scholarly journals Using Wavelet Transform for Speed Fluctuation Analysis During Manikin Carry with Fins

2017 ◽  
Vol 10 (1) ◽  
pp. 272-278
Author(s):  
Susana Soares ◽  
A. Toubekis ◽  
L.M. Machado ◽  
J.P Vilas-Boas ◽  
R.J. Fernandes ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Upper Limb ◽  
Fluctuation Analysis ◽  
Stroke Index ◽  
Stroke Rate ◽  
Stroke Length ◽  
Time Points ◽  
Speed Variation ◽  
Average Maximum

Background Wavelet analysis has been used to locate speed variation changes in swimmers, but this elaborated technique was not so far tested in lifesavers carrying a manikin and using one upper limb and fins for propulsion. Objective: Our purpose was to examine the feasibility of using the wavelet analysis to locate time-points of speed variation changes in a manikin carry lifesaving race using stiff and fiber fins. Method: Fourteen male lifesavers with a mean age of 20.79±4.93 years performed two 25 m all-out manikin carry swimming races using one upper limb and stiff or fiber fins for propulsion. Speed was recorded with a speedometer and its variation was analysed using a wavelet transform analysis. Video recordings were used to measure stroke rate and stroke length within each race. Results: Wavelet analysis detected, for some lifesavers, one (stiff: 10.50±1.29 vs. fiber: 9.75±0.50 s; p>0.05) and, for other lifesavers, two time-points (stiff: 6.75±0.96 and 11.50±1.29; fiber: 7.00±1.41 and 12.00±1.83 s; p>0.05) of speed variation changes. Mean speed was no different with fin types (stiff: 1.38±0.06 vs. fiber: 1.42±0.09 m∙s-1; p>0.05), as well as average, maximum and minimum speed. Stroke rate, stroke length and stroke index did not change within each race. Conclusion: Wavelet analysis was effective in detecting one and two time-points of speed variation changes within a short duration manikin carry race independently of the type of fins used. Fiber and stiff fins showed similar biomechanical and speed variations within race changes.

Individualizing Training in Swimming: Evidence for Utilizing the Critical Speed and Critical Stroke Rate Concepts

2020 ◽  
Vol 15 (5) ◽  
pp. 617-624
Author(s):  
Eva Piatrikova ◽  
Nicholas J. Willsmer ◽  
Ana C. Sousa ◽  
Javier T. Gonzalez ◽  
Sean Williams
Keyword(s):  
Critical Speed ◽  
Interval Training ◽  
Stroke Index ◽  
Stroke Rate ◽  
Training Volume ◽  
High Intensity Interval Training ◽  
Stroke Length ◽  
And Performance ◽  
High Intensity Interval ◽  
Peak Speed

Purpose: To monitor physiological, technical, and performance responses to individualized high-intensity interval training (HIIT) prescribed using the critical speed (CS) and critical stroke rate (CSR) concepts in swimmers completing a reduced training volume program (≤30 km·wk−1) for 15 weeks. Methods: Over the 15-week period, 12 highly trained swimmers (age 16 [1] y, height 179 [8] cm, weight 66 [8] kg) completed four 3-minute all-out tests to determine CS and the finite capacity to work above CS (D′), and four 200-m tests at CS to establish a CSR estimate. Combining CS and D′, 2 HIIT sessions designed as 5 × 3-minute intervals depleting 60% of D′ and 3 × 3.5-minute intervals depleting 80% of D′ were prescribed once per week, respectively. An additional HIIT session was prescribed using CS and CSR as 10 × 150 m or 200 m at CS with 2 cycles per minute lower stroke rate than the CSR estimate. Additional monitored variables included peak speed, average speed for 150 seconds (speed150s) and 180 seconds (speed180s), competition performance and stroke length (SL), stroke count (SC), and stroke index (SI) adopted at CS. Results: At the end of the intervention, swimmers demonstrated faster CS (mean change ± 90% confidence limits: +5.4 ± 1.6%), speed150s (+2.5 ± 0.9%), speed180s (+3.0 ± 0.9%), and higher stroke rate (+6.4 ± 3.0%) and stroke index (+4.2 ± 3.6%). D′ was reduced (−25.2 ± 7.5%), whereas peak speed, SL, and SC changed only trivially. The change in the swimmers’ personal best times in the first and second main event was −1.2 ± 1.3% and −1.6 ± 0.9%, respectively. Conclusion: HIIT prescribed based on the CS and CSR concepts was associated with improvements in several physiological, technical, and performance parameters in highly trained swimmers while utilizing time- and resource-efficient approach. This was achieved despite a ≥25% reduction in training volume.

scholarly journals A COMPARISON OF RACE PERFORMANCE CHARACTERISTICS BETWEEN ELITE MALE 50-M AND 100-M FREESTYLE SWIMMERS BASED ON THEIR RESULTS

2020 ◽  
pp. 453
Author(s):  
Marko Đurović ◽  
Damira Vranešić-Hadžimehmedović ◽  
Miloš Paunović ◽  
Dejan Madić ◽  
Tomislav Okičić
Keyword(s):  
Cluster Analysis ◽  
Performance Characteristics ◽  
Stroke Index ◽  
Stroke Rate ◽  
Stroke Length ◽  
Research Results ◽  
Long Course ◽  
Race Performance

The aim of this research was to determine the differences in specific race performance characteristics of male swimmers in the 50-m and 100-m freestyle at the Serbia Open Championship 2017 (long-course). The overall sample included in this study consisted of 40 swimmers divided by a K-Means Cluster Analysis into three groups in relation to the results in the 50-m freestyle (G1_50, T50=23.53±.27 s, n=6; G2_50, T50=24.54±.33 s, n=18; G3_50, T50=25.52±.33 s, n=16), and 55 swimmers also divided into three groups in relation to the results in the 100-m freestyle (G1_100, T100=50.99±.82s, n=10; G2_100, T100=53.41±.48 s, n=17; G3_100, T100=56.13±1.32 s, n=28). The research results indicate that there is a difference in the specific race performance characteristics in relation to the achieved results in the 50-m freestyle, including: t10_50 (F=16.79, p=.000), SL2_50 (F=4.44, p=.019) and SI2_50 (F=13.49, p=.000), also in the 100-m freestyle, including: t10_100 (F=36.45, p=.000), SL1_100 (F=5.77, p=.005), SL2_100 (F=17.47, p=.000), SL3_100 (F=7.72, p=.001), SL4_100 (F=9.84, p=.000), SI1_100 (F=5.12, p=.009), SI2_100 (F=45.97, p=.000), SI3_100 (F=13.86, p=.000), SI4_100 (F=31.23, p=.000), SR1_100 (F=4.12, p=.022) and SR2_100 (F=6.37, p=.003). Based on these results we can draw the conclusion that swimmers who have better control over their race performance characteristics during all the segments of the race, including stroke length, stroke index and stroke rate have the potential of being faster in the 50-m and 100-m freestyle. 

scholarly journals Physiological and Biomechanical Evaluation of a Training Macrocycle in Children Swimmers

Sports ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 57
Author(s):  
Sara Ferreira ◽  
Diogo Carvalho ◽  
Ana Monteiro ◽  
J. Abraldes ◽  
J. Vilas-Boas ◽  
...  
Keyword(s):  
Physiological Responses ◽  
Maximum Intensity ◽  
Stroke Index ◽  
Stroke Rate ◽  
Physiological Changes ◽  
Front Crawl ◽  
Stroke Length ◽  
Performance Change ◽  
Biomechanical Evaluation ◽  
Performance Gains

Physiological responses related to 400-m front crawl performance were examined in a 11-week training macrocycle in children 11.6 ± 1.2 years old. Fourteen girls and twenty-nine boys completed a maximum intensity 400-m test, at the beginning (Τ1) and at the end of four weeks of general preparation (Τ2), four weeks of specific preparation (Τ3), and three weeks of the competitive period (Τ4). Blood lactate (La), blood glucose (Glu) and heart rate were measured post effort. Stroke rate (SR), stroke length (SL) and stroke index (SI) were measured during the test. The 400-m time was decreased at T2, T3, and T4 compared to T1 by 4.2 ± 4.9, 7.5 ± 7.0, and 8.6 ± 7.3% (p < 0.05) and at T3 and T4 compared to T2 by 3.1 ± 4.3 and 4.2 ± 4.6%, respectively (p < 0.05). La was not different between tests (p > 0.05) and Glu was decreased at T3 compared to other testing moments (p < 0.05). SR, SL, and SI were higher at T3 and T4 compared to T1 (p < 0.05). SL and SI were also increased at T4 compared to T2 (p < 0.05). Performance changes from T1 to T2 were related to SL and SI changes (r = 0.45 and 0.83, p < 0.05), and subsequent changes between T2 to T3 were related to SR, SI, La, and Glu changes (r = 0.48, 0.68, 0.34, and 0.42, p < 0.05). Performance change from T3 to T4 was related to SL, SI, and La modifications (r = 0.34, 0.70, and 0.53, p < 0.05). Performance gains may be related to various biomechanical or physiological changes according to training macrocycle structure.

scholarly journals Is Swimmers’ Performance Influenced by Wetsuit Use?

2020 ◽  
Vol 15 (1) ◽  
pp. 46-51 ◽  
Author(s):  
Ana Gay ◽  
Gracia López-Contreras ◽  
Ricardo J. Fernandes ◽  
Raúl Arellano
Keyword(s):  
Blood Lactate ◽  
Perceived Exertion ◽  
Lactate Concentration ◽  
Blood Lactate Concentration ◽  
Swimming Pool ◽  
Rating Of Perceived Exertion ◽  
Stroke Index ◽  
Stroke Rate ◽  
Stroke Length ◽  
Propelling Efficiency

Purpose: To observe changes in performance, physiological, and general kinematic variables induced by the use of wetsuits vs swimsuits in both swimming-pool and swimming-flume conditions. Methods: In a randomized and counterbalanced order, 33 swimmers (26.46 [11.72] y old) performed 2 × 400-m maximal front crawl in a 25-m swimming pool (with wetsuit and swimsuit), and their mean velocities were used later in 2 swimming-flume trials with both suits. Velocity, blood lactate concentration, heart rate (HR), Borg scale (rating of perceived exertion), stroke rate, stroke length (SL), stroke index, and propelling efficiency were evaluated. Results: The 400-m performance in the swimming pool was 0.07 m·s−1 faster when using the wetsuit than when using the swimsuit, evidencing a reduction of ∼6% in time elapsed (P < .001). Maximal HR, maximal blood lactate concentration, rating of perceived exertion, stroke rate, and propelling efficiency were similar when using both swimsuits, but SL and stroke index presented higher values with the wetsuit in both the swimming pool and the swimming flume. Comparing swimming conditions, maximal HR and maximal blood lactate concentration were lower, and SL, stroke index, and propelling efficiency were higher when swimming in the flume than when swimming in the pool with both suits. Conclusions: The 6% velocity improvement was the result of an increase of 4% in SL. Swimmers reduced stroke rate and increased SL to benefit from the hydrodynamic reduction of the wetsuit and increase their swimming efficiency. Wetsuits might be utilized during training seasons to improve adaptations while swimming.

Front Crawl Technical Characterization of 11- to 13-Year-Old Swimmers

2012 ◽  
Vol 24 (3) ◽  
pp. 409-419 ◽  
Author(s):  
Ana Silva ◽  
Pedro Figueiredo ◽  
Susana Soares ◽  
Ludovic Seifert ◽  
João Paulo Vilas-Boas ◽  
...  
Keyword(s):  
Total Sample ◽  
Stroke Index ◽  
Stroke Rate ◽  
Front Crawl ◽  
Stroke Length ◽  
Underwater Cameras ◽  
Elite Swimmers ◽  
Biomechanical Parameters ◽  
Catch Up

Our aim was to characterize front crawl swimming performed at very high intensity by young practitioners. 114 swimmers 11–13 years old performed 25 m front crawl swimming at 50 m pace. Two underwater cameras was used to assess general biomechanical parameters (velocity, stroke rate, stroke length and stroke index) and interarm coordination (Index of Coordination), being also identified each front crawl stroke phase. Swimmers presented lower values in all biomechanical parameters than data presented in studies conducted with older swimmers, having the postpubertal group closest values to adult literature due to their superior anthropometric and maturational characteristics. Boys showed higher velocity and stroke index than girls (as reported for elite swimmers), but higher stroke rate than girls (in opposition to what is described for adults). In addition, when considering the total sample, a higher relationship was observed between velocity and stroke length (than with stroke rate), indicating that improving stroke length is a fundamental skill to develop in these ages. Furthermore, only catch-up coordination mode was adopted (being evident a lag time between propulsion of the arms), and the catch and the pull phases presented the highest and smallest durations, respectively.

Classification of Acceleration Waveforms during Walking by Wavelet Transform

1997 ◽  
Vol 36 (04/05) ◽  
pp. 356-359 ◽  
Author(s):  
M. Sekine ◽  
M. Ogawa ◽  
T. Togawa ◽  
Y. Fukui ◽  
T. Tamura
Keyword(s):  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Center Of Gravity ◽  
Dynamic Responses ◽  
Sequential Data ◽  
Acceleration Signal ◽  
Continuous Dynamic

Abstract:In this study we have attempted to classify the acceleration signal, while walking both at horizontal level, and upstairs and downstairs, using wavelet analysis. The acceleration signal close to the body’s center of gravity was measured while the subjects walked in a corridor and up and down a stairway. The data for four steps were analyzed and the Daubecies 3 wavelet transform was applied to the sequential data. The variables to be discriminated were the waveforms related to levels -4 and -5. The sum of the square values at each step was compared at levels -4 and -5. Downstairs walking could be discriminated from other types of walking, showing the largest value for level -5. Walking at horizontal level was compared with upstairs walking for level -4. It was possible to discriminate the continuous dynamic responses to walking by the wavelet transform.

Spatial-temporal variables for swimming coaches: A comparison study between video and TritonWear sensor

2021 ◽  
pp. 174795412110137
Author(s):  
Robin Pla ◽  
Thibaut Ledanois ◽  
Escobar David Simbana ◽  
Anaël Aubry ◽  
Benjamin Tranchard ◽  
...  
Keyword(s):  
Swimming Performance ◽  
Video Recording ◽  
Open Water ◽  
Percentage Error ◽  
Stroke Index ◽  
Wearable Sensor ◽  
Stroke Length ◽  
Video Recordings ◽  
Temporal Variables ◽  
Training Sets

The main aim of this study was to evaluate the validity and the reliability of a swimming sensor to assess swimming performance and spatial-temporal variables. Six international male open-water swimmers completed a protocol which consisted of two training sets: a 6×100m individual medley and a continuous 800 m set in freestyle. Swimmers were equipped with a wearable sensor, the TritonWear to collect automatically spatial-temporal variables: speed, lap time, stroke count (SC), stroke length (SL), stroke rate (SR), and stroke index (SI). Video recordings were added as a “gold-standard” and used to assess the validity and the reliability of the TritonWear sensor. The results show that the sensor provides accurate results in comparison with video recording measurements. A very high accuracy was observed for lap time with a mean absolute percentage error (MAPE) under 5% for each stroke (2.2, 3.2, 3.4, 4.1% for butterfly, backstroke, breaststroke and freestyle respectively) but high error ranges indicate a dependence on swimming technique. Stroke count accuracy was higher for symmetric strokes than for alternate strokes (MAPE: 0, 2.4, 7.1 & 4.9% for butterfly, breaststroke, backstroke & freestyle respectively). The other variables (SL, SR & SI) derived from the SC and the lap time also show good accuracy in all strokes. The wearable sensor provides an accurate real time feedback of spatial-temporal variables in six international open-water swimmers during classical training sets (at low to moderate intensities), which could be a useful tool for coaches, allowing them to monitor training load with no effort.

scholarly journals Energy Analysis Method Based on Wavelet Transform for Sensor Fault Diagnosis

2011 ◽  
Vol 2-3 ◽  
pp. 117-122 ◽  
Author(s):  
Peng Peng Qian ◽  
Jin Guo Liu ◽  
Wei Zhang ◽  
Ying Zi Wei
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Wavelet Analysis ◽  
Energy Analysis ◽  
Sensor Faults ◽  
Analysis Method ◽  
Sensor Fault ◽  
Fault Type ◽  
Ideal Tool ◽  
Non Stationary Signal

Wavelet analysis with its unique features is very suitable for analyzing non-stationary signal, and it can also be used as an ideal tool for signal processing in fault diagnosis. The characteristics of the faults and the necessary information on the diagnosis can be constructed and extracted respectively by wavelet analysis. Though wavelet analysis is specialized in characteristics extraction, it can not determine the fault type. So this paper has proposed an energy analysis method based on wavelet transform. Experiment results show the method is very effective for sensor fault diagnosis, because it can not only detect the sensor faults, but also determine the fault type.

scholarly journals Critical stroke rate as a parameter for evaluation in swimming

2013 ◽  
Vol 19 (4) ◽  
pp. 724-729 ◽  
Author(s):  
Marcos Franken ◽  
Fernando Diefenthaeler ◽  
Felipe Collares Moré ◽  
Ricardo Peterson Silveira ◽  
Flávio Antônio de Souza Castro
Keyword(s):  
Aerobic Capacity ◽  
Swimming Speed ◽  
Critical Speed ◽  
Stroke Rate ◽  
Front Crawl ◽  
Stroke Length ◽  
Competitive Swimmers

The purpose of this study was to investigate the critical stroke rate (CSR) compared to the average stroke rate (SR) when swimming at the critical speed (CS). Ten competitive swimmers performed five 200 m trials at different velocities relative to their CS (90, 95, 100, 103 and 105%) in front crawl. The CSR was significantly higher than the SR at 90% of the CS and lower at 105% of the CS. Stroke length (SL) at 103 and 105% of the CS were lower than the SL at 90, 95, and 100% of the CS. The combination of the CS and CSR concepts can be useful for improving both aerobic capacity/power and technique. CS and CSR could be used to reduce the SR and increase the SL, when swimming at the CS pace, or to increase the swimming speed when swimming at the CSR.

THE ADVANTAGE OFTHEWAVELET TRANSFORM IN PROCESSING OF SPEECH SIGNALS

2021 ◽  
Vol 4 (3) ◽  
pp. 37-41
Author(s):  
Sayora Ibragimova ◽  
Keyword(s):  
Fourier Transform ◽  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Speech Processing ◽  
High Performance ◽  
Speech Sound ◽  
Digital Signal ◽  
Speech Signals ◽  
Multi Scale ◽  
Processing Of Speech Signals

This work deals with basic theory of wavelet transform and multi-scale analysis of speech signals, briefly reviewed the main differences between wavelet transform and Fourier transform in the analysis of speech signals. The possibilities to use the method of wavelet analysis to speech recognition systems and its main advantages. In most existing systems of recognition and analysis of speech sound considered as a stream of vectors whose elements are some frequency response. Therefore, the speech processing in real time using sequential algorithms requires computing resources with high performance. Examples of how this method can be used when processing speech signals and build standards for systems of recognition.Key words: digital signal processing, Fourier transform, wavelet analysis, speech signal, wavelet transform

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