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A Novel Macro-Micro Approach for Swimming Analysis in Main Swimming Techniques Using IMU Sensors.

ABSTRACT: Inertial measurement units (IMU) are proven as efficient tools for swimming analysis by overcoming the limits of video-based systems application in aquatic environments. However, coaches still believe in the lack of a reliable and easy-to-use analysis system for swimming. To provide a broad view of swimmers' performance, this paper describes a new macro-micro analysis approach, comprehensive enough to cover a full training session, regardless of the swimming technique. Seventeen national level swimmers (5 females, 12 males, 19.6 ± 2.1 yrs) were equipped with six IMUs and asked to swim 4 × 50 m trials in each swimming technique (i.e., frontcrawl, breaststroke, butterfly, and backstroke) in a 25 m pool, in front of five 2-D cameras (four under water and one over water) for validation. The proposed approach detects swimming bouts, laps, and swimming technique in macro level and swimming phases in micro level on all sensor locations for comparison. Swimming phases are the phases swimmers pass from wall to wall (wall push-off, glide, strokes preparation, swimming, and turn) and micro analysis detects the beginning of each phase. For macro analysis, an overall accuracy range of 0.83-0.98, 0.80-1.00, and 0.83-0.99 were achieved, respectively, for swimming bouts detection, laps detection and swimming technique identification on selected sensor locations, the highest being achieved with sacrum. For micro analysis, we obtained the lowest error mean and standard deviation on sacrum for the beginning of wall-push off, glide and turn (-20 ± 89 ms, 4 ± 100 ms, 23 ± 97 ms, respectively), on shank for the beginning of strokes preparation (0 ± 88 ms) and on wrist for the beginning of swimming (-42 ± 72 ms). Comparing the swimming techniques, sacrum sensor achieves the smallest range of error mean and standard deviation during micro analysis. By using the same macro-micro approach across different swimming techniques, this study shows its efficiency to detect the main events and phases of a training session. Moreover, comparing the results of both macro and micro analyses, sacrum has achieved relatively higher amounts of accuracy and lower mean and standard deviation of error in all swimming techniques.

SUBMITTER: Hamidi Rad M

PROVIDER: S-EPMC7841373 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A Novel Macro-Micro Approach for Swimming Analysis in Main Swimming Techniques Using IMU Sensors.

Hamidi Rad Mahdi M Gremeaux Vincent V Dadashi Farzin F Aminian Kamiar K

Frontiers in bioengineering and biotechnology 20210114

Inertial measurement units (IMU) are proven as efficient tools for swimming analysis by overcoming the limits of video-based systems application in aquatic environments. However, coaches still believe in the lack of a reliable and easy-to-use analysis system for swimming. To provide a broad view of swimmers' performance, this paper describes a new macro-micro analysis approach, comprehensive enough to cover a full training session, regardless of the swimming technique. Seventeen national level s ...[more]

PMID: 33520955

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Project description:Comprehensive monitoring of performance is essential for swimmers and swimming coaches to optimize the training. Regardless of the swimming technique, the swimmer passes various swimming phases from wall to wall, including a dive into the water or wall push-off, then glide and strokes preparation and finally, swimming up to the turn. The coach focuses on improving the performance of the swimmer in each of these phases. The purpose of this study was to assess the potential of using a sacrum-worn inertial measurement unit (IMU) for performance evaluation in each swimming phase (wall push-off, glide, stroke preparation and swimming) of elite swimmers in four main swimming techniques (i.e. front crawl, breaststroke, butterfly and backstroke). Nineteen swimmers were asked to wear a sacrum IMU and swim four one-way 25 m trials in each technique, attached to a tethered speedometer and filmed by cameras in the whole lap as reference systems. Based on the literature, several goal metrics were extracted from the instantaneous velocity (e.g. average velocity per stroke cycle) and displacement (e.g. time to reach 15 m from the wall) data from a tethered speedometer for the swimming phases, each one representing the goodness of swimmer's performance. Following a novel approach, that starts from swimming bout detection and continues until detecting the swimming phases, the IMU kinematic variables in each swimming phase were extracted. The highly associated variables with the corresponding goal metrics were detected by LASSO (least absolute shrinkage and selection operator) variable selection and used for estimating the goal metrics with a linear regression model. The selected kinematic variables were relevant to the motion characteristics of each phase (e.g. selection of propulsion-related variables in wall push-off phase), providing more interpretability to the model. The estimation reached a determination coefficient (R2) value more than 0.75 and a relative RMSE less than 10% for most goal metrics in all swimming techniques. The results show that a single sacrum IMU can provide a wide range of performance-related swimming kinematic variables, useful for performance evaluation in four main swimming techniques.

Project description:Flagella and cilia are cellular appendages that inherit essential functions of microbial life including sensing and navigating the environment. In order to propel a swimming microorganism they displace the surrounding fluid by means of periodic motions, while precisely timed modulations of their beating patterns enable the cell to steer towards or away from specific locations. Characterizing the dynamic forces, however, is challenging and typically relies on indirect experimental approaches. Here, we present direct in vivo measurements of the dynamic forces of motile Chlamydomonas reinhardtii cells in controlled environments. The experiments are based on partially aspirating a living microorganism at the tip of a micropipette force sensor and optically recording the micropipette's position fluctuations with high temporal and sub-pixel spatial resolution. Spectral signal analysis allows for isolating the cell-generated dynamic forces caused by the periodic motion of the flagella from background noise. We provide an analytic, elasto-hydrodynamic model for the micropipette force sensor and describe how to obtain the micropipette's full frequency response function from a dynamic force calibration. Using this approach, we measure the amplitude of the oscillatory forces during the swimming activity of individual Chlamydomonas reinhardtii cells of 26 ± 5 pN, resulting from the coordinated flagellar beating with a frequency of 49 ± 5 Hz. This dynamic micropipette force sensor technique generalizes the applicability of micropipettes as force sensors from static to dynamic force measurements, yielding a force sensitivity in the piconewton range. In addition to measurements in bulk liquid environment, we study the dynamic forces of the biflagellated microswimmer in the vicinity of a solid/liquid interface. As we gradually decrease the distance of the swimming microbe to the interface, we measure a significantly enhanced force transduction at distances larger than the maximum extent of the beating flagella, highlighting the importance of hydrodynamic interactions for scenarios in which flagellated microorganisms encounter surfaces.

Project description:BackgroundWalking speed is often used in the clinic to assess the level of gait impairment following stroke. Nonetheless, post-stroke individuals may employ the same walking speed but at a distinct movement quality. The main objective of this study was to explore a novel movement quality metric, the estimation of gait smoothness by the spectral arc length (SPARC), in individuals with a chronic stroke displaying mild/moderate or severe motor impairment while walking in an outdoor environment. Also, to quantify the correlation between SPARC, gait speed, motor impairment, and lower limb spasticity focused on understanding the relationship between the movement smoothness metric and common clinical assessments.MethodsThirty-two individuals with a chronic stroke and 32 control subjects participated in this study. The 10 meters walking test (10 MWT) was performed at the self-selected speed in an outdoor environment. The 10 MWT was instrumented with an inertial measurement unit system (IMU), which afforded the extraction of trunk angular velocities (yaw, roll, and pitch) and subsequent SPARC calculation.ResultsMovement smoothness was not influenced by gait speed in the control group, indicating that SPARC may constitute an additional and independent metric in the gait assessment. Individuals with a chronic stroke displayed reduced smoothness in the yaw and roll angular velocities (lower SPARC) compared with the control group. Also, severely impaired participants presented greater variability in smoothness along the 10 MWT. In the stroke group, a smoother gait in the pitch angular velocity was correlated with lower limb spasticity, likely indicating adaptive use of spasticity to maintain the pendular walking mechanics. Conversely, reduced smoothness in the roll angular velocity was related to pronounced spasticity.ConclusionsIndividuals with a chronic stroke displayed reduced smoothness in the yaw and roll angular velocities while walking in an outdoor environment. The quantification of gait smoothness using the SPARC metric may represent an additional outcome in clinical assessments of gait in individuals with a chronic stroke.

Dataset Information

A Novel Macro-Micro Approach for Swimming Analysis in Main Swimming Techniques Using IMU Sensors.

Publications

A Novel Macro-Micro Approach for Swimming Analysis in Main Swimming Techniques Using IMU Sensors.

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