A method and system for data transmission under body networking

Abstract

The application relates to the technical field of data transmission, and particularly discloses a data transmission method and system for body networking, which comprises the following steps: step S1: deploying sensors on a user's limbs to collect limb motion data in real time; dividing a data transmission path, calculating total path loss; generating a motion change curve according to the limb data and generating a loss change curve according to the path loss; step S2: setting a loss threshold, dividing a high interval and a low interval of the loss curve; introducing a signal coefficient, generating a segmented function, and defining a transmission period in different intervals; step S3: when the user is moving, updating the limb data in real time and generating a current motion change curve; comparing the historical and current motion curves, calculating a period ratio; scaling the signal period segmented function according to the period ratio, obtaining a current segmented function, and re-dividing the high and low intervals; setting a low-frequency threshold and a high-frequency threshold, and dynamically adjusting the transmission rate according to the new interval.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data transmission, in particular to a data transmission method and system for body networking. BACKGROUND

[0002] Body networking refers to the connection of the human body and digital technology through various sensors and networks in information physical systems (CPS) to achieve the collection, analysis and application of health data, providing new possibilities for personalized healthcare services.

[0003] In body networking, edge devices (such as wearable devices, sensor nodes, etc.) are responsible for collecting physiological data of the human body, and edge data transmission of body networking is to perform preliminary processing and transmission of data on the side close to the human body or data source.

[0004] Under the existing technical framework, body networking devices such as various wearable sensors and implantable medical devices are often designed to be small in size and low in power consumption. The main design concept is to ensure that these devices can be easily worn or implanted in the human body and will not cause excessive burden or discomfort to the user during long-term use. However, due to the small size and low power consumption characteristics, these devices face many limitations in computing power, storage capacity, and battery life. Body networking devices usually do not have powerful processors and complex computing architectures like traditional computers. Their computing resources are relatively limited and difficult to handle data processing tasks that require a lot of computing and complex algorithms.

[0005] In addition, devices in body networking are also easily affected by human motion, environmental interference and other factors during actual use, which leads to unstable data transmission. Human motion is a common interference factor. When the user is in intense motion, the device may shake and shift, affecting signal reception and transmission. For example, during running, a wearable device worn on the arm may change the antenna direction due to arm swing, resulting in weakened or interrupted signal strength. SUMMARY

[0006] The purpose of the present application is to provide a data transmission method and system for body networking to solve the above technical problems.

[0007] The purpose of the present application can be achieved by the following technical solutions:

[0008] A data transmission method for body networking, comprising the following steps:

[0009] Step S1: setting a monitoring point at a user's limb, acquiring and transmitting limb data through the monitoring point; acquiring a transmission path, dividing the transmission path, and obtaining path total loss data; generating a motion change curve according to the limb data, and generating a loss change curve according to the path total loss data;

[0010] Step S2: setting a loss threshold and obtaining a threshold line; obtaining a high interval and a low interval on the loss change curve according to the threshold line; setting a signal coefficient and generating a signal period segmentation function according to the high interval and the low interval;

[0011] Step S3: if the current user starts to move, acquiring current limb data in real time; generating a current motion change curve according to the current limb data; obtaining a period ratio according to the motion change curve and the current motion change curve; scaling the signal period segmentation function according to the period ratio to obtain a current signal period segmentation function, and obtaining a current low interval and a current high interval;

[0012] Setting a low frequency threshold and a high frequency threshold, and adjusting the transmission rate of the monitoring point according to the current low interval and the current high interval.

[0013] As a further scheme of the present application: the limb data is the displacement distance of the limb at each time, and the displacement distance is the height of the limb from the horizontal surface.

[0014] As a further scheme of the present application: the acquisition process of the transmission path includes:

[0015] Acquiring a signal receiving end and taking the monitoring point as a signal sending end, obtaining a transmission path according to the signal receiving end and the signal sending end.

[0016] As a further scheme of the present application: the obtaining process of the path total loss data includes:

[0017] Dividing the transmission path, acquiring a transmission path segment blocked by the user's body on the transmission path, denoted as a human body interference segment, and acquiring a transmission path segment other than the human body interference segment on the transmission path, denoted as an environmental interference segment; acquiring the path loss of the human body interference segment, denoted as human body loss, and acquiring the path loss of the environmental interference segment, denoted as environmental loss; adding the human body loss and the environmental loss to obtain the path total loss of the transmission path; obtaining path total loss data according to the path total loss at each time.

[0018] As a further scheme of the present application: the obtaining process of the high interval and the low interval includes:

[0019] The loss threshold is denoted as PLt, and the ordinate of the loss change curve is denoted as PL, so that a threshold line PL=PLt is obtained; on the loss change curve, a curve segment below the threshold line is obtained and denoted as a high signal segment, and a curve segment above the threshold line is obtained and denoted as a low signal segment; the abscissa interval corresponding to the high signal segment is obtained and denoted as a high interval, and the abscissa interval corresponding to the low signal segment is obtained and denoted as a low interval.

[0020] As a further scheme of the present application, the generation process of the signal period segmentation function comprises:

[0021] A signal coefficient is set, the signal coefficient of the high interval is set as 1, and the signal coefficient of the low interval is set as 0; a coordinate system is established with the signal coefficient as the ordinate and the number of time as the abscissa, and a signal period segmentation function is generated.

[0022] As a further scheme of the present application, the obtaining process of the period ratio comprises:

[0023] The period of the motion change curve is obtained and denoted as a standard motion period, and the period of the current motion change curve is obtained and denoted as a current motion period; the period ratio P=Ty´ / Ty, wherein Ty represents the standard motion period, and Ty´ represents the current motion period.

[0024] As a further scheme of the present application, the process of adjusting the transmission rate of the monitoring point comprises:

[0025] When entering the current low interval, the transmission rate of the monitoring point is adjusted to the low frequency threshold, and when entering the current high interval, the transmission rate of the monitoring point is adjusted to the high frequency threshold.

[0026] As a further scheme of the present application, a data transmission system used in body networking comprises:

[0027] A data acquisition module: setting a monitoring point at a user's limb, acquiring and transmitting limb data through the monitoring point, acquiring a transmission path, dividing the transmission path, and obtaining path total loss data, generating a motion change curve according to the limb data, and generating a loss change curve according to the path total loss data;

[0028] A signal strength division module: setting a loss threshold and obtaining a threshold line, obtaining a high interval and a low interval on the loss change curve according to the threshold line, setting a signal coefficient, and generating a signal period segmentation function according to the high interval and the low interval;

[0029] The transmission rate adjusting module: if the current user starts to move, real-time current limb data is obtained; according to the current limb data, a current motion change curve is generated; according to the motion change curve and the current motion change curve, a period ratio is obtained; according to the period ratio, the signal period segmentation function is scaled to obtain a current signal period segmentation function, and a current low interval and a current high interval are obtained;

[0030] The low frequency threshold and the high frequency threshold are set, and the transmission rate of the monitoring point is adjusted according to the current low interval and the current high interval.

[0031] The beneficial effects of the present application are:

[0032] The present application dynamically adjusts the transmission strategy by simultaneously analyzing the motion change curve (user behavior) and the loss change curve (channel quality), significantly improving the reliability of data transmission; mainly including: high loss interval (such as during vigorous exercise): reduce the transmission rate to reduce packet loss; low loss interval (such as in a stationary state): increase the transmission rate to enhance real-time performance; avoid energy waste caused by fixed rate transmission, prolong the device endurance, and improve resource utilization; the present application divides the transmission path into human interference section and environmental interference section, respectively calculates the loss and accumulates, more accurately reflects the actual channel state; according to the real-time channel state, the high and low frequency thresholds are switched, which effectively deals with sudden interference; through period ratio scaling (rather than complex algorithm) to dynamically adjust the transmission period, which is suitable for the limited computing power of body networking devices; in summary, the present application solves the stability, energy efficiency and real-time performance contradiction of data transmission in body networking through behavior-channel joint optimization and lightweight dynamic control, especially suitable for resource-limited and environmentally variable medical health scenarios. BRIEF DESCRIPTION OF DRAWINGS

[0033] The present application will be further described below with reference to the accompanying drawings.

[0034] Figure 1 It is a flowchart of a data transmission method for body networking according to the present application. DETAILED DESCRIPTION

[0035] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0036] Please refer to Figure 1 The present application is a data transmission method for body networking, including the following steps:

[0037] Step S1: setting a monitoring point at a user's limb, the monitoring point being used to acquire and transmit limb data, the limb data being a displacement distance of the limb at each time; acquiring a signal receiving end, and taking the monitoring point as a signal sending end, obtaining a transmission path according to the signal receiving end and the signal sending end; dividing the transmission path into a human body interference section and an environmental interference section, and obtaining a total path loss of the transmission path according to the human body interference section and the environmental interference section; obtaining path total loss data according to the total path loss at each time; generating a motion change curve according to the limb data, and generating a loss change curve according to the path total loss data;

[0038] As a preferred embodiment of the present application, the time obtaining process comprises:

[0039] Setting a monitoring time interval threshold, acquiring a starting time of the user, the starting time being a time when the user starts to move; starting from the starting time, obtaining a time every monitoring time interval threshold;

[0040] As a preferred embodiment of the present application, the displacement distance is a height of the limb from the ground;

[0041] As a preferred embodiment of the present application, the limb is a leg or an arm;

[0042] As a preferred embodiment of the present application, the transmission path dividing process comprises:

[0043] Obtaining a transmission path section on the transmission path that is blocked by the user's body, denoted as a human body interference section; and obtaining a transmission path section on the transmission path other than the human body interference section, denoted as an environmental interference section;

[0044] As a preferred embodiment of the present application, the total path loss obtaining process comprises:

[0045] Obtaining a path loss of the human body interference section, denoted as a human body loss, and obtaining a path loss of the environmental interference section, denoted as an environmental loss; accumulating the human body loss and the environmental loss to obtain a total path loss;

[0046] As a preferred embodiment of the present application, the motion change curve generating process comprises:

[0047] Sequentially numbering each time, taking the time number as the horizontal coordinate and the displacement distance as the vertical coordinate to establish a rectangular coordinate system; converting each numbered time and its corresponding displacement distance into a coordinate point at a corresponding position on the rectangular coordinate system, connecting each coordinate point with a smooth curve, and taking the curve as a motion change curve; similarly, the loss change curve is generated;

[0048] It is worth noting that since there are several types of motion, the motion change curves collected by different types of motion are different, that is, one type of motion corresponds to one type of motion change curve, to realize multi-motion type compatibility; the types of motion include skipping, running, swimming and pull-ups;

[0049] In body networking monitoring, the user's limb movement (such as walking, running) usually shows quasi-periodicity, and the motion change curve has the following characteristics:

[0050] Approximate periodicity: the curve waveform presents a repeating pattern similar to a sine wave or a pulse wave in the time domain (such as the swing-support phase cycle in the gait cycle);

[0051] Non-strict periodicity: due to changes in exercise intensity, individual differences or environmental interference, the length and amplitude of the cycle may have slight fluctuations;

[0052] It can be understood that by deploying sensors (such as accelerometers, gyroscopes) on the limbs (such as arms, legs), the displacement distance (such as the change in height of the limb relative to the horizontal ground) is monitored in real time, and the user's motion state is quantified; the signal of the human body interference segment is blocked or reflected by the human body tissue (such as signal attenuation caused by trunk blocking), and the path part of the environmental interference segment is regularly affected by the external environment (such as Wi-Fi, Bluetooth interference);

[0053] The human body loss is obtained based on a radio frequency propagation model (such as a Log-distance model), and the attenuation of a 2.4GHz frequency band in muscle is about 3-6dB / cm; the environmental loss is based on environmental noise measurement (such as RSSI);

[0054] The motion change curve reflects the time domain characteristics of the user's motion (such as periodic running gait), and the loss change curve dynamically represents the channel quality (such as periodic fluctuation of loss caused by limb blocking during motion);

[0055] It should be noted that the traditional method only processes motion data or channel state alone, while the present application generates motion curve and loss curve synchronously, reveals the correlation between the two (for example: the corresponding relationship between arm swing frequency and signal attenuation peak), and provides a basis for subsequent dynamic transmission strategy; by path segmentation modeling, the influence of human body and environmental interference is distinguished, avoiding the limitations of a single channel model; for example, in the swimming scenario, environmental interference (water absorption) dominates; in the running scenario, human body interference (limb blocking) is more significant;

[0056] Step S2: Set a loss threshold, obtain a threshold line according to the loss threshold, and on the loss change curve, obtain a curve segment below the threshold line, denoted as a high signal segment, and obtain a curve segment above the threshold line, denoted as a low signal segment;

[0057] obtain the horizontal coordinate interval corresponding to the high signal segment, denoted as high interval, and obtain the horizontal coordinate interval corresponding to the low signal segment, denoted as low interval; set a signal coefficient, and set the signal coefficient of the high interval as 1 and the signal coefficient of the low interval as 0; establish a coordinate system with the signal coefficient as the vertical coordinate and the number of the time as the horizontal coordinate, and generate a signal period segmentation function;

[0058] As a preferred embodiment of the present application, the threshold line obtaining process comprises:

[0059] denote the loss threshold as PLt, and denote the vertical coordinate of the loss change curve as PL, so that the threshold line PL=PLt is obtained;

[0060] It can be understood that a preset loss threshold is set to divide the loss change curve into two intervals: a low signal segment (PL>PLt): the channel loss is higher than the threshold, and the signal quality is poor (for example, the user's shielding increases due to intense movement); and a high signal segment (PL≤PLt): the channel loss is lower than the threshold, and the signal quality is stable;

[0061] Step S3: if the current user starts to move, real-time acquisition of the body data of the current user is performed, denoted as current body data; a movement change curve is generated according to the current body data, denoted as current movement change curve;

[0062] obtain the period of the movement change curve, denoted as standard movement period; obtain the period of the current movement change curve, denoted as current movement period, obtain a period ratio according to the current movement period and the standard movement period; scale the signal period segmentation function according to the period ratio to obtain a current signal period segmentation function, and obtain a current low interval and a current high interval according to the current signal period segmentation function;

[0063] set a low frequency threshold and a high frequency threshold, when entering the current low interval, adjust the transmission rate of the monitoring point to the low frequency threshold, and when entering the current high interval, adjust the transmission rate of the monitoring point to the high frequency threshold;

[0064] As a preferred embodiment of the present application, the standard movement period obtaining process comprises:

[0065] perform Fourier transform on the movement change curve to convert the movement change curve into a frequency domain signal, obtain a main frequency fpeak according to the frequency domain signal, and then obtain the standard movement period Ty=1 / fpeak;

[0066] As a preferred embodiment of the present application, the period ratio P = Ty' / Ty, wherein Ty represents a standard motion period, and Ty' represents a current motion period.

[0067] It can be understood that the signal period segmentation function is time axis scaled by a period ratio (P), if P > 1, the function is stretched horizontally (high / low interval time is extended), if P < 1, the function is compressed horizontally (high / low interval time is shortened); for example: when the user runs (P = 0.5), the original high interval is shortened from 2 seconds to 1 second.

[0068] As a preferred embodiment of the present application, in the current signal period segmentation function, the horizontal coordinate interval occupied by the function segment with a signal coefficient of 1 is recorded as a current high interval, and the horizontal coordinate interval occupied by the function segment with a signal coefficient of 0 is recorded as a current low interval.

[0069] A data transmission system for body networking, comprising:

[0070] A data acquisition module: setting a monitoring point at the user's limb, acquiring and transmitting limb data through the monitoring point; acquiring a transmission path, dividing the transmission path, and obtaining path total loss data; generating a motion change curve according to the limb data, and generating a loss change curve according to the path total loss data;

[0071] A signal strength division module: setting a loss threshold and obtaining a threshold line; obtaining a high interval and a low interval on the loss change curve according to the threshold line; setting a signal coefficient and generating a signal period segmentation function according to the high interval and the low interval;

[0072] A transmission rate adjustment module: if the current user starts to move, real-time acquisition of current limb data; generating a current motion change curve according to the current limb data; obtaining a period ratio according to the motion change curve and the current motion change curve; scaling the signal period segmentation function according to the period ratio to obtain a current signal period segmentation function, and obtaining a current low interval and a current high interval;

[0073] Setting a low frequency threshold and a high frequency threshold, and adjusting the transmission rate of the monitoring point according to the current low interval and the current high interval.

[0074] It should be noted that the conventional method uses fixed rate transmission, which wastes energy, and the present application dynamically adjusts the rate transmission, which improves the endurance by more than 30%; when the user moves violently, the transmission rate is adaptively reduced, and the packet loss rate is reduced by 50%; through human body interference segment loss prediction, the signal interruption risk is avoided in advance, the daily average power consumption is reduced by 40%, and the demand for 7-day continuous monitoring is met.

[0075] The above has been described in detail one embodiment of the present application, but the content is only the preferred embodiment of the present application, cannot be considered for limiting the scope of the present application. Any equivalent changes and improvements made in the scope of the present application, should still belong to the scope of the present application.

Claims

1. A method for data transmission under body networking, characterized in that, The method comprises the following steps: Step S1: setting a monitoring point at the user's limb, acquiring and transmitting limb data through the monitoring point; acquiring a transmission path, dividing the transmission path, and obtaining path total loss data; generating a motion change curve according to the limb data, and generating a loss change curve according to the path total loss data; Step S2: setting a loss threshold and obtaining a threshold line; obtaining a high interval and a low interval on the loss change curve according to the threshold line; setting a signal coefficient, and generating a signal period segmentation function according to the high interval and the low interval; Step S3: if the current user starts to move, acquiring current limb data in real time; generating a current motion change curve according to the current limb data; obtaining a period ratio according to the motion change curve and the current motion change curve; scaling the signal period segmentation function according to the period ratio to obtain a current signal period segmentation function, and obtaining a current low interval and a current high interval; setting a low frequency threshold and a high frequency threshold, and adjusting the transmission rate of the monitoring point according to the current low interval and the current high interval; In step S2, the process of obtaining the high interval and the low interval comprises: Let the loss threshold be denoted as PL t Let the ordinate of the loss change curve be denoted as PL, and a threshold line PL=PL is obtained t On the loss change curve, a curve segment below the threshold line is obtained, denoted as a high signal segment, and a curve segment above the threshold line is obtained, denoted as a low signal segment; an abscissa interval corresponding to the high signal segment is obtained, denoted as a high interval, and an abscissa interval corresponding to the low signal segment is obtained, denoted as a low interval; In step S3, the process of adjusting the transmission rate of the monitoring point comprises: When entering the current low interval, the transmission rate of the monitoring point is adjusted to the low frequency threshold, and when entering the current high interval, the transmission rate of the monitoring point is adjusted to the high frequency threshold.

2. The data transmission method for body networking according to claim 1, wherein, In step S1, the limb data is the displacement distance of the limb at each time, and the displacement distance is the height of the limb from the horizontal surface.

3. The data transmission method for body networking according to claim 1, wherein, In step S1, the process of acquiring the transmission path comprises: acquiring a signal receiving end, taking the monitoring point as a signal sending end, and obtaining a transmission path according to the signal receiving end and the signal sending end.

4. The data transmission method for body networking according to claim 1, wherein, In step S1, the process of obtaining the path total loss data comprises: dividing the transmission path, acquiring a transmission path segment blocked by the user's body on the transmission path, denoted as a human body interference segment, and acquiring a transmission path segment other than the human body interference segment on the transmission path, denoted as an environmental interference segment; acquiring the path loss of the human body interference segment, denoted as human body loss, and acquiring the path loss of the environmental interference segment, denoted as environmental loss; adding the human body loss and the environmental loss to obtain the path total loss of the transmission path; obtaining path total loss data according to the path total loss at each time.

5. The data transmission method for body networking according to claim 1, wherein, In step S2, the process of generating the signal period segmentation function comprises: setting a signal coefficient, and setting the signal coefficient of the high interval to 1 and the signal coefficient of the low interval to 0; establishing a coordinate system with the signal coefficient as the ordinate and the number of time as the abscissa to generate a signal period segmentation function.

6. The data transmission method for body networking according to claim 1, wherein, In step S3, the process of obtaining the period ratio comprises: acquire the period of the motion change curve, denoted as standard motion period; acquire the period of the current motion change curve, denoted as current motion period; the period ratio P=T y ´ / T y , wherein T y represents the standard motion period, T y ´ represents the current motion period.

7. A data transmission system for body networking, characterized by comprising: data acquisition module: setting a monitoring point at the user's limb, acquiring and transmitting limb data through the monitoring point; Obtaining a transmission path, dividing the transmission path, and obtaining path total loss data; generating a motion change curve according to the limb data, and generating a loss change curve according to the path total loss data; A signal strength division module: setting a loss threshold and obtaining a threshold line; obtaining a high interval and a low interval on the loss change curve according to the threshold line; Setting a signal coefficient and generating a signal period segmentation function according to the high interval and the low interval; A transmission rate adjustment module: if the current user starts to move, real-time acquisition of the current limb data; Generating a current motion change curve according to the current limb data; obtaining a period ratio according to the motion change curve and the current motion change curve; scaling the signal period segmentation function according to the period ratio to obtain a current signal period segmentation function, and obtaining a current low interval and a current high interval; Setting a low frequency threshold and a high frequency threshold, and adjusting the transmission rate of the monitoring point according to the current low interval and the current high interval; The process of obtaining the high interval and the low interval includes: Let the loss threshold be denoted as PL t Let the ordinate of the loss change curve be denoted as PL, and a threshold line PL=PL is obtained t On the loss change curve, a curve segment below the threshold line is obtained, denoted as a high signal segment, and a curve segment above the threshold line is obtained, denoted as a low signal segment; an abscissa interval corresponding to the high signal segment is obtained, denoted as a high interval, and an abscissa interval corresponding to the low signal segment is obtained, denoted as a low interval; The process of adjusting the transmission rate of the monitoring point includes: When entering the current low interval, the transmission rate of the monitoring point is adjusted to the low frequency threshold, and when entering the current high interval, the transmission rate of the monitoring point is adjusted to the high frequency threshold.

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