Cycling Biomechanics and Its Relationship to Performance

State-of-the-art biomechanical laboratories provide a range of tools that allow precise measurements of kinematic, kinetic, motor and physiologic characteristics. Force sensors, motion capture devices and electromyographic recording measure the forces exerted at the pedal, saddle, and handlebar and the joint torques created by muscle activity. These techniques make it possible to obtain a detailed biomechanical analysis of cycling movements. However, despite the reasonable accuracy of such measures, cycling performance remains difficult to fully explain. There is an increasing demand by professionals and amateurs for various biomechanical assessment services. Most of the difficulties in understanding the link between biomechanics and performance arise because of the constraints imposed by the bicycle, human physiology and musculo-skeletal system. Recent studies have also pointed out the importance of evaluating not only output parameters, such as power output, but also intrinsic factors, such as the cyclist coordination. In this narrative review, we present various techniques allowing the assessment of a cyclist at a biomechanical level, together with elements of interpretation, and we show that it is not easy to determine whether a certain technique is optimal or not.

Action of galvanic current on an experimentally generated muscle lesion: preliminary findings

Background Recently, Abat et al evaluated the effect of the application of galvanic currents on a model of muscle injury in the rat by injection of intramuscular Notexin. In mice, Notexin causes a lesion of the entire muscle when in humans, complete affectation is exceptional. In this study, we evaluated the action of the galvanic current on muscle regeneration in partially lesioned muscles with bupivacaine. Aim To evaluate the action of the galvanic current in an animal model with partial muscle lesion generated with Bupivacaine. Material and Methods The experiments were performed in adult male Swiss mice who were intramuscularly inoculated with Bupivacaine (BPV) in the posterior muscle bundle of the leg. The control subjects were inoculated with physiological saline (PS). The galvanic current protocol used in this study was 1.5mA during 5 seconds and 3 applications (1.5:5:3; Physio Invasiva®, Grupo Prim). The electromyographic recording was performed at 72 hours and at 7 and 10 days, after the first administration (Medelec Synergy Ultrasound machine, concentric recording needle). The number of areas presenting endplate noise were evaluated and the frequency of endplate noise for each of these areas. Results Considering that the fibers which have been lesioned by bupivacaine are electromyographically silent, a registration of endplate noise was related with muscle regeneration. The number of areas with endplate noise considerably increased in the injured limb which received the galvanic current compared to the limb that was only lesioned in the first 72 hours. After this, there was no other modification in the number of areas. The frequency of the endplate noise of each area has been significantly greater in all the periods studied, indicating that galvanic current has facilitated muscle regeneration. It is worth noting that these are preliminary results and other more direct tests are pending. Conclusions The functional findings uncovered in this study, enable us to establish that the application of galvanic currents in an animal model of muscle injury reduce the recovery time of the damaged muscle tissue.

Facial Expression Is Driven by Appraisal and Generates Appraisal Inference

Emotion researchers generally concur that most emotions in humans and animals are elicited by the appraisals of events that are highly relevant for the organism, generating action tendencies that are often accompanied by changes in expression, autonomic physiology, and feeling. Scherer’s component process model of emotion (CPM) postulates that individual appraisal checks drive the dynamics and configuration of the facial expression of emotion and that emotion recognition is based on appraisal inference with consequent emotion attribution. This chapter outlines the model and reviews the accrued empirical evidence that supports these claims, covering studies that experimentally induced specific appraisals or that used induction of emotions with typical appraisal configurations (measuring facial expression via electromyographic recording) or behavioral coding of facial action units. In addition, recent studies analyzing the mechanisms of emotion recognition are shown to support the theoretical assumptions.