CN101868047A - Information transmission method of wireless body area network - Google Patents

Information transmission method of wireless body area network Download PDF

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Publication number
CN101868047A
CN101868047A CN 201010213993 CN201010213993A CN101868047A CN 101868047 A CN101868047 A CN 101868047A CN 201010213993 CN201010213993 CN 201010213993 CN 201010213993 A CN201010213993 A CN 201010213993A CN 101868047 A CN101868047 A CN 101868047A
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signal
human body
node
behavior pattern
area network
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CN101868047B (en
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李阳
刘伟
冯晶凌
王炜
钱良
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Shanghai Jiaotong University
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Shanghai Jiaotong University
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Abstract

The invention relates to an information transmission method of a wireless body area network in the technical field of wireless communication. The method comprises the following steps: a node A detecting a body to obtain a body physiological signal and diving the body physiological signal into a plurality of signal segments with length equal to signal period; sequentially conducting re-sampling processing, direct current offset elimination processing and amplitude conversion processing to the signal segments; conducting principal component analysis processing to the processed body physiological signal to obtain the current behavior information of the body; conducting judgment processing to the current behavior information of the body to obtain the next hop node candidate set of the node A; and selecting a node C closest to a target node B as a next hop node from the next hop node candidate set of the node A till the physiological information of the body is transmitted to the target node B. By adopting the method, the change of the body posture is monitored in real time, the nodes which cannot be used for communication are eliminated in advance before routing selection, the failed information transmission is avoided and the energy wastage caused by retransmission and the reselection of the next hop node is avoided.

Description

The information transferring method of wireless body area network
Technical field
What the present invention relates to is a kind of method of wireless communication technology field, specifically is a kind of information transferring method of the wireless body area network based on human body behavior recognition technology.
Background technology
Wireless body area network (Body Area Network) is developed by wireless sensor network (Wireless Sensor Network).It is in remote medical monitoring that a typical case of wireless body area network uses, the wireless sensor node that is placed on human body surface by subsides constitutes network, human body physiologic information and transmission are mutual, the health status of coming the remote monitoring human body at last by antenna transmission to medical centre.The energy of wireless senser is very limited, is close to human body surface again, so parameters such as the signal transmission power of wireless channel, data transfer bandwidth all will suffer restraints, the general mode of multi-hop relay that adopts is communicated by letter between node far away.Be subjected to the influence of human body to electro-magnetic wave absorption, different in the wireless channel in the wireless body area network and the free space.In addition, because wireless senser and human body are combined closely, the variation of human body attitude can cause the human body variation of wireless channel on every side.
Find by prior art documents, people such as Karp B are published in " Greedy PerimeterStateless Routing for Wireless Networks (the greedy edge stateless route of wireless network; GPSR method) " on the ACM magazine, have proposed a kind of wireless sensor network routing method based on distance.This method mainly is the relative position information by node, selects the neighbors of close destination node, as next-hop node to its transmission information.But this method need be known the relative position information of each node by additive method, and does not dynamically consider the influence of human body behavior to wireless channel.When human body attitude changes, the relative position information of node changes may influence the accuracy of method, and this node can't communicate with when selected next-hop node is blocked by human body, and information sends failure and retransmits and to the waste that all can cause energy of reselecting of next-hop node.
Summary of the invention
The objective of the invention is to overcome above-mentioned the deficiencies in the prior art, a kind of information transferring method of wireless body area network is proposed, by network route in the wireless body area network medical scene and human body behavior identification are combined, the change of monitoring human attitude in real time, dynamically upgrade the relative position information of node in the network according to human body attitude, taken into full account the influence of blocking of human body simultaneously to wireless channel, getting rid of in advance before carrying out Route Selection can not nodes in communication, avoids information to send failure and retransmits and reselect the energy dissipation that next-hop node causes.
The present invention is achieved by the following technical solutions, the present invention includes following steps:
Step 1 utilizes the node A in the wireless body area network that human body is detected, and obtains physiology signal, and physiology signal is divided into some signal segments that equate with the signal period.
Step 2, the physiology signal after obtaining handling is handled and the amplitude conversion process in resample successively processing, cancellation of DC offset to signal segment.
Described resampling is handled, and is meant: utilize DSP (Digital Signal Processing) technology, the signal that extracts is sampled again with scale factor M/L, wherein: M is that the standard sample in the one-period is counted, and L is that the actual samples of the signal that extracts is counted.
Described cancellation of DC offset is handled, and is meant: the signal that resamples is deducted a constant value C, and wherein: C is that all theoretical values of physiology signal are the mean value of actual value on zero the sampled point.
Described amplitude conversion process is meant: to the signal times of eliminating direct current offset with scale factor a/b, wherein: a is the peaked standard value of physiology signal amplitude, and b is the maximum of actual extracting signal amplitude.
Step 3 is carried out principal component analysis to the physiology signal after handling and is handled, and obtains the behavioural information of current human body.
Described principal component analysis is handled, and may further comprise the steps:
1) sets up human body behavior pattern sample storehouse, the physiology signal that to obtain every kind of duration under the human body behavior pattern be t;
2) according to the method for step 1 and step 2, to 1) physiology signal that obtains handles the signal after obtaining handling;
3) obtain the mean value and the covariance matrix of signal under every kind of human body behavior pattern, and obtain M characteristic value of the covariance matrix of signal under every kind of human body behavior pattern;
The mean value of signal under described every kind of human body behavior pattern is:
q i = 1 N i Σ j = 1 N i r ij ,
Wherein: q iBe the mean value of signal under the i kind human body behavior pattern, N iBe the number of the signal segment that comprises of i kind human body behavior pattern, r IjBe the signal after the processing of j segment signal in the i kind human body behavior pattern, 1≤i≤N, N are the numbers of human body behavior pattern in the human body behavior pattern sample storehouse, 1≤j≤N i
The covariance matrix of signal under described every kind of human body behavior pattern is:
C i = 1 N i Σ j = 1 N i r ij r ij T ,
Wherein: C iBe the covariance matrix of signal under the i kind human body behavior pattern, N iBe the number of the signal segment that comprises of i kind human body behavior pattern, r IjBe the signal after the processing of j segment signal in the i kind human body behavior pattern, 1≤i≤N, N are the numbers of human body behavior pattern in the human body behavior pattern sample storehouse, 1≤j≤N i
4) M characteristic value of the covariance matrix of signal under every kind of human body behavior pattern arranged according to order from big to small, i kind human body behavior pattern is chosen the K of its front iIndividual characteristic value, its pairing characteristic vector is formed matrix E i = [ e i 1 , e i 2 , · · · , e iK i ] ;
5) human body signal after the processing that step 2 is obtained carries out error analysis and handles, and obtains itself and the error of the signal of every kind of human body behavior pattern, the behavioural information that the pairing human body behavior pattern of error of minimum is exactly current human body.
Described error analysis is handled, and is:
e i＝|p i-p i′| 2，
Wherein: p i=r-q i,
p i ′ = ( E i E i T ) p i ,
e iBe the error of the signal of human body signal after the processing that obtains of step 2 and i kind human body behavior pattern, r is the human body signal after the processing that obtains of step 2.
Step 4 is carried out judgment processing to the behavioural information of current human body, obtains the next-hop node Candidate Set of node A.
Described judgment processing may further comprise the steps:
1) sets up look-up table, obtain each internodal position relation and correspondence under every kind of behavior pattern of human body;
2) after identifying the behavior pattern of current human body, the search look-up table, the position that obtains each node and node A under the current behavior pattern concerns and correspondence;
3) there is the node of direct communication relation to list in the next-hop node Candidate Set of node A all and node A.
Step 5, in the next-hop node Candidate Set of node A, choose the node C nearest with target node b, the detected Human Physiology information of node A is passed to node C, again according to the method for step 4 and step 5, obtain the next-hop node of node C, until the physiologic information of human body is passed to target node b.
Compared with prior art, the present invention has following beneficial effect:
1, discerns the change of monitoring human attitude in real time by the human body behavior, dynamically upgrade the relative position information of wireless body area network node, can guarantee the validity that follow-up route is handled according to the current attitude of human body.
2, taken into full account the influence of human body to wireless channel, but make node calculate nodes in communication on every side by this locality, carry out route handle front-seat removing can not nodes in communication, avoid information to send failure and retransmit, and reselect the energy dissipation that next-hop node brings, prolong the life span of node.
Embodiment
Below embodiments of the invention are elaborated: present embodiment is being to implement under the prerequisite with the technical solution of the present invention, provided detailed execution mode and concrete operating process, but protection scope of the present invention is not limited to following embodiment.
Embodiment
Total A in the wireless body area network of present embodiment 1, A 2..., A 7Seven wireless sensor nodes lay respectively at neck, chest, left side waist, right side waist, left finesse, right finesse and back, wherein: A 2Be the Centroid of wireless body area network, responsible whole wireless body area network is communicated by letter A with external network 6Be an ECG (electrocardiogram) node, be responsible for measuring human body ECG signal, because channel obviously increases with the decay that distance increases signal around the human body, so each internodal distance is controlled in the 40cm.Can only communicate by letter by the mode of multi-hop relay between the non-conterminous node, adjacent node direct single-hop communication when not being subjected to human body and blocking, but when being subjected to human body and blocking, also can only communicate by letter by the mode of multi-hop relay.In the present embodiment with ECG node A 6For example is operated.
Present embodiment comprises the steps:
Step 1 is utilized the wireless sensor node A in the wireless body area network 6Human body is detected, obtain physiology signal, physiology signal is divided into some signal segments that equate with the signal period.
A in the present embodiment 6Sampling rate with 256Hz detects the ECG signal, obtains the sampling number L of one-period by the distance between former and later two peak value sampling points, and extracting the duration is one-period, and length is the signal of L, and makes peak point middle.
Step 2, the physiology signal after obtaining handling is handled and the amplitude conversion process in resample successively processing, cancellation of DC offset to signal segment.
Described resampling is handled, and is meant: utilize the DSP technology, the signal that extracts is sampled again with scale factor M/L, wherein: M is that the standard sample in the one-period is counted, and L is that the actual samples of the signal that extracts is counted.
Described cancellation of DC offset is handled, and is meant: the signal that resamples is deducted a constant value C, and wherein: C is that all theoretical values of physiology signal are the mean value of actual value on zero the sampled point.
C is the mean value of all sampled values between the P ripple end of ECG signal of actual extracting and the beginning of Q ripple in the present embodiment.
Described amplitude conversion process is meant: to the signal times of eliminating direct current offset with scale factor a/b, wherein: a is the peaked standard value of physiology signal amplitude, and b is the maximum of actual extracting signal amplitude.
Step 3 is carried out principal component analysis to the physiology signal after handling and is handled, and obtains the behavioural information of current human body.
Described principal component analysis is handled, and may further comprise the steps:
1) sets up human body behavior pattern sample storehouse, the physiology signal that to obtain every kind of duration under the pattern be t;
The human body behavior pattern sample storehouse that present embodiment is set up comprises: stand, sit down, lie low, lie on one's side left, lie on one's side to the right, right arm swings to the place ahead, right arm swings to the rear, left arm swings to the place ahead, left arm swings to rear etc.
2), be that the physiology signal of t is handled the signal after obtaining handling to the duration under every kind of pattern according to the method for step 1 and step 2;
3) obtain the mean value and the covariance matrix of signal under every kind of human body behavior pattern, and obtain M characteristic value of the covariance matrix of signal under every kind of human body behavior pattern,
The mean value of signal under described every kind of human body behavior pattern is:
q i = 1 N i Σ j = 1 N i r ij ,
Wherein: q iBe the mean value of signal under the i kind human body behavior pattern, N iBe the number of the signal segment that comprises of i kind human body behavior pattern, r IjBe the signal after the processing of j segment signal in the i kind human body behavior pattern, 1≤i≤N, N are the numbers of human body behavior pattern in the human body behavior pattern sample storehouse, 1≤j≤N i
The covariance matrix of signal under described every kind of human body behavior pattern is:
C i = 1 N i Σ j = 1 N i r ij r ij T ,
Wherein: C iBe the covariance matrix of signal under the i kind human body behavior pattern, N iBe the number of the signal segment that comprises of i kind human body behavior pattern, r IjBe the signal after the processing of j segment signal in the i kind human body behavior pattern, 1≤i≤N, N are the numbers of human body behavior pattern in the human body behavior pattern sample storehouse, 1≤j≤N i
4) M characteristic value of the covariance matrix of signal under every kind of human body behavior pattern arranged according to order from big to small, human body behavior pattern among the i is chosen the K of its front iIndividual characteristic value, its pairing characteristic vector is formed matrix E i = [ e i 1 , e i 2 , . . . , e ik i ] ;
K in the present embodiment i=5.
5) human body signal after the processing that step 2 is obtained carries out error analysis and handles, and obtains itself and the error of the signal of every kind of human body behavior pattern, the behavioural information that the pairing human body behavior pattern of error of minimum is exactly current human body.
Described error analysis is handled, and is:
e i＝|p i-p i′| 2，
Wherein: p i=r-q i,
p i ′ = ( E i E i T ) p i ,
e iBe the error of the signal of human body signal after the processing that obtains of step 2 and i kind human body behavior pattern, r is the human body signal after the processing that obtains of step 2.
The current behavior pattern of the human body that obtains in the present embodiment is: right arm swings to the place ahead.
Step 4 is carried out judgment processing to the behavioural information of current human body, obtains node A 6The next-hop node Candidate Set.
Described judgment processing may further comprise the steps:
1) sets up look-up table, obtain each internodal position relation and correspondence under every kind of behavior pattern of human body;
2) after identifying the behavior pattern of current human body, the search look-up table obtains each node and node A under the current behavior pattern 6Position relation and correspondence;
3) with all and node A 6There is the node of direct communication relation to list node A in 6The next-hop node Candidate Set.
The current behavior pattern of human body is in the present embodiment: right arm swings to the place ahead, then A 6The next-hop node Candidate Set that the node searching look-up table obtains is: A 1, A 2And A 4
Step 5 adopts the GPSR method, at wireless sensor node A 6The next-hop node Candidate Set in choose and destination node A 2Nearest node, i.e. A 2, with wireless sensor node A 6Detected Human Physiology information is directly passed to destination node A 2Thereby, finish the message transmission of unlimited body area network.
Present embodiment is by combining network route in the wireless body area network medical scene and human body behavior identification, the change of monitoring human attitude in real time, dynamically upgrade the relative position information of node in the network according to human body attitude, taken into full account the influence of blocking of human body simultaneously to wireless channel, getting rid of in advance before carrying out Route Selection can not nodes in communication, avoids information to send failure and retransmits and reselect the energy dissipation that next-hop node causes.

Claims (9)

1. the information transferring method of a wireless body area network is characterized in that, may further comprise the steps:
Step 1 utilizes the node A in the wireless body area network that human body is detected, and obtains physiology signal, and physiology signal is divided into some signal segments that equate with the signal period;
Step 2, the physiology signal after obtaining handling is handled and the amplitude conversion process in resample successively processing, cancellation of DC offset to signal segment;
Step 3 is carried out principal component analysis to the physiology signal after handling and is handled, and obtains the behavioural information of current human body;
Step 4 is carried out judgment processing to the behavioural information of current human body, obtains the next-hop node Candidate Set of node A;
Step 5, in the next-hop node Candidate Set of node A, choose the node C nearest with target node b, the detected Human Physiology information of node A is passed to node C, again according to the method for step 4 and step 5, obtain the next-hop node of node C, until the physiologic information of human body is passed to target node b.
2. the information transferring method of wireless body area network according to claim 1, it is characterized in that, resampling described in the step 2 is handled, be meant: utilize the DSP technology, the signal that extracts is sampled again with scale factor M/L, wherein: M is that the standard sample in the one-period is counted, and L is that the actual samples of the signal that extracts is counted.
3. the information transferring method of wireless body area network according to claim 1, it is characterized in that, cancellation of DC offset described in the step 2 is handled, be meant: the signal that resamples is deducted a constant value C, and wherein: C is that all theoretical values of physiology signal are the mean value of actual value on zero the sampled point.
4. the information transferring method of wireless body area network according to claim 1, it is characterized in that, amplitude conversion process described in the step 2, be meant: to the signal times of eliminating direct current offset with scale factor a/b, wherein: a is the peaked standard value of physiology signal amplitude, and b is the maximum of actual extracting signal amplitude.
5. the information transferring method of wireless body area network according to claim 1 is characterized in that, the principal component analysis described in the step 3 is handled, and may further comprise the steps:
1) sets up human body behavior pattern sample storehouse, the physiology signal that to obtain every kind of duration under the human body behavior pattern be t;
2) according to the method for step 1 and step 2, to 1) physiology signal that obtains handles the signal after obtaining handling;
3) obtain the mean value and the covariance matrix of signal under every kind of human body behavior pattern, and obtain M characteristic value of the covariance matrix of signal under every kind of human body behavior pattern, wherein: M is that the standard sample in the one-period is counted;
4) M characteristic value of the covariance matrix of signal under every kind of human body behavior pattern arranged according to order from big to small, i kind human body behavior pattern is chosen the K of its front iIndividual characteristic value, its pairing characteristic vector is formed matrix E i = [ e i 1 , e i 2 , . . . , e ik i ] ;
5) human body signal after the processing that step 2 is obtained carries out error analysis and handles, and obtains itself and the error of the signal of every kind of human body behavior pattern, the behavioural information that the pairing human body behavior pattern of error of minimum is exactly current human body.
6. the information transferring method of wireless body area network according to claim 5 is characterized in that, the mean value of signal under described every kind of human body behavior pattern is:
q i = 1 N i Σ j = 1 N i r ij ,
Wherein: q iBe the mean value of signal under the i kind human body behavior pattern, N iBe the number of the signal segment that comprises of i kind human body behavior pattern, r IjBe the signal after the processing of j segment signal in the i kind human body behavior pattern, 1≤i≤N, N are the numbers of human body behavior pattern in the human body behavior pattern sample storehouse, 1≤j≤N i
7. the information transferring method of wireless body area network according to claim 5 is characterized in that, the covariance matrix of signal under described every kind of human body behavior pattern is:
C i = 1 N i Σ j = 1 N i r ij r ij T ,
Wherein: C iBe the covariance matrix of signal under the i kind human body behavior pattern, N iBe the number of the signal segment that comprises of i kind human body behavior pattern, r IjBe the signal after the processing of j segment signal in the i kind human body behavior pattern, 1≤i≤N, N are the numbers of human body behavior pattern in the human body behavior pattern sample storehouse, 1≤j≤N i
8. the information transferring method of wireless body area network according to claim 5 is characterized in that, described error analysis is handled, and is:
e i＝|p i-p i′| 2，
Wherein: p i=r-q i,
p i ′ = ( E i E i T ) p i ,
e iBe the error of the signal of human body signal after the processing that obtains of step 2 and i kind human body behavior pattern, r is the human body signal after the processing that obtains of step 2.
9. the information transferring method of wireless body area network according to claim 1 is characterized in that, the judgment processing described in the step 4 may further comprise the steps:
1) sets up look-up table, obtain each internodal position relation and correspondence under every kind of behavior pattern of human body;
2) after identifying the behavior pattern of current human body, the search look-up table, the position that obtains each node and node A under the current behavior pattern concerns and correspondence;
3) there is the node of direct communication relation to list in the next-hop node Candidate Set of node A all and node A.
CN 201010213993 2010-06-30 2010-06-30 Information transmission method of wireless body area network Expired - Fee Related CN101868047B (en)

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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102178529A (en) * 2011-03-11 2011-09-14 清华大学 Body area network-based respiratory disease remote diagnosis monitoring system
CN103326791A (en) * 2013-05-16 2013-09-25 吉林大学 Physiological data collection method used for telemedicine
CN103391594A (en) * 2012-05-09 2013-11-13 电信科学技术研究院 Wireless body area network routing optimization method and device
CN109219101A (en) * 2018-09-21 2019-01-15 南京理工大学 Method for routing foundation based on Double moving average predicted method in wireless body area network
CN112512092A (en) * 2020-11-03 2021-03-16 中国科学院深圳先进技术研究院 Multi-node human body communication networking method and device

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CN101674573A (en) * 2009-09-30 2010-03-17 西安电子科技大学 Security awakening device and method for wireless body area network sensing node

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Publication number Priority date Publication date Assignee Title
US20090005016A1 (en) * 2007-06-29 2009-01-01 Betty Eng Apparatus and method to maintain a continuous connection of a cellular device and a sensor network
CN101674573A (en) * 2009-09-30 2010-03-17 西安电子科技大学 Security awakening device and method for wireless body area network sensing node

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102178529A (en) * 2011-03-11 2011-09-14 清华大学 Body area network-based respiratory disease remote diagnosis monitoring system
CN103391594A (en) * 2012-05-09 2013-11-13 电信科学技术研究院 Wireless body area network routing optimization method and device
CN103391594B (en) * 2012-05-09 2016-08-03 电信科学技术研究院 A kind of method and device of wireless body area network routing optimality
CN103326791A (en) * 2013-05-16 2013-09-25 吉林大学 Physiological data collection method used for telemedicine
CN103326791B (en) * 2013-05-16 2015-08-05 吉林大学 A kind of physiological data collection method for tele-medicine
CN109219101A (en) * 2018-09-21 2019-01-15 南京理工大学 Method for routing foundation based on Double moving average predicted method in wireless body area network
CN109219101B (en) * 2018-09-21 2021-09-10 南京理工大学 Route establishing method based on quadratic moving average prediction method in wireless body area network
CN112512092A (en) * 2020-11-03 2021-03-16 中国科学院深圳先进技术研究院 Multi-node human body communication networking method and device
CN112512092B (en) * 2020-11-03 2023-03-24 中国科学院深圳先进技术研究院 Multi-node human body communication networking method and device

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