Impact of Combined CST, BFR, and Tai Chi on Muscle Physiology and Functional Characteristics Among Adults With LBP

Background: Low back pain (LBP) is highly prevalent globally, affecting people of all ages(Wu et al., 2020). In China, LBP is a leading cause of disease burden(Wu et al., 2019). Exercise therapy such as core stability training(CST), Tai Chi(TC) and education are commonly recommended treatments, but research on optimal protocols has been limited. Blood flow restriction(BFR) is beneficial for inducing muscle hypertrophy and promoting muscle strength (Hughes et al., 2019). Combined approaches using multiple modalities may provide added benefits but are understudied. Research objectives: 1. To determine the effects of combined CST, BFR and Tai Chi on muscle physiology (muscle activation, muscle fatigue, back extensor strength, and transverses abdominus control) among working adults with LBP. 2. To determine the effects of combined CST+ BFR+Tai Chi on functional performance (gait speed, balance, proprioception, and postural sway) among working adults with LBP. 3. To determine the effects of combined CST+BFR+Tai Chi on pain intensity among working adults with LBP. 4. To determine the effects of combined CST+BFR+Tai Chi on fear among working adults with LBP. Location of research: Qianxinan Wutong Orthopedic Hospital, Guizhou Province, China Instrumentations: 1. Demographic Data 2. Surface Electromyography (S-EMG) 3. Pressure Biofeedback Unit (PBU) 4. Back Extensor Strength Test (BEST) 5. Joint Repositioning Error(JRE) 6. APECS app 7. Y-Balance Test(YBT) 8.10-Meter Walk Test(10MWT) 9.Visual Analogue Scale (VAS) 10.Chinese version of the Fear-Avoidance Beliefs Questionnaire(FABQ-CHI) Interventions: Group A: CST+BFR+Tai Chi+Education; Group B: CST+BFR+Education; Group C: Tai Chi +BFR+Education; Group D: CST+Education. Sample size: Considering 30% drop out. 52 participants. 13 participants in each group Statistical analysis: Data were processed using SPSS version 25.0 and Microsoft Excel 2010 software. 1. Demographic data = descriptive analytics. 2. All objectives = repeated measure ANCOVA (within-between interactions) for all variables. 3. The significant level is P \< 0.05.