Measurement of three-dimensional hand kinematics during swimming with a motion capture system: a feasibility study

Development of a Methodology for Low-Cost 3D Underwater Motion Capture: Application to the Biomechanics of Horse Swimming

Hydrotherapy has been utilized in horse rehabilitation programs for over four decades. However, a comprehensive description of the swimming cycle of horses is still lacking. One of the challenges in studying this motion is 3D underwater motion capture, which holds potential not only for understanding equine locomotion but also for enhancing human swimming performance. In this study, a marker-based system that combines underwater cameras and markers drawn on horses is developed. This system enables the reconstruction of the 3D motion of the front and hind limbs of six horses throughout an entire swimming cycle, with a total of twelve recordings. The procedures for pre- and post-processing the videos are described in detail, along with an assessment of the estimated error. This study estimates the reconstruction error on a checkerboard and computes an estimated error of less than 10 mm for segments of tens of centimeters and less than 1 degree for angles of tens of degrees. This study computes the 3D joint angles of the front limbs (shoulder, elbow, carpus, and front fetlock) and hind limbs (hip, stifle, tarsus, and hind fetlock) during a complete swimming cycle for the six horses. The ranges of motion observed are as follows: shoulder: 17 ± 3°; elbow: 76 ± 11°; carpus: 99 ± 10°; front fetlock: 68 ± 12°; hip: 39 ± 3°; stifle: 68 ± 7°; tarsus: 99 ± 6°; hind fetlock: 94 ± 8°. By comparing the joint angles during a swimming cycle to those observed during classical gaits, this study reveals a greater range of motion (ROM) for most joints during swimming, except for the front and hind fetlocks. This larger ROM is usually achieved through a larger maximal flexion angle (smaller minimal angle of the joints). Finally, the versatility of the system allows us to imagine applications outside the scope of horses, including other large animals and even humans.

Motion Capture Technologies for Ergonomics: A Systematic Literature Review

Muscular skeletal disorder is a difficult challenge faced by the working population. Motion capture (MoCap) is used for recording the movement of people for clinical, ergonomic and rehabilitation solutions. However, knowledge barriers about these MoCap systems have made them difficult to use for many people. Despite this, no state-of-the-art literature review on MoCap systems for human clinical, rehabilitation and ergonomic analysis has been conducted. A medical diagnosis using AI applies machine learning algorithms and motion capture technologies to analyze patient data, enhancing diagnostic accuracy, enabling early disease detection and facilitating personalized treatment plans. It revolutionizes healthcare by harnessing the power of data-driven insights for improved patient outcomes and efficient clinical decision-making. The current review aimed to investigate: (i) the most used MoCap systems for clinical use, ergonomics and rehabilitation, (ii) their application and (iii) the target population. We used preferred reporting items for systematic reviews and meta-analysis guidelines for the review. Google Scholar, PubMed, Scopus and Web of Science were used to search for relevant published articles. The articles obtained were scrutinized by reading the abstracts and titles to determine their inclusion eligibility. Accordingly, articles with insufficient or irrelevant information were excluded from the screening. The search included studies published between 2013 and 2023 (including additional criteria). A total of 40 articles were eligible for review. The selected articles were further categorized in terms of the types of MoCap used, their application and the domain of the experiments. This review will serve as a guide for researchers and organizational management.

Non-human primate models and systems for gait and neurophysiological analysis

Brain-computer interfaces (BCIs) have garnered extensive interest and become a groundbreaking technology to restore movement, tactile sense, and communication in patients. Prior to their use in human subjects, clinical BCIs require rigorous validation and verification (V&V). Non-human primates (NHPs) are often considered the ultimate and widely used animal model for neuroscience studies, including BCIs V&V, due to their proximity to humans. This literature review summarizes 94 NHP gait analysis studies until 1 June, 2022, including seven BCI-oriented studies. Due to technological limitations, most of these studies used wired neural recordings to access electrophysiological data. However, wireless neural recording systems for NHPs enabled neuroscience research in humans, and many on NHP locomotion, while posing numerous technical challenges, such as signal quality, data throughout, working distance, size, and power constraint, that have yet to be overcome. Besides neurological data, motion capture (MoCap) systems are usually required in BCI and gait studies to capture locomotion kinematics. However, current studies have exclusively relied on image processing-based MoCap systems, which have insufficient accuracy (error: ≥4° and 9 mm). While the role of the motor cortex during locomotion is still unclear and worth further exploration, future BCI and gait studies require simultaneous, high-speed, accurate neurophysiological, and movement measures. Therefore, the infrared MoCap system which has high accuracy and speed, together with a high spatiotemporal resolution neural recording system, may expand the scope and improve the quality of the motor and neurophysiological analysis in NHPs.

Stroke Kinematics, Temporal Patterns, Neuromuscular Activity, Pacing and Kinetics in Elite Breaststroke Swimming: A Systematic Review

Background

Breaststroke is a technically complex stroke characterised by discontinuous propulsive phases, large intracyclic velocity variation and low mean velocity. The performance of this stroke at an elite level is influenced by a number of biomechanical, physiological and psychological factors. The present systematic review aimed to synthesise the biomechanical factors influencing elite breaststroke swimming performance. This review aims to provide elite coaches and performance scientists with a breadth of knowledge from which training and racing interventions can be developed.

Methods

Electronic searches of Medline, Scopus and SPORTDiscus databases were conducted in May 2020 and March 2022. Search results that were peer-reviewed, published in English and published during or after the year 2000 were considered for review. The methodological rigour of studies was assessed using a risk of bias scale previously used for the evaluation of sports science research.

Results

Thirty-eight articles were included in the present review. Articles investigated elite breaststroke performance in relation to one of the following areas: stroke kinematics, temporal patterns, neuromuscular activity, pacing and kinetics.

Discussion

Kinematic, temporal and neuromuscular activity comparisons between groups of various race distance, performance or experience level, and athlete sex were common in the literature. These analyses demonstrated differences in stroke rate, stroke length, propulsive time, recovery time, glide time, sum of total integrated EMG and triceps brachii activation patterns between groups. The evaluation of various pacing strategies, and the relationship between kinetics and breaststroke performance was comparatively rare within the literature. Further research into the relationship between kinetics and breaststroke performance, and the manipulation of pacing strategy would increase the breadth of knowledge from which coaches and performance scientists can develop evidence-based training and racing interventions.

Novel Method for Estimating Propulsive Force Generated by Swimmers' Hands Using Inertial Measurement Units and Pressure Sensors

Propulsive force is a determinant of swimming performance. Several methods have been proposed to estimate the propulsive force in human swimming; however, their practical use in coaching is limited. Herein, we propose a novel method for estimating the propulsive force generated by swimmers' hands using an inertial measurement unit (IMU) and pressure sensors. In Experiment 1, we use a hand model to examine the effect of a hand-mounted IMU on pressure around the hand model at several flow velocities and water flow directions. In Experiment 2, we compare the propulsive force estimated using the IMU and pressure sensors (FIMU) via an underwater motion-capture system and pressure sensors (FMocap). Five swimmers had markers, pressure sensors, and IMUs attached to their hands and performed front crawl swimming for 25 m twice at each of nine different swimming speeds. The results show that the hand-mounted IMU affects the resultant force; however, the effect of the hand-mounted IMU varies with the flow direction. The mean values of FMocap and FIMU are similar (19.59 ± 7.66 N and 19.36 ± 7.86 N, respectively; intraclass correlation coefficient_(2,1) = 0.966), and their waveforms are similar (coefficient of multiple correlation = 0.99). These results indicate that the IMU can estimate the same level of propulsive force as an underwater motion-capture system.

Validation of a Sensor-Based Dynamic Ski Deflection Measurement in the Lab and Proof-of-Concept Field Investigation

Introduction: Ski deflection is a performance-relevant factor in alpine skiing and the segmental and temporal curvature characteristics (m−1) along the ski have lately received particular attention. Recently, we introduced a PyzoFlex® ski deflection measurement prototype that demonstrated high reliability and validity in a quasi-static setting. The aim of the present work is to test the performance of an enhanced version of the prototype in a dynamic setting both in a skiing-like bending simulation as well as in a field proof-of-concept measurement. Material and methods: A total of twelve sensor foils were implemented on the upper surface of the ski. The ski sensors were calibrated with an empirical curvature model and then deformed on a programmable bending robot with the following program: 20 times at three different deformation velocities (vslow, vmedium, vfast) with (1) central bending, (2) front bending, (3) back bending, (4) edging left, and (5) edging right. For reliability assessment, pairs of bending cycles (cycle 1 vs. cycle 10 and cycle 10 vs. cycle 20) at vslow, vmedium, and vfast and between pairs of velocity (vslow vs. vmedium and vslow vs. vfast) were evaluated by calculating the change in the mean (CIM), coefficient of variation (CV) and intraclass correlation coefficient (ICC 3.1) with a 95% confidence interval. For validity assessment, the calculated segment-wise mean signals were compared with the values that were determined by 36 infrared markers that were attached to the ski using an optoelectrical measuring system (Qualisys). Results: High reliability was found for pairs of bending cycles (CIM −0.69−0.24%, max CV 0.28%, ICC 3.1 > 0.999) and pairs of velocities (max CIM = 3.03%, max CV = 3.05%, ICC 3.1 = 0.997). The criterion validity based on the Pearson correlation coefficient was r = 0.98. The accuracy (systematic bias) and precision (standard deviation), were −0.003 m−1 and 0.047 m−1, respectively. Conclusions: The proof-of-concept field measurement has shown that the prototype is stable, robust, and waterproof and provides characteristic curvature progressions with plausible values. Combined with the high laboratory-based reliability and validity of the PyzoFlex® prototype, this is a potential candidate for smart ski equipment.

An Adaptive Integral Terminal Sliding Mode Controller to Track the Human Upper Limb during Front Crawl Swimming

AbstractInjuries are inevitable during swimming. The main goal for athletes especially competitive ones and coaches is to do the most mechanically effective motion patterns. In this case, biomechanical assessments could be beneficial in the management and prevention of injuries and pain in swimmers' vulnerable joints. As upper limb in swimming causes the highest propulsive force, the arm is exposed to more injuries. A skeletal model with 5 degrees of freedom is developed to simulate the swimmer's arm during front crawl swimming. This model includes shoulder and elbow joints with all of their degrees of freedom. An adaptive integral sliding mode (AITSM) controller is employed to track the desired joint trajectories during swimming. This controller can converge the tracking errors to zero in finite time. For tuning the controller gains regardless of the upper bounds of the system uncertainties, an adaptive controller is applied. Results demonstrate the performance of the AITSM strategy in tracking the desired trajectory of an underwater arm model during swimming. During the down sweep to catch phase, arm movements cause more stress in the shoulder than elbow. The applied moment at the shoulder is almost triple of elbow's moment. Therefore, the most vulnerable joint is the shoulder. By considering shoulder strength, the injury risk is predicted about 10% for the considered swimmer.

Curvature Detection with an Optoelectronic Measurement System Using a Self-Made Calibration Profile

So far, no studies of material deformations (e.g., bending of sports equipment) have been performed to measure the curvature (w″) using an optoelectronic measurement system OMS. To test the accuracy of the w″ measurement with an OMS (Qualisys), a calibration profile which allowed to: (i) differentiates between three w″ (0.13˙ m^-1, 0.2 m^-1, and 0.4 m^-1) and (ii) to explore the influence of the chosen infrared marker distances (50 mm, 110 mm, and 170 mm) was used. The profile was moved three-dimensional at three different mean velocities (vzero = 0 ms^-1, vslow = 0.2 ms^-1, vfast  = 0.4 ms^-1) by an industrial robot. For the accuracy assessment, the average difference between the known w″ of the calibration profile and the detected w″ from the OMS system, the associated standard deviation (SD) and the measuring point with the largest difference compared to the defined w″ (=maximum error) were calculated. It was demonstrated that no valid w″ can be measured at marker distances of 50 mm and only to a limited extent at 110 mm. For the 170 mm marker distance, the average difference (±SD) between defined and detected w″ was less than 1.1 ± 0.1 mm^-1 in the static and not greater than -3.8 ± 13.1 mm^-1 in the dynamic situations. The maximum error in the static situation was small (4.0 mm^-1), while in the dynamic situations there were single interfering peaks causing the maximum error to be larger (-30.2 mm^-1 at a known w″ of 0.4 m^-1). However, the Qualisys system measures sufficiently accurately to detect curvatures up to 0.13˙ m^-1 at a marker distance of 170 mm, but signal fluctuations due to marker overlapping can occur depending on the direction of movement of the robot arm, which have to be taken into account.

Framework for Intelligent Swimming Analytics with Wearable Sensors for Stroke Classification

Intelligent approaches in sports using IoT devices to gather data, attempting to optimize athlete’s training and performance, are cutting edge research. Synergies between recent wearable hardware and wireless communication strategies, together with the advances in intelligent algorithms, which are able to perform online pattern recognition and classification with seamless results, are at the front line of high-performance sports coaching. In this work, an intelligent data analytics system for swimmer performance is proposed. The system includes (i) pre-processing of raw signals; (ii) feature representation of wearable sensors and biosensors; (iii) online recognition of the swimming style and turns; and (iv) post-analysis of the performance for coaching decision support, including stroke counting and average speed. The system is supported by wearable inertial (AHRS) and biosensors (heart rate and pulse oximetry) placed on a swimmer’s body. Radio-frequency links are employed to communicate with the heart rate sensor and the station in the vicinity of the swimming pool, where analytics is carried out. Experiments were carried out in a real training setup, including 10 athletes aged 15 to 17 years. This scenario resulted in a set of circa 8000 samples. The experimental results show that the proposed system for intelligent swimming analytics with wearable sensors effectively yields immediate feedback to coaches and swimmers based on real-time data analysis. The best result was achieved with a Random Forest classifier with a macro-averaged F1 of 95.02%. The benefit of the proposed framework was demonstrated by effectively supporting coaches while monitoring the training of several swimmers.

Search for Available Biomechanical Technologies Suitable for Use in Physical Education Classes

Introduction: One of the most important physical education tasks in school is to learn motor actions. Biomechanical technologies can promote to this process. A school lesson is different from a sports training, so it is necessary keep in mind its specifics. The purpose of the article is to analyse the existing professional biomechanical complexes for their suitability for use in physical education classes. Methods: We studied articles on sports biomechanics and selected 20 professional biomechanical complexes. These complexes can be divided into four technological groups: Optoelectronic Measurement Systems (OMSs), Electromagnetic Measurement Systems (EMSs), Image Processing Systems (IMSs), Inertial Sensory Systems (IMUs). Besides that, we identified 10 crucial categories to estimate opportunity to use biomechanical complexes in school lessons: cost, complexity of setting up and using, assistance need, portability, universality, room volume, construction traumatic, place for using, promptness, volume of data. Thus, each complex was evaluated according to 10 criteria. The biomechanical complex was excluded from further consideration if it got a critical limitation at least one of the criteria. Results: None of the professional biomechanical complexes can be considered suitable for use in physical education classes. As alternative we propose using free biomechanical software and smartphone camera with slow-motion caption.

SwimBIT: A Novel Approach to Stroke Analysis During Swim Training Based on Attitude and Heading Reference System (AHRS)

In a world where technology is assuming a pervasive role, sports sciences are also increasingly exploiting the possibilities opened by advanced sensors and intelligent algorithms. This paper focuses on the development of a convenient, practical, and low-cost system, SwimBIT, which is intended to help swimmers and coaches in performance evaluation, improvement, and injury reduction. Real-world data were collected from 13 triathletes (age 20.8 ± 3.5 years, height 173.7 ± 5.3 cm, and weight 63.5 ± 6.3 kg) with different skill levels in performing the four competitive styles of swimming in order to develop a representative database and allow assessment of the system's performance in swimming conditions. The hardware collects a set of signals from swimmers based on an attitude and heading reference system (AHRS), and a machine learning workflow for data analysis is used to extract a selection of indicators that allows analysis of a swimmer's performance. Based on the AHRS data, three novel indicators are proposed: trunk elevation, body balance, and body rotation. Experimental evaluation has shown promising results, with a 100% accuracy in swim lap segmentation, a precision of 100% in the recognition of backstroke, and a precision of 89.60% in the three remaining swimming techniques (butterfly, breaststroke, and front crawl). The performance indicators proposed here provide valuable information for both swimmers and coaches in their quest for enhancing performance and preventing injuries.

Critical scapula motions for preventing subacromial impingement in fully-tethered front-crawl swimming

The aims were to quantitatively describe the coordinated motions of the scapula and humerus during fully tethered front-crawl strokes and to test the hypothesis that scapular motion functions to reduce the risk of subacromial compression. An electromagnetic tracking device was used to record the kinematics of the thorax, humerus, and scapula on the dominant side in 17 collegiate swimmers. Because evidence suggests that compressive force develops under the coracoacromial arch when the arm elevated above 90º of arm elevation is maximally internally rotated, such shoulder configurations were measured for each participant. A series of scapulohumeral angles measured with this procedure were compared with the corresponding angles exhibited during fully tethered front-crawl swimming to identify the scapulohumeral angles indicative of subacromial compression. Additional comparison was performed without taking the scapular motion into account. Scapulohumeral angles indicative of subacromial compression were observed in 15 participants, accounting for 7.7 ± 7.1% of stroke cycle time. This duration was significantly less than the corresponding duration identified without having taken the scapular motion into account (22.6 ± 13.8% of stroke cycle time). The difference was due primarily to the unique movements of the scapular to accommodate demands imposed by stroke motions, and this supported the hypothesis.

Accuracy of human motion capture systems for sport applications; state-of-the-art review

OBJECTIVE

Sport research often requires human motion capture of an athlete. It can, however, be labour-intensive and difficult to select the right system, while manufacturers report on specifications which are determined in set-ups that largely differ from sport research in terms of volume, environment and motion. The aim of this review is to assist researchers in the selection of a suitable motion capture system for their experimental set-up for sport applications. An open online platform is initiated, to support (sport)researchers in the selection of a system and to enable them to contribute and update the overview.

DESIGN

systematic review; Method: Electronic searches in Scopus, Web of Science and Google Scholar were performed, and the reference lists of the screened articles were scrutinised to determine human motion capture systems used in academically published studies on sport analysis.

RESULTS

An overview of 17 human motion capture systems is provided, reporting the general specifications given by the manufacturer (weight and size of the sensors, maximum capture volume, environmental feasibilities), and calibration specifications as determined in peer-reviewed studies. The accuracy of each system is plotted against the measurement range.

CONCLUSION

The overview and chart can assist researchers in the selection of a suitable measurement system. To increase the robustness of the database and to keep up with technological developments, we encourage researchers to perform an accuracy test prior to their experiment and to add to the chart and the system overview (online, open access).

Analysis of a swimmer's hand and forearm in impulsive start from rest using computational fluid dynamics in unsteady flow conditions

The propulsive forces generated by the hands and arms of swimmers have so far been determined essentially by quasi-steady approaches. This study aims to quantify the temporal dependence of the hydrodynamic forces for a simple translation movement: an impulsive start from rest. The study, carried out in unsteady numerical simulation, couples the calculation of the lift and the drag on an expert swimmer hand-forearm model with visualizations of the flow and flow vortex structure analysis. The results of these simulations show that the hand and forearm hydrodynamic forces should be studied from an unsteady approach because the quasi-steady model is inadequate. It also appears that the delayed stall effect generates higher circulatory forces during a short translation at high angle of attack than forces calculated under steady state conditions. During this phase the hand force coefficients are approximately twice as large as those of the forearm. The total force coefficients are highest for angles of attack between 40° and 60°. For the same angle of attack, the forces produced when the leading edge is the thumb side are slightly greater than those produced when the leading edge is the little finger side.

Unsteady computational fluid dynamics in front crawl swimming

The development of codes and power calculations currently allows the simulation of increasingly complex flows, especially in the turbulent regime. Swimming research should benefit from these technological advances to try to better understand the dynamic mechanisms involved in swimming. An unsteady Computational Fluid Dynamics (CFD) study is conducted in crawl, in order to analyse the propulsive forces generated by the hand and forearm. The k-ω SST turbulence model and an overset grid method have been used. The main objectives are to analyse the evolution of the hand-forearm propulsive forces and to explain this relative to the arm kinematics parameters. In order to validate our simulation model, the calculated forces and pressures were compared with several other experimental and numerical studies. A good agreement is found between our results and those of other studies. The hand is the segment that generates the most propulsive forces during the aquatic stroke. As the pressure component is the main source of force, the orientation of the hand-forearm in the absolute coordinate system is an important kinematic parameter in the swimming performance. The propulsive forces are biggest when the angles of attack are high. CFD appears as a very valuable tool to better analyze the mechanisms of swimming performance and offers some promising developments, especially for optimizing the performance from a parametric study.

In-air versus underwater comparison of 3D reconstruction accuracy using action sport cameras

Action sport cameras (ASC) have achieved a large consensus for recreational purposes due to ongoing cost decrease, image resolution and frame rate increase, along with plug-and-play usability. Consequently, they have been recently considered for sport gesture studies and quantitative athletic performance evaluation. In this paper, we evaluated the potential of two ASCs (GoPro Hero3+) for in-air (laboratory) and underwater (swimming pool) three-dimensional (3D) motion analysis as a function of different camera setups involving the acquisition frequency, image resolution and field of view. This is motivated by the fact that in swimming, movement cycles are characterized by underwater and in-air phases what imposes the technical challenge of having a split volume configuration: an underwater measurement volume observed by underwater cameras and an in-air measurement volume observed by in-air cameras. The reconstruction of whole swimming cycles requires thus merging of simultaneous measurements acquired in both volumes. Characterizing and optimizing the instrumental errors of such a configuration makes mandatory the assessment of the instrumental errors of both volumes. In order to calibrate the camera stereo pair, black spherical markers placed on two calibration tools, used both in-air and underwater, and a two-step nonlinear optimization were exploited. The 3D reconstruction accuracy of testing markers and the repeatability of the estimated camera parameters accounted for system performance. For both environments, statistical tests were focused on the comparison of the different camera configurations. Then, each camera configuration was compared across the two environments. In all assessed resolutions, and in both environments, the reconstruction error (true distance between the two testing markers) was less than 3mm and the error related to the working volume diagonal was in the range of 1:2000 (3×1.3×1.5m³) to 1:7000 (4.5×2.2×1.5m³) in agreement with the literature. Statistically, the 3D accuracy obtained in the in-air environment was poorer (p<10^-5) than the one in the underwater environment, across all the tested camera configurations. Related to the repeatability of the camera parameters, we found a very low variability in both environments (1.7% and 2.9%, in-air and underwater). This result encourage the use of ASC technology to perform quantitative reconstruction both in-air and underwater environments.

Action Sport Cameras as an Instrument to Perform a 3D Underwater Motion Analysis

Action sport cameras (ASC) are currently adopted mainly for entertainment purposes but their uninterrupted technical improvements, in correspondence of cost decreases, are going to disclose them for three-dimensional (3D) motion analysis in sport gesture study and athletic performance evaluation quantitatively. Extending this technology to sport analysis however still requires a methodologic step-forward to making ASC a metric system, encompassing ad-hoc camera setup, image processing, feature tracking, calibration and 3D reconstruction. Despite traditional laboratory analysis, such requirements become an issue when coping with both indoor and outdoor motion acquisitions of athletes. In swimming analysis for example, the camera setup and the calibration protocol are particularly demanding since land and underwater cameras are mandatory. In particular, the underwater camera calibration can be an issue affecting the reconstruction accuracy. In this paper, the aim is to evaluate the feasibility of ASC for 3D underwater analysis by focusing on camera setup and data acquisition protocols. Two GoPro Hero3+ Black (frequency: 60Hz; image resolutions: 1280×720/1920×1080 pixels) were located underwater into a swimming pool, surveying a working volume of about 6m³. A two-step custom calibration procedure, consisting in the acquisition of one static triad and one moving wand, carrying nine and one spherical passive markers, respectively, was implemented. After assessing camera parameters, a rigid bar, carrying two markers at known distance, was acquired in several positions within the working volume. The average error upon the reconstructed inter-marker distances was less than 2.5mm (1280×720) and 1.5mm (1920×1080). The results of this study demonstrate that the calibration of underwater ASC is feasible enabling quantitative kinematic measurements with accuracy comparable to traditional motion capture systems.

Kinematic hand parameters in front crawl at different paces of swimming

The aim of this study was to investigate the evolution of kinematic hand parameters (sweepback angle, angle of attack, velocity, acceleration and orientation of the hand relative to the absolute coordinate system) throughout an aquatic stroke and to study the possible modifications caused by a variation of the swimming pace. Seventeen competitive swimmers swam at long distance, middle distance and sprint paces. Parameters were calculated from the trajectory of seven markers on the hand measured with an optoelectronic system. Results showed that kinematic hand parameters evolve differently depending on the pace. Angle of attack, sweepback angle, acceleration and orientation of the hand do not vary significantly. The velocity of the hand increases when the pace increases, but only during the less propulsive phases (entry and stretch and downsweep to catch). The more the pace increases and the more the absolute durations of the entry and stretch and downsweep to catch phases decrease. Absolute durations of the insweep and upsweep phases remain constant. During these phases, the propulsive hand forces calculated do not vary significantly when the pace increases. The increase of swimming pace is then explained by the swimmer's capacity to maintain propulsive phases rather than increasing the force generation within each cycle.