Research On Hallux Valgus Rehabilitation Identification And Orthotic Design Based On Image Feature Capture Technology

Hallux Valgus（HV）is one of the most common clinical deformities of the foot and its causes include genetic and footwear factors.It has been classified as mild,moderate or severe according to the degree of the deformity.Mild hallux valgus are often overlooked and if not treated promptly and effectively,the degree of the deformity will gradually increase over time,thus affecting the health and function of the foot to some extent.Although radiological methods can provide accurate and reliable data,the environmental restrictions and radiation hazards associated with the use of x-ray machines still prevent their widespread use.Hallux valgus orthoses are statistically significant for the correction of HVA,but the orthoses available on the market do not provide a biomechanical correction for the pathophysiology of the hallux valgus and are prone to reverse injury when used inappropriately.Therefore,a timely and effective determination of the indicators of parameters related to hallux valgus deformity is important to prevent and reduce the occurrence of hallux valgus.This study is guided by image feature capturing technology for the rehabilitation recognition algorithm of HVA.The initial algorithm design of the HVA detection rehabilitation recognition system was achieved by extracting the first metatarsal toe ROI of the hallux valgus and calculating the HVA through image enhancement,Gaussian filtering,image binarization,Canny operator,erosion expansion operation and opening and closing operation.Subsequently,20 adult females were recruited to conduct a hallux valgus rehabilitation recognition error compensation experiment,which was divided into two sub-experiments: HVA measurement based on the hallux valgus rehabilitation recognition algorithm and HVA measurement based on 3D CT reconstruction.The aim was to analyse and compare clinical HVA data with algorithmic HVA data,to form and verify algorithmic confidence through error compensation,and to ensure the accuracy,reliability and reasonableness of the measurement results.The results of the experiment showed that: the normality test p=0.078 determined that the HVA difference for this experiment obeyed a normal distribution;the paired samples t-test yielded t=-27.571,p=0.000（p<0.05）,which determined that the two sub-experiments had a high correlation,a high level of significance and that the measured HVA was statistically significant;the linear regression analysis yielded R2=0.957 and For the experimental results,the hallux valgus rehabilitation identification algorithm was improved to maintain the final measurement results to a 95% confidence interval.The image feature recognition detection algorithm was used as a guide for the design of the hallux valgus rehabilitation recognition software system.Based on the target population and requirement analysis,the design framework of the software system was determined.For the rehabilitation recognition function module,the Flask framework was selected to build the software system server side,and the We Chat applet was selected to build the software system client side,which realized the system design and development;for other auxiliary function modules,Adobe XD was selected to complete the preliminary design of the pages.Ten experts were invited to evaluate the design of the hallux valgus rehabilitation identification We Chat applet client based on quantitative testing tasks in five aspects: ease of use,fluency,fault tolerance,aesthetics and professionalism.Using the biomechanical orthopaedic principles of hallux valgus as a guide,a hallux valgus multi-position adjustment orthosis was designed for adult women with mild or no hallux valgus.The preliminary design was developed through an analysis of the functional,stylistic,structural,ergonomic,material and processing elements of the orthosis.The final design of the hallux valgus multi-position adjustment orthosis was determined based on considerations of product structure,man-machine dimensions and material selection.20 adult women with mild hallux valgus were invited to participate in a usability evaluation of the SUS system to verify that the designed hardware product generally met the usability assessment criteria.This study provides a new idea for the design and development of hardware and software products for hallux valgus rehabilitation identification.