The Study Of The Evaluation Method Of Dysfunction In Individuals With Low Back Pain Based On Inertial Sensors

In the diagnosis and monitoring and plan formulation of rehabilitation progress of low back pain,it plays an important role to the evaluation of dysfunction in patients with low back pain.The diagnosis of low back pain used in existing clinical studies is imaging methods: X-ray,CT,and MRI.The imaging method has the following shortcomings: it has a certain degree of radiation,and it is not suitable for long-term and repeatedly use in the evaluation of rehabilitation process of low back pain;it is not easy to query dyskinesia,while the common spinal injury and pain are often manifested in the spine movement abnormalities.To solve this problem,this paper presents a method of non-invasive and real-time dynamic monitoring-method based on inertial sensor.The reseach,the evaluation of dysfunction in individuals with low back pain based on inertial sensors,has not yet been studied in the country.It is only used for reseach on hemiplegic patients and Parkinson’s disease patients;However,it has long been used to measure motion parameters of low back pain in foreign countries.Only in those studies,those parameters,such as range of motion(ROM),acceleration,angular velocity,are analysed by single and scattered.Aiming at this problem,this paper designs a systematic three-level multi-parameter evaluation system based on the inertial sensor.In order to realize the reseach of the three-level multi-parameter evaluation system of the dysfunction of patients with low back pain based on inertial sensor,the main work of this paper includes:(1)On the basis of the study of spine sport biomechanics and inertial sensor in patients with low back pain,the evaluation experiment are designed to research.This paper select the appropriate placement of inertial sensors.In this basis,Two inertial sensor data were collected from the spinal nodes of the upper trunk of healthy people and patients with low back pain,to analysing and processing.(2)The data analysis and processing module is designed in the paper.In which includes five modules: data preprocessing,multi-sensor data fusion,adaptive peak detection,data feature extraction and parameter evaluation.Outliers elimination of adaptive median filtering and data filtering are utilized to realize data preprocessing;After data pretreatment,quaternion update algorithm is used to fuse two inertial sensor data;The characteristic values of the fused data are detected by adaptive peak detection module;The data feature extraction is carried on in three aspects: the time domain,frequency domain and heuristic;After the feature extraction,evaluation analysis of the data parameters is applied in three levels of characteristic parameters,clinical scales and performance index.(3)Three-level multi-parameter evaluation system,which based on characteristic parameters,based on clinical scale,and based on performance index of low back pain dysfunction,was proposed in the paper.Statistical analysis of the three-level multi-parameter evaluation system is added in the study.The assessment system can diagnose and screen out healthy people and patients with low back pain in different illness degrees to calculate the difference and accuracy.Experiments show that the evaluation system has a high reliability and validity.It can assist doctors to early diagnose the disease of low back pain,and provide to the evaluation of real-time monitoring in rehabilitation process of low back pain.