ArticleFrontiers in bioengineering and biotechnology2020
A Novel Macro-Micro Approach for Swimming Analysis in Main Swimming Techniques Using IMU Sensors.
Article in Frontiers in bioengineering and biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 32 citations in OpenAlex.
- Quantification of Lower Limb Kinematics During Swimming in Individuals with Spinal Cord Injury.Sensors (Basel, Switzerland) · 2025Article
- Automated Detection of Change of Direction in Basketball Players Using Xsens Motion Tracking.Sensors (Basel, Switzerland) · 2025Article
- Case Report: Impact of dolphin kick implementation during backstroke finishes on swimming performance. From regional to olympic-level swimmers. A comparative case study.Frontiers in sports and active living · 2025Article
- In-field assessment of change-of-direction ability with a single wearable sensor.Scientific reports · 2023Article
- Commentaries on Viewpoint: Hoping for the best, prepared for the worst: can we perform remote data collection in sport sciences?Journal of applied physiology (Bethesda, Md. : 1985) · 2022Article
- A Focused Review on the Flexible Wearable Sensors for Sports: From Kinematics to Physiologies.Micromachines · 2022Review
- Automatic Swimming Activity Recognition and Lap Time Assessment Based on a Single IMU: A Deep Learning Approach.Sensors (Basel, Switzerland) · 2022Article
- SmartSwim, a Novel IMU-Based Coaching Assistance.Sensors (Basel, Switzerland) · 2022Article
- Monitoring weekly progress of front crawl swimmers using IMU-based performance evaluation goal metrics.Frontiers in bioengineering and biotechnology · 2022Article
- Framework for Intelligent Swimming Analytics with Wearable Sensors for Stroke Classification.Sensors (Basel, Switzerland) · 2021Article
- Swimming Phase-Based Performance Evaluation Using a Single IMU in Main Swimming Techniques.Frontiers in bioengineering and biotechnology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.