Wearables for disabled and extreme sports

Case study: Evaluating deep-water start techniques and training demands in seated slalom waterskiing for an athlete with paraplegia

Purpose

Recreational and competitive slalom waterskiing is increasingly popular among individuals with spinal cord injuries (SCI), particularly for those with paraplegia using sit-skis. A key component of slalom skiing is the deep-water start (DWS), yet little is known about the physiological and physical demands of this activity when the athlete is seated. This study aims to fill this gap by focusing on the training requirements for a seated slalom athlete.

Materials and methods

Focusing on a young male athlete with paraplegia, this case study evaluates the effectiveness and efficiency of traditional (TDWS) and alternative (ADWS) DWS techniques during seated slalom waterskiing sessions. It assesses internal training load (TL) through heart rate (HR) zones and session rating of perceived exertion (sRPE), alongside pre- and post-session handgrip strength measurements to gauge peripheral muscle fatigue.

Results and conclusions

Performing the ADWS, achieving a full success rate, proved more effective but slightly more time-consuming than TDWS, which had limited success. HR during DWS maneuvers ranged from 63.2 to 81.3% of maximal HR, with most sessions occurring below the ventilatory threshold, thus perceived as hard effort. A moderate yet non-significant correlation was found between HR and sRPE-based TL. A significant reduction in handgrip strength post-session underscores the activity's demands. These insights illuminate the technical, physiological, and physical challenges in mastering DWS for seated slalom athletes with SCI, providing valuable guidance for the development of tailored training programs and techniques in this sport.

Determining push-off forces in speed skating imitation drills

Speed skating takes place on ice rinks and is, therefore, dependent on seasonal conditions. To be able to train all year round, training in the summer months, when no ice rinks are available, consists mainly of athletics and endurance training as well as imitation drills. Imitation drills are exercises, e.g. on a slide board, which imitate the actual skating movement. To objectively evaluate the quality of the execution of these exercises, key performance indicators such as push-off forces need to be quantified. The aim of this work was to determine the push-off forces during speed skating imitation drills using pressure insoles in combination with machine-learning methods. A slide board is usually not instrumented. Here, the slide board was equipped with force plates to record the target variables, i.e. the push-off forces. The input variables to determine the push-off forces were recorded using plantar pressure insoles and triaxial accelerometers. Seven participants took part in the study. Two different machine-learning algorithms were compared. A non-linear deep neural network model and a linear multiple variable regression model. The models were trained using the obtained force–time curves. The linear regression model proved sufficient to predict the push-off forces. The relative difference between the measured and modelled maximum push-off force remained below 5%. This approach, based on a mobile and low-cost measurement system, allows a quantitative analysis of the athlete’s technique/performance. Therefore, we expect the instrument to be a helpful tool for the training of speed skaters.