CN-121985292-A - External medical equipment positioning method based on mobile low-power-consumption Bluetooth base station

CN121985292ACN 121985292 ACN121985292 ACN 121985292ACN-121985292-A

Abstract

The invention belongs to the technical field of medical equipment positioning in the range of intelligent medical systems, and provides an external medical equipment positioning method based on a mobile low-power consumption Bluetooth base station, which comprises the steps of screening and marking edge error positioning by acquiring historical positioning data, and judging whether an edge error phenomenon exists or not; when the current device is positioned in real time, judging whether the device is positioned in the edge region or not, distributing base station weights according to the correlation model, calculating the device position by a weighted least square method, solving the problem of low positioning precision of the covered edges of multiple base stations, adapting to the stability and signal relation of different edge regions, improving the positioning precision, reducing the energy consumption and adapting to the positioning requirement of the medical scene on the device.

Inventors

YU HAOJIE
SU JIAN

Assignees

烟台先飞信息技术有限公司

Dates

Publication Date: 20260505
Application Date: 20260313

Claims (10)

1. The external medical equipment positioning method based on the mobile low-power consumption Bluetooth base station is characterized by comprising the following steps: identifying edge error positioning by carrying out edge region feature identification and positioning error analysis on multiple historical positioning, and carrying out statistical analysis on the edge error positioning to judge whether an edge error phenomenon exists; if the edge area corresponding to the edge error positioning is fixed, base station deployment optimization is carried out on the fixed edge area; if not, carrying out association analysis on the signal value positioned by the edge error and the positioning error, constructing an association model of the signal value and the positioning error according to an association analysis result, and determining an edge area judging condition; And judging whether the equipment is positioned in the edge zone or not through the comparison analysis of the signal values of all the base stations received by the equipment in the current positioning and the judgment conditions of the edge zone, if so, distributing weights to all the base stations according to the association model of the signal values and the positioning errors, and calculating the positioning coordinates of the final equipment according to a weighted least square method.
2. The external medical equipment positioning method based on the mobile low-power consumption Bluetooth base station as set forth in claim 1, wherein: The edge error positioning identification mode is as follows: Acquiring multiple historical positioning data from a positioning system, and for any one historical positioning: Calculating the signal value difference of the strongest two signal values received by the equipment, and if the signal value difference meets the approach threshold and the strongest signal value received by the equipment meets the weak signal threshold, conforming to the edge region characteristics; Calculating the distance between the single base station positioning coordinates and the multi-base station fusion positioning coordinates to obtain single base station positioning errors, calculating single base station average errors, and calculating the distance between the multi-base station fusion coordinates and the real coordinates of the equipment to obtain multi-base station fusion errors; and if the single-station average error and the multi-base station fusion error meet the error judgment conditions and meet the edge region characteristics, marking the historical positioning as edge error positioning.
3. The external medical equipment positioning method based on the mobile low-power consumption Bluetooth base station as set forth in claim 1, wherein: The judging mode of whether the edge error phenomenon exists is as follows: And counting the proportion of the edge error positioning in the history positioning, and if the proportion meets the requirement, carrying out external medical equipment positioning based on the mobile low-energy Bluetooth base station, wherein the edge error phenomenon exists.
4. The external medical equipment positioning method based on the mobile low-power consumption Bluetooth base station as set forth in claim 1, wherein: the judging mode of whether the edge area corresponding to the edge error positioning is fixed is as follows: dividing a hospital positioning area into space units, counting the times of marking the space units as edge areas, and performing proportion calculation with the total times of edge error positioning to obtain the occurrence ratio of the edge areas; screening out space units with the edge area occurrence ratio larger than or equal to a preset ratio from all the space units, and marking the space units as a high-duty ratio unit set; Through carrying out statistical analysis on adjacent space units in the high-duty ratio unit set, judging whether the space distribution of the high-duty ratio space units is space concentrated or not; if one or more high-duty space units exist in the Gao Zhanbi unit set and the spatial distribution of the high-duty space units is concentrated, the edge region corresponding to the edge error positioning is fixed.
5. The external medical equipment positioning method based on the mobile low-power consumption Bluetooth base station as set forth in claim 4, wherein: The judgment mode of whether the spatial distribution of the high-duty space unit is space concentrated is as follows If the transverse coordinate difference and the longitudinal coordinate difference of the two space units are smaller than or equal to 1, judging that the space units are adjacent units; counting the number of adjacent units of Gao Zhanbi units in the high-duty-ratio unit set for each high-duty-ratio unit in the high-duty-ratio unit set; Adding the adjacent unit numbers of all the high-duty ratio units, dividing the added adjacent unit numbers by 2 to obtain total adjacent unit logarithms, and calculating the proportion of the total adjacent unit logarithms to the theoretical maximum adjacent unit logarithms to obtain adjacent unit duty ratios; If the adjacent unit duty ratio is larger than or equal to the concentration threshold, the spatial distribution is concentrated, otherwise, the spatial distribution is dispersed.
6. The external medical equipment positioning method based on the mobile low-power consumption Bluetooth base station as set forth in claim 5, wherein: the process for base station deployment optimization of the fixed edge area comprises the following steps: Marking a space range formed by the high-duty space units as a fixed edge area; Counting the equipment occurrence frequency of each space in the fixed edge area, and marking the space units with the equipment occurrence frequency meeting the requirement as an equipment core active area, otherwise, as a non-equipment core active area; If the distance between the fixed edge area and the nearest base station meets the requirement and no other base station exists in the middle, the defect type is that the density of the base station is insufficient, and edge micro base stations are complementarily deployed between the fixed edge area and the nearest base station; If the base station is fixed in the non-equipment core active area for a long time, the defect type is that the position of the base station deviates from the core area, and the existing mobile base station is adjusted to be near the geometric center of the equipment core active area.
7. The external medical equipment positioning method based on the mobile low-power consumption Bluetooth base station as set forth in claim 1, wherein: The construction process of the correlation model of the signal value and the positioning error comprises the following steps: Screening the strongest signal value received by the equipment in each edge error positioning and fusing positioning errors by a plurality of base stations, and performing standardization to obtain a signal value and a positioning error; Taking the signal value as an independent variable, taking the multi-base station fusion positioning error as a dependent variable, performing linear fitting on the signal value and the positioning error, and solving a fitting equation according to a least square method; Calculating a fitting goodness, wherein if the fitting goodness meets a linear condition, the signal value and the positioning error are in a linear relation, otherwise, the signal value and the positioning error are in a nonlinear relation; if the signal value and the positioning error are in a linear relation, the fitting equation is a correlation model of the signal value and the positioning error; And if the signal value and the positioning error are in a nonlinear relation, clustering according to the positioning error positioned by the edge error and the signal value to obtain a plurality of clustering groups.
8. The external medical equipment positioning method based on the mobile low-power consumption Bluetooth base station as set forth in claim 7, wherein: The edge area judging conditions are determined in the following manner: if the positioning error and the signal value are in a linear relation, substituting an error acceptable threshold into an edge region threshold obtained by a fitting equation, and obtaining an edge region judgment condition; if the positioning error and the signal value are in a nonlinear relation, counting the signal value range and the positioning error range of each cluster group; And taking the total range of the signal values of each cluster group as an edge region threshold interval, namely an edge region judgment condition.
9. The external medical equipment positioning method based on the mobile low-power consumption Bluetooth base station as set forth in claim 1, wherein: The calculation process of the final equipment positioning coordinates comprises the following steps: acquiring signal values of all base stations received by equipment in real time when the equipment is positioned currently; If the positioning error and the signal value are in a linear relation, if the maximum signal value received by the equipment is smaller than or equal to the threshold value of the edge area, the equipment is positioned in the edge area, and the signal value of each base station received by the equipment is substituted into a fitting equation to obtain the expected error of each participating positioning base station; For any one of the participating positioning base stations, calculating the proportion of the expected error reciprocal in the sum of the expected error reciprocal of all the participating positioning base stations to obtain the weight of each participating positioning base station; substituting the real-time coordinates, signal values and weights of the participating positioning base stations into a weighted least square formula to obtain final equipment positioning coordinates.
10. The external medical equipment positioning method based on the mobile low-power consumption Bluetooth base station as set forth in claim 9, wherein: the calculation process of the final equipment positioning coordinates further comprises the following steps: If the positioning error and the signal value are in a nonlinear relation, if the maximum signal value received by the current equipment is not in the threshold value interval of the edge area, the equipment is positioned in the edge area; matching each base station signal value received by the current equipment with the signal value range of each cluster group respectively to determine the cluster group to which each base station signal value belongs; Calculating the average positioning error of each cluster group, wherein the weight of each base station is the reciprocal ratio of the average positioning error of each cluster group; substituting the coordinates and weights of the base stations into a weighted least square formula to obtain final equipment positioning coordinates.

Description

External medical equipment positioning method based on mobile low-power-consumption Bluetooth base station Technical Field The invention belongs to the technical field of medical equipment positioning in the range of intelligent medical systems, and particularly relates to an external medical equipment positioning method based on a mobile low-power-consumption Bluetooth base station. Background In the intelligent medical field, the real-time positioning of external medical equipment mobile intelligent terminal is crucial to diagnosis and treatment efficiency improvement, asset turnover management and emergency response speed. The mobile low-energy Bluetooth (BLE) base station is a mainstream technical scheme for positioning external equipment in the current hospital due to the advantages of flexible deployment, low power consumption, controllable cost and the like, and the equipment coordinates are calculated by combining the Bluetooth signals broadcasted by the beacons of the equipment through the cooperation of multiple base stations and the RSSI (received signal value indication) or TOF (time of flight) ranging technology, so that the positioning accuracy of 1-1.5 meters in a daily scene is realized, and the medical basic requirement is basically met. However, in the case of covering edge areas (such as signal transition zones of two ends of a corridor, ward corners, operating room gates and the like) by multiple base stations, the conventional positioning technology faces remarkable precision bottlenecks, and the specific problems are concentrated in two aspects, namely, firstly, the single base station positioning error is rapidly enlarged, the signal attenuation of the edge areas is severe, the single base station RSSI value received by equipment is generally low, the distance conversion error based on RSSI is rapidly increased, the coordinate drift of the base stations is overlapped, the final single base station positioning error is enlarged to 3-5 meters, the precision requirements of medical scenes on equipment positioning can not be met completely, secondly, the multi-base station combined positioning is difficult to break through the signal reliability bottlenecks, the edge area signal is influenced by multipath interference and electromagnetic interference, the RSSI fluctuation variance is often more than 5dBm2, the direct signal ratio is low, the signal reliability is remarkably reduced, even if a multi-base station fusion algorithm is adopted, the conventional fusion strategy is not optimized aiming at the signal characteristics of the edge areas, the low-reliability data can not be filtered effectively, and finally, the combined positioning precision of the multiple base stations is insufficient for 2 meters, and the emergency equipment is difficult to support the high-precision requirements of fast searching, real-time tracking of TOF instruments and the like. Therefore, the invention provides an external medical equipment positioning method based on the mobile low-power consumption Bluetooth base station. Disclosure of Invention In order to overcome the deficiencies of the prior art, at least one technical problem presented in the background art is solved. The invention solves the technical problems by adopting the technical scheme that the external medical equipment positioning method based on the mobile low-power consumption Bluetooth base station is characterized by comprising the following steps: identifying edge error positioning by carrying out edge region feature identification and positioning error analysis on multiple historical positioning, and carrying out statistical analysis on the edge error positioning to judge whether an edge error phenomenon exists; if the edge area corresponding to the edge error positioning is fixed, base station deployment optimization is carried out on the fixed edge area; if not, carrying out association analysis on the signal value positioned by the edge error and the positioning error, constructing an association model of the signal value and the positioning error according to an association analysis result, and determining an edge area judging condition; And judging whether the equipment is positioned in the edge zone or not through the comparison analysis of the signal values of all the base stations received by the equipment in the current positioning and the judgment conditions of the edge zone, if so, distributing weights to all the base stations according to the association model of the signal values and the positioning errors, and calculating the positioning coordinates of the final equipment according to a weighted least square method. Further, the edge error positioning identification method is as follows: Acquiring multiple historical positioning data from a positioning system, and for any one historical positioning: calculating the signal value difference of the signal value rank 2 before the signal value ranks, and if the signal value di