wherein P=[1 1111 1]/6, U=[1 1111 1]/12;
Work as C
2(k)>=0 and C
6(k) <C
2(k), time, select following (4,2) interpolating wavelet transform:
，N=4；
，?N=2；
Wherein P=[1 11 1]/4, U=[1 1]/4;
Work as C
2(k) during <0, the dependency between sample a little less than, select following (2,2) interpolating wavelet transform:
。
6. the self-adapting detecting method of physiological parameter as claimed in claim 5, it is characterized in that described elimination decompose after specifically the comprising the steps: of interfering signal composition in signal
(3.1) the original physiologic parameter signal gathering is carried out to described adaptive wavelet decomposition, to decomposing postamble sequence, carry out waveform analysis, the original waveform feature that identification is relevant;
(3.2) introduce disturbing wave wave character, described disturbing wave wave character can obtain by following any one or various ways: (a) interfering signal being produced by interference factor is carried out to the adaptive wavelet identical with step (3.1) and decompose, waveform analysis is carried out in decomposition postamble sequence to disturbing wave, identifies relevant disturbing wave wave character: (b) according to the feature of interference factor by analysis or experiment obtain relevant disturbing wave wave character;
(3.3) the disturbing wave wave character of the original waveform feature obtaining in above-mentioned steps (3.1) and above-mentioned steps (3.2) introducing is analysed and compared, according to analyses and comparison result, from the decomposition postamble sequence of original physiologic parameter signal, identify and extract the interfering signal sequence causing because of interference factor;
(3.4) extracted interfering signal sequence inversion is added in primary signal, the interfering signal composition being caused by interference factor in counteracting and filtering primary signal thus.
7. a multi parameter intallingent is monitored hands table, comprise matrix, it is characterized in that described matrix is provided with central processing unit and for gathering the physiological parameter sensors of human physiology parameter signal, described physiological parameter sensors connects described central processing unit by physiological parameter data Acquisition Circuit, described central processing unit at least adopts the self-adapting detecting method of the physiological parameter as described in any one claim in claim 1-6 to process to a kind of human physiology parameter signal from described physiological parameter sensors, eliminate the interfering signal composition in signal after decomposing, obtain the human physiology parameter signal of eliminating after disturbing.
8. multi parameter intallingent as claimed in claim 7 is monitored wrist-watch, it is characterized in that being also provided with on described matrix motion sensor for gathering people's motor message, for the position sensor of collection position signal, for gathering environment parameter sensing device, human-computer interaction device, voice output, image display device and the telecommunication circuit of ambient signal, described motion sensor, position sensor and environment parameter sensing device are respectively by exercise data acquisition circuit, placement data acquisition circuit be connected described central processing unit by environmental data collecting circuit.
9. multi parameter intallingent as claimed in claim 8 is monitored wrist-watch, it is characterized in that described physiological parameter sensors comprises following any one or multiple sensors: EGC sensor, pressure transducer, heart rate sensor, blood oxygen transducer, blood glucose sensor and pulse wave sensor, by the date processing to pulse wave signal, obtain and carry out a plurality of physiological parameters such as blood pressure, heart rate, pulse frequency, described motion sensor comprises following any one or multiple sensors: acceleration transducer, gyroscope, meter step sensor, fall signal transducer and geomagnetic sensor, utilize acceleration transducer to carry out moving state identification, meter step, motion tracking, sleep monitor, the action recognition of raising one's hand, fall detection and horizontal survey etc., utilize gyroscope to carry out azimuth detection etc., utilize geomagnetic sensor to carry out the measurements such as azimuthal orientation, by special-purpose meter step sensor and the signal transducer of falling, realize meter step and signals collecting and warning, described position sensor comprises following any one or multiple sensors: gps signal receptor and dipper system locating signal receiver, utilize gps signal receptor and dipper system locating signal receiver to position by receiving the framing signal of respective satellite navigation system, described environment parameter sensing device comprises following any one or multiple sensors: temperature sensor, humidity sensor, baroceptor, UV sensor, gas composition sensor and optical sensor, utilize the temperature in these sensors sense environmental, humidity, air pressure, uitraviolet intensity, gas componant and concentration and light sensation identification etc., described telecommunication circuit comprises following any one or multiple telecommunication circuit: bluetooth communication circuit, WiFi telecommunication circuit, Mobile Communication Circuit and usb circuit.
10. multi parameter intallingent as claimed in claim 9 is monitored hands table, the profile that it is characterized in that described matrix is wrist-watch shape, be provided with watchband, described central processing unit comprises signal input module, amplify synthesis module, signal output module, real-time analysis and prediction module and signal acquisition module, described signal input module is for the original data signal of receipt source corresponding data Acquisition Circuit, access the normal phase input end of described amplification synthesis module, described amplification synthesis module is to amplifying synthetic from positive terminal and end of oppisite phase input, form the output signal of certain amplification, and export by signal output module, described signal acquisition module is for gathering the output of described amplification synthesis module, described real-time analysis and prediction module are carried out analysis and prediction according to the signal from described signal acquisition module, generate the interfering signal of approaching most and send into the inverting input of described amplification synthesis module, to offset the interfering signal in described original data signal, the work process of described real-time analysis and prediction module is: first waveform morphology is analyzed, determine waveform morphology character, carry out signal templates correlation analysis simultaneously, waveform morphology analysis result and template analysis result are sent into small echo batten generation unit, by the interference small echo batten (interfering signal sequence) approaching most, send into noise cancellation, by adopting adaptive morphology analysis and adaptive wavelet, analyze, make system can pass through adaptive wavelet analyses and prediction interfering signal, thereby eliminate, disturb, and do not make distorted signals.
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| CN107174260A (en) * | 2017-06-29 | 2017-09-19 | 叶子钰 | Healthy bracelet |
| CN108042106A (en) * | 2017-11-14 | 2018-05-18 | 李明 | Artificial intelligence deviation rectifying method for improving detection precision of human body sign non-invasive detection equipment |
| CN107808493A (en) * | 2017-11-24 | 2018-03-16 | 四川大学 | A kind of calling wrister in imminent danger based on BDS |
| CN107692992A (en) * | 2017-11-28 | 2018-02-16 | 苏州切思特电子有限公司 | A kind of human body monitoring system |
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