Three-dimensional printing for preoperative rehearsal and intraoperative navigation during laparoscopic rectal cancer surgery with left colic artery preservation

BACKGROUND Prior studies have shown that preserving the left colic artery(LCA)during laparo-scopic radical resection for rectal cancer(RC)can reduce the occurrence of anasto-motic leakage(AL),without compromising oncological outcomes.However,anatomical variations in the branches of the inferior mesenteric artery(IMA)and LCA present significant surgical challenges.In this study,we present our novel three dimensional(3D)printed IMA model designed to facilitate preoperative rehearsal and intraoperative navigation to analyze its impact on surgical safety.AIM To investigate the effect of 3D IMA models on preserving the LCA during RC surgery.METHODS We retrospectively collected clinical dates from patients with RC who underwent laparoscopic radical resection from January 2022 to May 2024 at Fuyang People’s Hospital.Patients were divided into the 3D printing and control groups for sta-tistical analysis of perioperative characteristics.RESULTS The 3D printing observation group comprised of 72 patients,while the control group comprised 68 patients.The operation time(174.5±38.2 minutes vs 198.5±49.6 minutes,P=0.002),intraoperative blood loss(43.9±31.3 mL vs 58.2±30.8 mL,P=0.005),duration of hospitalization(13.1±3.1 days vs 15.9±5.6 days,P<0.001),postoperative recovery time(8.6±2.6 days vs 10.5±4.9 days,P=0.007),and the postoperative complication rate(P<0.05)were all significantly lower in the observation group.CONCLUSION Utilization of a 3D-printed IMA model in laparoscopic radical resection of RC can assist surgeons in understanding the LCA anatomy preoperatively,thereby reducing intraoperative bleeding and shortening operating time,demonstrating better clinical application potential.

Current trends in three-dimensional visualization and real-time navigation as well as robot-assisted technologies in hepatobiliary surgery

With the continuous development of digital medicine,minimally invasive precision and safety have become the primary development trends in hepatobiliary surgery.Due to the specificity and complexity of hepatobiliary surgery,traditional preoperative imaging techniques such as computed tomography and magnetic resonance imaging cannot meet the need for identification of fine anatomical regions.Imaging-based three-dimensional(3D)reconstruction,virtual simulation of surgery and 3D printing optimize the surgical plan through preoperative assessment,improving the controllability and safety of intraoperative operations,and in difficult-to-reach areas of the posterior and superior liver,assistive robots reproduce the surgeon’s natural movements with stable cameras,reducing natural vibrations.Electromagnetic navigation in abdominal surgery solves the problem of conventional surgery still relying on direct visual observation or preoperative image assessment.We summarize and compare these recent trends in digital medical solutions for the future development and refinement of digital medicine in hepatobiliary surgery.

Free-walking:Pedestrian inertial navigation based on dual foot-mounted IMU

The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time performance.However,the intricate and unpredictable pedestrian motion patterns lead the INS localization error to significantly diverge with time.This paper aims to enhance the accuracy of zero-velocity interval(ZVI)detection and reduce the heading and altitude drift of foot-mounted INS via deep learning and equation constraint of dual feet.Aiming at the observational noise problem of low-cost inertial sensors,we utilize a denoising autoencoder to automatically eliminate the inherent noise.Aiming at the problem that inaccurate detection of the ZVI detection results in obvious displacement error,we propose a sample-level ZVI detection algorithm based on the U-Net neural network,which effectively solves the problem of mislabeling caused by sliding windows.Aiming at the problem that Zero-Velocity Update(ZUPT)cannot suppress heading and altitude error,we propose a bipedal INS method based on the equation constraint and ellipsoid constraint,which uses foot-to-foot distance as a new observation to correct heading and altitude error.We conduct extensive and well-designed experiments to evaluate the performance of the proposed method.The experimental results indicate that the position error of our proposed method did not exceed 0.83% of the total traveled distance.

Effect of navigation endoscopy combined with threedimensional printing technology in the treatment of orbital blowout fractures

●AIM:To explore the combined application of surgical navigation nasal endoscopy(NNE)and three-dimensional printing technology(3DPT)for the adjunctive treatment of orbital blowout fractures(OBF).●METHODS:Retrospective analysis was conducted on the data of patients with OBF who underwent surgical treatment at the Affiliated Eye Hospital of Nanchang University between July 2012 and November 2022.The control group consisted of patients who received traditional surgical treatment(n=43),while the new surgical group(n=52)consisted of patients who received NNE with 3DPT.The difference in therapeutic effects between the two groups was evaluated by comparing the duration of the operation,best corrected visual acuity(BCVA),enophthalmos difference,recovery rate of eye movement disorder,recovery rate of diplopia,and incidence of postoperative complications.●RESULTS:The study included 95 cases(95 eyes),with 63 men and 32 women.The patients’age ranged from 5 to 67y(35.21±15.75y).The new surgical group and the control group exhibited no statistically significant differences in the duration of the operation,BCVA and enophthalmos difference.The recovery rates of diplopia in the new surgical group were significantly higher than those in the control group at 1mo[OR=0.03,95%CI(0.01–0.15),P<0.0000]and 3mo[OR=0.11,95%CI(0.03–0.36),P<0.0000]postoperation.Additionally,the recovery rates of eye movement disorders at 1 and 3mo after surgery were OR=0.08,95%CI(0.03–0.24),P<0.0000;and OR=0.01,95%CI(0.00–0.18),P<0.0000.The incidence of postoperative complications was lower in the new surgical group compared to the control group[OR=4.86,95%CI(0.95–24.78),P<0.05].●CONCLUSION:The combination of NNE and 3DPT can shorten the recovery time of diplopia and eye movement disorder in patients with OBF.

Map Aided Pedestrian Dead Reckoning Using Buildings Information for Indoor Navigation Applications

Navigation systems play an important role in many vital disciplines. Determining the location of a user relative to its physical environment is an important part of many indoor-based navigation services such as user navigation, enhanced 911 (E911), law enforcement, location-based and marketing services. Indoor navigation applications require a reliable, trustful and continuous navigation solution that overcomes the challenge of Global Navigation Satellite System (GNSS) signal unavailability. To compensate for this issue, other navigation systems such as Inertial Navigation System (INS) are introduced, however, over time there is a significant amount of drift especially in common with low-cost commercial sensors. In this paper, a map aided navigation solution is developed. This research develops an aiding system that utilizes geospatial data to assist the navigation solution by providing virtual boundaries for the navigation trajectories and limits its possibilities only when it is logical to locate the user on a map. The algorithm develops a Pedestrian Dead Reckoning (PDR) based on smart-phone accelerometer and magnetometer sensors to provide the navigation solution. Geospatial model for two indoor environments with a developed map matching algorithm was used to match and project navigation position estimates on the geospatial map. The developed algorithms were field tested in indoor environments and yielded accurate matching results as well as a significant enhancement to positional accuracy. The achieved results demonstrate that the contribution of the developed map aided system enhances the reliability, usability, and accuracy of navigation trajectories in indoor environments.

Resilient tightly coupled INS/UWB integration method for indoor UAV navigation under challenging scenarios

Based on the high positioning accuracy,low cost and low-power consumption,the ultra-wide-band(UWB)is an ideal solution for indoor unmanned aerial vehicle(UAV)localization and navigation.However,the UWB signals are easy to be blocked or reflected by obstacles such as walls and furniture.A resilient tightly-coupled inertial navigation system(INS)/UWB integration is proposed and implemented for indoor UAV navigation in this paper.A factor graph optimization(FGO)method enhanced by resilient stochastic model is established to cope with the indoor challenging scenarios.To deal with the impact of UWB non-line-of-sight(NLOS)signals and noise uncertainty,the conventional neural net-works(CNNs)are introduced into the stochastic modelling to improve the resilience and reliability of the integration.Based on the status that the UWB features are limited,a‘two-phase'CNNs structure was designed and implemented:one for signal classification and the other one for measurement noise prediction.The proposed resilient FGO method is tested on flighting UAV platform under actual indoor challenging scenario.Compared to classical FGO method,the overall positioning errors can be decreased from about 0.60 m to centimeter-level under signal block and reflection scenarios.The superiority of resilient FGO which effectively verified in constrained environment is pretty important for positioning accuracy and integrity for indoor navigation task.

A Comprehensive UAV Indoor Navigation System Based on Vision Optical Flow and Laser FastSLAM

这份报纸论述为室内的 quadrotor 的全面控制，航行，本地化和印射的答案无人的天线车辆(UAV ) 系统。三个主要传感器在 quadrotor 站台上被使用，也就是，一个惯性的测量单位，一个向下看起来的照相机和扫描激光变化查找者。与这安装， UAV 能要用体力地估计它的自己的速度和位置，当没有碰撞，沿着一个房间的内部墙飞时。在一个以后完成飞行，与收集了数据历史性的 UAV 路径和室内的环境能很好被估计。系统的自治航行部分不要求任何遥远的感觉信息或离线的计算力量，当印射被做时离线。完全的飞行测试被执行了验证忠实和性能航行答案。

Indoor Navigation Network Model Construction Method Based on Building Information Model

In view of the poor information integrity of the 3D model used to make the indoor road network and the lack of versatility of the constructed indoor road network, a method for building an indoor navigation network model that can be seamlessly connected with outdoor paths is proposed in this paper. First, the IFC model is converted to the CityGML model using the BIM model as the indoor data source. Then, using GIS technology and limited Delaunay triangulation refinement algorithm, the necessary elements of indoor navigate on network model such as semantic information, geometric information and topological relationship contained in CityGML model are extracted. Finally, it is visualized and verified based on experimental model data. The results show that the indoor navigation network model constructed based on the CityGML model can accurately perform indoor navigation, make the constructed road network more general, and provide reference and technical support for the integrated construction of indoor and outdoor road network models.

Enhanced Map-Based Indoor Navigation System of a Humanoid Robot Using Ultrasound Measurements

During recent years, walking humanoid robots have gained popularity from wheeled vehicle robots in various assistive roles in human’s environment. Self-localization is a necessary requirement for the humanoid robots used in most of the assistive tasks. This is because the robots have to be able to locate themselves in their environment in order to accomplish their tasks. In addition, autonomous navigation of walking robots to the pre-defined destination is equally important mission, and therefore it is required that the robot knows its initiate location precisely. The indoor navigation is based on the map of the environment used by the robot. Assuming that the walking robot is capable of locating itself based on its initiate location and the distance walked from it, there are still factors that impair the map-based navigation. One of them is the robot’s limited ability to keep its direction when it is walking, which means that the robot is not able to walk directly from one point to another due to a stochastic error in walking direction. In this paper we present an algorithm for straightening the walking path using distance measurements by built-in sonar sensors of a NAO humanoid robot. The proposed algorithm enables the robot to walk directly from one point to another, which enables precise map-based indoor navigation.

Multiconstraint adaptive three-dimensional guidance law using convex optimization

The traditional guidance law only guarantees the accuracy of attacking a target. However, the look angle and acceleration constraints are indispensable in applications. A new adaptive three-dimensional proportional navigation(PN) guidance law is proposed based on convex optimization. Decomposition of the three-dimensional space is carried out to establish threedimensional kinematic engagements. The constraints and the performance index are disposed by using the convex optimization method. PN guidance gains can be obtained by solving the optimization problem. This solution is more rapid and programmatic than the traditional method and provides a foundation for future online guidance methods, which is of great value for engineering applications.

Current and future role of three-dimensional modelling technology in rectal cancer surgery:A systematic review

BACKGROUND Three-dimensional(3D)modelling technology translates the patient-specific anatomical information derived from two-dimensional radiological images into virtual or physical 3D models,which more closely resemble the complex environment encountered during surgery.It has been successfully applied to surgical planning and navigation,as well as surgical training and patient education in several surgical specialties,but its uptake lags behind in colorectal surgery.Rectal cancer surgery poses specific challenges due to the complex anatomy of the pelvis,which is difficult to comprehend and visualise.AIM To review the current and emerging applications of the 3D models,both virtual and physical,in rectal cancer surgery。METHODS Medline/PubMed,Embase and Scopus databases were searched using the keywords“rectal surgery”,“colorectal surgery”,“three-dimensional”,“3D”,“modelling”,“3D printing”,“surgical planning”,“surgical navigation”,“surgical education”,“patient education”to identify the eligible full-text studies published in English between 2001 and 2020.Reference list from each article was manually reviewed to identify additional relevant papers.The conference abstracts,animal and cadaveric studies and studies describing 3D pelvimetry or radiotherapy planning were excluded.Data were extracted from the retrieved manuscripts and summarised in a descriptive way.The manuscript was prepared and revised in accordance with PRISMA 2009 checklist.RESULTS Sixteen studies,including 9 feasibility studies,were included in the systematic review.The studies were classified into four categories:feasibility of the use of 3D modelling technology in rectal cancer surgery,preoperative planning and intraoperative navigation,surgical education and surgical device design.Thirteen studies used virtual models,one 3D printed model and 2 both types of models.The construction of virtual and physical models depicting the normal pelvic anatomy and rectal cancer,was shown to be feasible.Within the clinical context,3D models were used to identify vascular anomalies,for surgical planning and navigation in lateral pelvic wall lymph node dissection and in management of recurrent rectal cancer.Both physical and virtual 3D models were found to be valuable in surgical education,with a preference for 3D printed models.The main limitations of the current technology identified in the studies were related to the restrictions of the segmentation process and the lack of 3D printing materials that could mimic the soft and deformable tissues.CONCLUSION 3D modelling technology has potential to be utilised in multiple aspects of rectal cancer surgery,however,it is still at the experimental stage of application in this setting.

ARCHITECTURE AND ITS IMPLEMENTATION FOR ROBOTS TO NAVIGATE IN UNKNOWN INDOOR ENVIRONMENTS

It is discussed with the design and implementation of an architecture for a mobile robot to navigate in dynamic and anknown indoor environments. The architecture is based on the framework of Open Robot Control Software at KTH （OROCOS@KTH）, which is also discussed and evaluated to navigate indoor efficiently, a new algorithm named door-like-exit detection is proposed which employs 2D feature oft. door and extracts key points of pathway from the raw data of a laser scanner. As a hybrid architecture, it is decomposed into several basic components which can be classified as either deliberative or reactive. Each component can concurrently execute and communicate with another. It is expansible and transferable and its components are reusable.

Local Scenario Perception and Web AR Navigation

This paper proposes a local point cloud map-based Web augmented reality(AR)indoor navigation system solution.By delivering the local point cloud map to the web front end for positioning,the real-time positioning can be implemented only with the help of the computing power of the web front end.In addition,with the characteristics of short time consumption and accurate positioning,an optimization solution to the local point cloud map is proposed,which includes specific measures such as descriptor de-duplicating and outlier removal,thus improving the quality of the point cloud.In this document,interpolation and smoothing effects are introduced for local map positioning,enhancing the anchoring effect and improving the smoothness and appearance of user experience.In small-scale indoor scenarios,the positioning frequency on an iPhone 13 can reach 30 fps,and the positioning precision is within 50 cm.Compared with an existing mainstream visual-based positioning manner for AR navigation,this specification does not rely on any additional sensor or cloud computing device,thereby greatly saving computing resources.It takes a very short time to meet the real-time requirements and provide users with a smooth positioning effect.

Indoor INS/UWB-based Human Localization With Missing Data Utilizing Predictive UFIR Filtering

A combined algorithm for the loosely fused ultra wide band(UWB)and inertial navigation system(INS)-based measurements is designed under the indoor human navigation conditions with missing data.The scheme proposed fuses the INS-and UWB-derived positions via a data fusion filter.Since the UWB signal is prone to drift in indoor environments and its outage highly affects the integrated scheme reliability,we also consider the missing data problem in UWB measurements.To overcome this problem,the loosely-coupled INS/UWB-integrated scheme is augmented with a prediction option based on the predictive unbiased finite impulse response(UFIR)fusion filter.We show experimentally that,the standard UFIR fusion filter has higher robustness than the Kalman filter.It is also shown that the predictive UFIR fusion filter is able to produce an acceptable navigation accuracy under temporary missing UWB-data.

Accuracy and complications of posterior C2 screw fixation using intraoperative three-dimensional fluoroscopy-based navigation

Background The peculiar and highly variable C2 anatomy can make screw fixation more challenging and prone to potential vertebral artery or neurologic injury. Conventional C-arm fluoroscopy has several drawbacks. The aim of this research was to evaluate the accuracy of posterior C2 screw fixation using intraoperative three-dimensional fluoroscopy- based navigation （ITFN） and assess the perioperative complication rate related to screw placement. Methods A retrospective review identified patients who underwent operative management with C2 instruments using ITFN at our hospital between January 2006 and December 2012. Clinical data were obtained from medical records and final screw positions were graded according to a modified classification of Gertzbein and Robbins. Grade A and B screws were considered well positioned. Results The study included 99 patients （53 males and 46 females） who underwent posterior C2 screw fixation using ITFN. The mean Japan Orthopedic Association score improved from （6.7±1.9） points before surgery to （12.5±2.7） points at 6-month follow-up （z= ＋8.628, P 〈0.01）. The mean visual analogue scale improved from （4.1±1.2） points before surgery to （0.7±0.9） points at 6-month follow-up, with an improvement of 83.7% （z= 8.638, P 〈 0.01）. Of the 196 screws analyzed using computed tomography and chart review, 126 transarticular, 64 pedicle, and 6 pars screws were placed with 82.5% （104/126）, 89.1% （57/64）, and 100% （6/6） accuracy （grade A）, respectively; 98.5% （193/196） of screws were grade A or B （grade C, 1.5% （3/196））, and no neurologic injuries occurred. In normal C2 cases, 93 transarticulars and 47 pedicles were placed with high accuracy rates of 90.3% （84/93） and 93.6% （44/47） （grade A）, respectively. However, in cases with C2 deformity, 33 transarticular, 17 pedicle, and 6 pars screws were placed with only 60.6% （20/33）, 76.5% （13/17）, and 100% （6/6） accuracy （grade A）, respectively. Conclusion ITFN is a safe, accurate, and effective tool for posterior C2 fixation. Chin Med J 2014;127 （14）： 2654-2658

Posterior Reduction and Monosegmental Fusion with Intraoperative Three-dimensional Navigation System in the Treatment of High-grade Developmental Spondylolisthesis

Background： The treatment of high-grade developmental spondylolisthesis （HGDS） is still challenging and controversial. In this study, we investigated the efficacy of the posterior reduction and monosegmental fusion assisted by intraoperative three-dimensional （3D） navigation system in managing the HGDS. Methods： Thirteen consecutive HGDS patients were treated with posterior decompression, reduction and monosegmental fusion ofL5/S1, assisted by intraoperative 3D navigation system. The clinical and radiographic outcomes were evaluated, with a minimum follow-up of 2 years. The differences between the pre- and post-operative measures were statistically analyzed using a two-tailed, paired t-test. Results： At most recent follow-up, 12 patients were pain-free. Only l patient had moderate pain, There were no permanent neurological complications or pseudarthrosis. The magnetic resonance imaging showed that there was no obvious disc degeneration in the adjacent segment. All radiographic parameters were improved. Mean slippage improved from 63.2% before surgery to 12.2% after surgery and 11.0% at latest follow-up. Lumbar lordosis changed from preoperative 34.9 ± 13.3° to postoperative 50.4 ±9.9°, and 49.3 ± 7.8° at last follow-up. L5 incidence improved from 71.0 ± 11.3° to 54.0 ± 1 1.9° and did not change significantly at the last follow-up 53.±1 15.4°. While pelvic incidence remained unchanged, sacral slip significantly decreased from preoperative 32.7± 12.5° to postoperative 42.6 ± 9.8°and remained constant to the last follow-up 44.4 ± 6.9°. Pelvic tilt significantly decreased from 38.4±12.5° to 30.9± 8.1° and remained unchanged at the last fbllow-up 28.1± 11.2°. Conclusions： Posterior reduction and monosegmental fusion of L5/S1 assisted by intraoperative 3D navigation are an effective technique for managing high-grade dysplastic spondylolisthesis. A complete reduction of local deformity and excellent correction of overall sagittal balance can be achieved.

Three-dimensional Fluoroscopy-based Navigation for the Pedicle Screw Placement in Patients with Primary Invasive Spinal Tumors

Background：Although pedicle screw placement （PSP） is a well-established technique for spine surgery,the treatment of patients with primary invasive spinal tumor （PIST） has high surgical risks secondary to destroyed pedicles.Intraoperative three-dimensional fluoroscopy-based navigation （ITFN） system permits safe and accurate instrumentation of the spine with the advantage of obtaining intraoperative real-time three-dimensional images and automatic registration.The aim of this study is to evaluate the feasibility and accuracy of PSP using ITFN system for patients afflicted with PIST in the thoracic spine.Methods：Fifty-one patients diagnosed with PISTs were retrospectively analyzed,and 157 pedicles screws were implanted in 23 patients using the free-hand technique （free-hand group） and 197 pedicle screws were implanted in 28 patients using the ITFN system （ITFN group）.Modified classification of Gertzbein and Robbins was used to evaluate the accuracy of PSP,and McCormick classification was applied for assessment of neurological function.Demographic data and factors affecting accuracy of screw insertion were compared using independent t-test while comparison of accuracy of screw insertion between the two groups was analyzed with Chi-square test.Results：Of 51 patients,39 demonstrated improved neurological status and the other 12 patients reported that symptoms remained the same.In the free-hand group,145 screws （92.4%） were Grade Ⅰ,9 screws （5.7%） were Grade Ⅱ,and 3 screws （1.9%） were Grade Ⅲ.In the ITFN group,192 screws （97.4%） were Grade Ⅰ,5 screws （2.6%） were Grade Ⅱ,and no Grade Ⅲ screw was detected.Statistical analysis showed that the accuracies of pedicle screws in the two groups are significantly different （χ^2 =4.981,P =0.026）.Conclusions：The treatments of PISTs include total tumor resection and reconstruction of spine stability.The ITFN system provides a high accuracy of pedicle screw placement.

A Novel Dataset For Intelligent Indoor Object Detection Systems

Indoor Scene understanding and indoor objects detection is a complex high-level task for automated systems applied to natural environments.Indeed,such a task requires huge annotated indoor images to train and test intelligent computer vision applications.One of the challenging questions is to adopt and to enhance technologies to assist indoor navigation for visually impaired people(VIP)and thus improve their daily life quality.This paper presents a new labeled indoor object dataset elaborated with a goal of indoor object detection(useful for indoor localization and navigation tasks).This dataset consists of 8000 indoor images containing 16 different indoor landmark objects and classes.The originality of the annotations comes from two new facts taken into account:(1)the spatial relationships between objects present in the scene and(2)actions possible to apply to those objects(relationships between VIP and an object).This collected dataset presents many specifications and strengths as it presents various data under various lighting conditions and complex image background to ensure more robustness when training and testing objects detectors.The proposed dataset,ready for use,provides 16 vital indoor object classes in order to contribute for indoor assistance navigation for VIP.

Design of Indoor Security Robot based on Robot Operating System

The design and implementation of indoor security robot can well integrate the two fields of indoor navigation and object detection, in order to achieve a more powerful robot system, the development of this project has certain theoretical research significance and practical application value. The project development is completed in ROS (Robot Operating System). The main tools or frameworks used include AMCL (Adaptive Monte Carlo Localization) package, SLAM (Simultaneous Localization and Mapping) algorithm, Darknet deep learning framework, YOLOv3 (You Only Look Once)algorithm, etc. The main development methods include odometer information fusion, coordinate transformation, localization and mapping, path planning, YOLOv3 model training, function package configuration and deployment. Indoor security robot has two main functions: first, it can complete real-time localization, mapping and navigation of indoor environment through sensors such as lidar and camera;Second, object detection is accomplished through USB camera. Through the detailed analysis and research of the functional design of the two modules, the expected function is finally realized, which can meet the daily use needs.

基于多模型融合的室内行人航迹推算建模与性能分析

针对行人航位推算(pedestrian dead reckoning,PDR)室内信号易受到环境和多径效应干扰的问题,提出一种基于多模型融合的室内PDR优化建模方法.给出多模型融合的室内PDR建模方法系统模型,包括步数检测、步长推算、方向推算以及位置推算4个关键阶段.该方法在步数检测阶段融合了峰值检测算法、局部最大值算法以及提前过零检测算法;在步长推算阶段融合Weinberg方法和Kim方法,并利用卡尔曼滤波算法校正步数检测和步长推算的误差.基于不同场景从步数、步长、方向、位置误差方面与传统算法进行比较.结果表明,该组合模型结合了传统步数检测和步长推算算法的特征识别结果,可实现对步数检测、步长推算过程中信号特征的优化处理;在手持场景下,步数检测识别准确,步长推算中值误差在0.060 m以内,方向推算平均绝对误差最小为3.06°,位置推算平均误差为0.2353 m,取得较好的室内步行状态识别与定位性能.