Search Results (5)

Previous studies examining the flexion–relaxation phenomenon (FRP) in back muscles through trunk forward flexion tests have yielded inconsistent findings, primarily due to variations in leg posture control. This study aimed to explore the influence of leg posture control and individual flexibility on FRP in back and low limb muscles. Thirty-two male participants, evenly distributed into high- and low-flexibility groups, were recruited. Activities of the erector spinae, biceps femoris, and gastrocnemius muscles, alongside the lumbosacral angle (LSA), were recorded as participants executed trunk flexion from 0° to 90° in 15° increments, enabling an analysis of FRP and its correlation with the investigated variables. The findings highlighted significant effects of all examined factors on the measured responses. At a trunk flexion angle of 60°, the influence of leg posture and flexibility on erector spinae activities was particularly pronounced. Participants with limited flexibility exhibited the most prominent FRP under constrained leg posture, while those with greater flexibility and unconstrained leg posture displayed the least FRP, indicated by their relatively larger LSAs. Under constrained leg posture conditions, participants experienced an approximate 1/3 to 1/2 increase in gastrocnemius activity throughout trunk flexion from 30° to 90°, while biceps femoris activity remained relatively constant. Using an inappropriate leg posture during back muscle FRP assessments can overestimate FRP. These findings offer guidance for designing future FRP research protocols. Full article

The myoelectric activity of the back muscles can be studied to evaluate the flexion-relaxation phenomenon and find differences between electromyography patterns on different subjects. In this paper, we propose an algorithm able to provide a myoelectric silence evaluation based on the data acquired from a wireless body sensor network consisting of surface electromyography sensors in association with a wearable inertial measurement unit. From the study group was chosen a gold standard subject, a healthy control with the best regular patterns, as a reference to find a first validity range. Through the subsequent iterations, the range was modified to include the other healthy subjects who showed muscle relaxation according to the previous ranges. Through this likelihood analysis, we want to compare patterns on different channels, identified by the electromyography root mean squared values, to study and find with iterations a validity range for the myoelectric activity silence identification and classification. The proposed algorithm was tested by processing the data collected in an acquisition campaign conducted to evaluate the flexion-relaxation phenomenon on the back muscles of subjects with and without lower back pain. The results show that the submitted method is significant for the clinical assessment of electromyography activity patterns to evaluate which are the subjects that have patterns near or far from the gold standard. This analysis is useful both for prevention and for assessing the progress of subjects with low back pain undergoing physiotherapy. Full article

This study quantified the neck posture and fatigue using the flexion relaxation phenomenon (FRP) and craniovertebral angle (CVA); further, it compared the difference between the level of fatigue and neck posture induced by two types of monitors (regular fixed monitor and moving monitor). Twenty-three male participants were classified into two groups—the low-flexion relaxation ratio (FRR) group and the normal-FRR group, depending on the FRR value. All participants performed a document task for 50 min using both types of monitors. It was found that the FRR values significantly decreased after the documentation task. The CVA analysis showed that the moving monitor’s frequency of forward head posture (FHP) was lower than that for the fixed monitor. Overall, the moving monitor worked better than the fixed monitor; this can be interpreted as proof that such monitors can reduce neck fatigue. Full article

Numerous studies have been conducted on lower back injury caused by deeper stooped posture, which is associated with the back muscle flexion–relaxation phenomenon (FRP). Individual flexibility also affects FRP; individuals with high flexibility have the benefit of delayed FRP occurrence. This study attempted to determine the most efficient measurement of flexibility for evaluating the occurrence and degree of FRP when participants flexed their trunk forward. We recruited 40 male university students who were grouped on the basis of three flexibility measurements (toe-touch test, TTT; sit-and-reach test, SRT; modified Schober’s test, MST) into three levels (high, middle and low). Muscle activation (thoracic and lumbar erector spinae, TES and LES, respectively; hamstring, HMS) and lumbosacral angle (LSA) were recorded when the trunk flexed forward from 0° (upright) to 15°, 30°, 45°, 60°, 75° and 90°. The results indicated that trunk angle had a significant effect on three muscle activation levels and LSA. The effects of muscles and LSA varied depending on flexibility measurement. TTT significantly discriminated LES electromyography findings between high and low flexibility groups, whereas MST and SRT distinguished between high and non-high flexibility groups. The TTT values positively correlated with the time of LES FRP occurrence, showing that the higher the TTT, the slower the occurrence of FRP. This is beneficial in delaying or avoiding excessive loading on the passive tissue of the lumbar spine when performing a deeper trunk flexion. Full article

An accurate clinical assessment of the flexion-relaxation phenomenon on back muscles requires objective tools for the analysis of surface electromyography signals correlated with the real movement performed by the subject during the flexion-relaxation test. This paper deepens the evaluation of the flexion-relaxation phenomenon using a wireless body sensor network consisting of sEMG sensors in association with a wearable device that integrates accelerometer, gyroscope, and magnetometer. The raw data collected from the sensors during the flexion relaxation test are processed by an algorithm able to identify the phases of which the test is composed, provide an evaluation of the myoelectric activity and automatically detect the phenomenon presence/absence. The developed algorithm was used to process the data collected in an acquisition campaign conducted to evaluate the flexion-relaxation phenomenon on back muscles of subjects with and without Low Back Pain. The results have shown that the proposed method is significant for myoelectric silence detection and for clinical assessment of electromyography activity patterns. Full article