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Creating the right environment for VI training
Ciro Winckler APB/CPB/UNIFESP
Professor of São Paulo Federal University
Athletics Technical Coordinator of Brazil NPC
Member of IPC Athletics Coach Council
Member of Brazilian Paralympic Academy
Ciro Winckler
• Vision
• VI Classification
• Motor Performance in Athletics
• Training
Agenda
Visual Impairment
Vision is impacted by either an impairment of the eye structure, optical nerves or optical pathways, or visual cortex of the central brain.
IPC, 2015Visual Field
Visual Acuity
Visual Acuity
Distance where The athlete can see and define the object
Visual Field
VI Classification• Model Started of 1970 decade
• Legal Blindness
• B1 Blind
• B2 Low Vision
• B3 Low Vision
VI Classification• Decade of 2000
• Modification of the System
• 11
Visual acuity poorer than LogMAR 2.6.
• 12 Visual acuity ranging from LogMAR 1.5 to 2.6 (inclusive) and/or Visual field constricted to a diameter of less than 10 degrees.
• 13 Visual acuity ranging from LogMAR 1.4 to 1.0 (inclusive) and/or Visual field constricted to a diameter of less than 40 degrees.
VI Classification
50 Faculteit der Bewegingswetenschappen
RESEARCH APPROACH 1 IMPAIRMENT-PERFORMANCE RELATIONSHIP
S13 S12 S11
S13 S12 S11NE
NE
R² = 0.687
R² = 0.373
VI Classification Research Expert Meeting
Day II
Amsterdam 23-25th January 2015
Eye Mask or Opaque Glass
Visual FunctionsVisualAcuity• Sta.c• Dinamic
BinocularVisuion
VisualField
ColorvisionLuminosityAdapta.on
VisualIntelligence
Contrast
Visual Inteligency
Limita&on
Experience
Time of the impairment
Time Life
Birth
Cong
enita
l
Brain
Maturatio
n
Acqu
ired
Motor Development
Can you do the Description?
Can you do the Description?
Can you do the Description?
Can you do the Description?
Motor Performance in Athletics
Sprinter
Midle and Long
Distance runners
Jumper
Thrower
11 12 13 Guide
Are Guides necessary only for Track events?
Hay, J.G., Miller, J.A. and Canterna, R.W. (1986). The techniques of elite male long jumpers. Journal of Biomechanics, 19, 855-866.
athlete’s physical capabilities. (In long jumping, the optimum technique is usually to use the fastest possible run-up and to spring upwards as much as possible at takeoff.)
0
2
4
6
8
10
0 2 4 6 8 10 12run-up speed (m/s)
jum
p di
stan
ce (m
)
Cross-sectional study (Hay, 1993)
Intervention study (Current study)
Figure 1. Comparison of results from a cross-sectional study and a technique intervention study. (Cross-sectional data courtesy of Jim Hay.) In contrast, the intervention study reported here considered only a single athlete. Although the jumps by the athlete were always at maximum effort, the jumps with the slower run-ups were not employing the optimum technique that would result in the maximum possible jump distance. However, at any given run-up speed the technique used by the athlete was close to the optimum for that run-up speed. This is a reasonable assumption because the athlete was highly experienced and regularly performed jumps from a short run-up as part of his normal training program. The trend line for the intervention study intersects that for the cross-sectional study at a jump distance of about 8 m. This is expected because data points in this region correspond to conditions identical to those for the cross-sectional study; namely, jumping for maximum possible distance using a near-optimum technique. Speed Training: The results from the technique intervention study confirm the role of speed work in the training program of the long jump athlete. The faster your run-up, the farther you will jump. The present study indicates a rate of improvement of 8 cm per 0.1 m/s increase in run-up speed. A long jumper may improve his run-up speed by using a better running technique or by increasing the strength of the muscles used in sprinting (or by a combination of the two). We contend that the trend from the technique intervention study indicates the improvement to be expected solely through better running technique. Note that the intervention study considers a single athlete with a unique combination of body size, muscular strengths, and technical proficiency. The trend line for this athlete indicates the expected improvement if all these characteristics are unchanged, except that the athlete is able to a produce a faster run-up speed. During the technique intervention study, the muscular strength of the athlete did not change, and so the trend line must therefore indicate the improvement to be expected through better running technique. Strength Training: We also contend that Hay’s trend line indicates the effect of muscular strength on long jump performance, rather than the effect of run-up speed. Recall that this study considers athletes of different ability. It is well accepted that athletes with stronger dynamic leg strength can run faster and can exert a greater force at takeoff (Young, 1995). We believe that the main cause of variations in ability among athletes is differences in muscular strength, rather than differences in body size or technical proficiency. That is, the performances in the upper right of Figure 1 (for the cross-sectional study) are produced by strong athletes who can therefore run fast and exert large takeoff forces, whereas the
Sprinter
Midle and Long
Distance runners
Jumper
Thrower
11 12 13 GuideC o m p e t i t i o n
T r a i n i n g
State of Art
BalanceCoordination
Speed of Learning
Incidental learning
VO2
Sedentarism Psycologial Profile
Low levels of Physical Activity
Leverenz, 2009
Sedentarism caused by the visual limitation or
absense of stimulation
STANFORD, 1975, HOPKINS, et al. 1987, COMITÉ OLIMPICO ESPANHOL, 1992,
MOURA E CASTRO, COSTA, FREITAS, 1992, WILLIANS, et al. 1996
Sedentarism
VO2
VO2 max. associated with the visual acuity level Hopkins et al. 1987, Leverenz, 2009
VO2
People with blindness that are sys tematic physical activity practitioners can develop similar results of the VO2 of people without disabilities KOBBERLING; JANKOWSK & Leger, 1991
T h e l o w v i s u a l capacity causes a r e d u c t i o n i n mechanical efficiency of movement, thus demand more energy e x p e n d i t u r e a n d increased fatigue
STAMFORD, 1975, HOPKINS et al., 1987
Coordination
Balance
VIwithout VI
Psychological Profile
VI
BRAMS Nome Means Athlete and Guide
T-Escore FATOR T-Escore Tension Depression Anger Vigour Fatigue Confusion
80+ 79 78 77 76 75 74 73 72 71 70 69 68 67 66 65 64 63 62 61 60 59 58 57 56 55 54 53 52 51 50 49 48 47 46 45 44 43 42 41 40 39 38 37 36 35 34 33 32 31 30 29
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
5
4
3
2
1
0
5
4
3
2
1
0
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
11
10
9
8
7
6
5
4
3
2
1
0
9
8
7
6
5
4
3
2
1
0
80+ 79 78 77 76 75 74 73 72 71 70 69 68 67 66 65 64 63 62 61 60 59 58 57 56 55 54 53 52 51 50 49 48 47 46 45 44 43 42 41 40 39 38 37 36 35 34 33 32 31 30 29
Guides
Athletes
BRAMS
Nome Gold Medalist and guide
T-Escore FATOR T-Escore Tension Depression Anger Vigour Fatigue Confusion
80+ 79 78 77 76 75 74 73 72 71 70 69 68 67 66 65 64 63 62 61 60 59 58 57 56 55 54 53 52 51 50 49 48 47 46 45 44 43 42 41 40 39 38 37 36 35 34 33 32 31 30 29
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
5
4
3
2
1
0
5
4
3
2
1
0
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
11
10
9
8
7
6
5
4
3
2
1
0
9
8
7
6
5
4
3
2
1
0
80+ 79 78 77 76 75 74 73 72 71 70 69 68 67 66 65 64 63 62 61 60 59 58 57 56 55 54 53 52 51 50 49 48 47 46 45 44 43 42 41 40 39 38 37 36 35 34 33 32 31 30 29
guide
Athlete
Injuries in VI athletics
were not recorded. Where athletes suffered a recurrent injury,the injury was counted only once.
Statistical analysis. Data were collated using MicrosoftExcel 2007! and analyzed using the SPSS 14.0!. Descriptivestatistics were calculated and used to determine the total andrelative frequency of injuries. The Shapiro–Wilk test wasused to determine the normality of data distribution. Wherethe normality of data distribution could be assumed, a one-way ANOVA test for independent groups was used to assessdifferences between visual classes and track and field events,and a t-test was used to compare between sexes. Alterna-tively, the Kruskal–Wallis test was used to assess differencesbetween sexes and visual classes. The acceptance level ofsignificance was set at P G 0.05.
RESULTS
Forty athletes participated in this study and 31 suffered atotal of 77 sports injuries (Table 1), which correspond to aprevalence of 78%, a clinical incidence of 1.93 injuries perparticipating athlete (Table 1), and an average incidence rateof 0.39 injuries per athlete per competition.
Female athletes presented a slightly higher prevalenceand clinical incidence when compared to male athletes(Table 1), but this was not statistically significant (P 9 0.05).With regard to visual class, T/F11 athletes presented a
slightly higher prevalence of sports injuries, followed byT/F12 and T/F13 athletes. However, T/F12 athletes showedslightly higher clinical incidence, followed by T/F11 andT/F13 (Table 1). There were no statistically significant dif-ferences observed between classifications or groups in theseepidemiological data (P 9 0.05). When comparing the epi-demiological data between event types such as track (sprint,medium, and long distance) and field (throws and jumps), nostatistically significant differences were observed.
TABLE 1. Number of participant athletes, injured athletes, sports injuries, prevalence, and clinical incidence according to visual class, event type, and sex.
Visual Class Event Type Sex
Competitions T/F11 T/F12 T/F13 Track Field Female Male Total
ParticipantsParalympic Games 2004 4 5 2 11 — 5 6 11IBSA Para Pan-American Games 2005 8 12 8 25 3 7 21 28IBSA World Championship 2007 9 12 7 25 3 8 20 28Para Pan-American Games 2007 7 8 4 19 — 6 13 19Paralympic Games 2008 8 10 4 22 — 8 14 22Total 14 15 11 35 5 12 28 40
Injured athletesParalympic Games 2004 3 5 1 8 — 4 5 9IBSA Para Pan-American Games 2005 3 7 3 12 1 4 9 13IBSA World Championship 2007 6 7 4 14 3 6 11 17Para Pan-American Games 2007 2 4 3 9 — 4 5 9Paralympic Games 2008 2 6 1 8 — 3 5 8Total 12 12 7 27 3 11 20 31
No. sports injuriesParalympic Games 2004 3 7 1 11 — 5 6 11IBSA Para Pan-American Games 2005 5 8 3 15 1 4 12 16IBSA World Championship 2007 7 14 7 22 6 8 20 28Para Pan-American Games 2007 3 4 4 11 — 6 5 11Paralympic Games 2008 3 6 2 11 — 3 8 11Total 21 39 17 70 7 27 50 77
Prevalence (%)Paralympic Games 2004 75 100 50 73 — 80 83 82IBSA Para Pan-American Games 2005 38 58 38 48 33 57 43 46IBSA World Championship 2007 67 58 57 56 100 75 55 61Para Pan-American Games 2007 29 50 75 47 — 67 38 47Paralympic Games 2008 25 60 25 36 — 38 36 36Total 86 80 64 77 60 92 71 78
Clinical incidenceParalympic Games 2004 0.8 1.4 0.5 1.00 — 1.0 1.0 1.0IBSA Para Pan-American Games 2005 0.6 0.7 0.4 0.60 0.33 0.6 0.6 0.6IBSA World Championship 2007 0.8 1.2 1.0 0.88 2.00 1.0 1.0 1.0Para Pan-American Games 2007 0.4 0.5 1.0 0.58 — 1.0 0.4 0.6Paralympic Games 2008 0.4 0.6 0.5 0.50 — 0.4 0.6 0.5Total 1.5 2.6 1.5 2.00 1.40 2.3 1.8 1.9
FIGURE 1—Mechanism of sport injury in track and field paralympiccompetitions.
http://www.acsm-msse.org910 Official Journal of the American College of Sports Medicine
EPIDEM
IOLO
GY
Copyright © 2013 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.With respect to injury mechanisms (Fig. 1), overuse in-
juries were the most prevalent (82%), and traumatic injuriesconstituted the remaining smaller proportion (P G 0.05).
Figure 2 represents the distribution of sport injuries bybody segment, where the lower limbs appeared to be mostaffected.
The frequency of injuries by body region (Fig. 3) revealedthat the thighs were most affected.
The frequency of sport injuries varied by diagnosis (Fig. 4),with the greatest frequencies reported as tendinopathy andspasm.
DISCUSSION
The results of this study demonstrate that the overall clin-ical incidence was 1.93 injuries per injured Paralympic athleteduring the period of observation, indicating that many athletessustained multiple injuries (21). Paralympic track and fieldis considered a low risk sport when compared to other Para-lympic sports modalities (10). In terms of sports injuryprevalence, we demonstrated an overall value of 78%, vary-ing from 82% to 36% across the five competitions observed
(Table 1). A previous study in track and field athletes withoutdisability observed an injury prevalence of 42.8% (17).
When comparing sports injuries by sex, female athletespresented a slightly higher prevalence (92% vs 71%) andclinical incidence (2.3 vs 1.8 injuries per athlete) of injury(Table 1) compared to males. This trend suggests that ahigher proportion of female athletes were injured and thosethat were sustained more injuries per athlete compared tomales. While these observations were not significantly dif-ferent, this may be a function of the relatively small samplesize stemming from a single nation team. There seems to bevery little difference in the pattern of injuries between menand women when comparing the same sports among able-bodied athletes (30). A review article suggests that the risk ofsports injuries is lower in female than in male athletes withoutdisability (20). Clearly, further studies should be encouragedto evaluate the risk of injury by sex in Paralympic sports. Toaddress this question fully, greater statistical power is re-quired, which may ultimately require the collection and col-lation of data, using common injury reporting methods acrossmultiple nations.
With regard to visual class, T/F11 athletes presented a higherPrevalence of injury, but B2 athletes a higher clinical incidence;this means that a larger percentage of T/F11 athletes was in-jured, but B2 athletes sustained more injuries, but no statisticalsignificance was revealed. In addition, another study with 131visually impaired athletes affirms that the prevalence of injury isgreatest among athletes with the greatest visual impairment(24). This can be related to the fact that postural stability isaffected by vision (2), and proprioception in blind individualstends to be worse than in those with partial vision resulting inabnormal gait and biomechanics, which can lead to injuries(34). These findings suggest that the implementation of pro-prioception training, as a preventive measure, may be useful toreduce the prevalence and clinical incidence of sports injuriesin athletes with visual impairment.
Overuse injuries were most frequently observed in thispopulation. This mechanism of injury is not atypical in sport
FIGURE 2—Distribution of sport injury by body segment in track andfield paralympic competitions.
FIGURE 3—Distribution of sport injury by body part in track and field paralympic competitions.
INJURIES IN VISUALLY IMPAIRED ATHLETES Medicine & Science in Sports & Exercised 911
EPIDEM
IOLO
GY
Copyright © 2013 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.
Sports Injuries in Paralympic Track and FieldAthletes with Visual Impairment
MARILIA PASSOS MAGNO E SILVA1, CIRO WINCKLER2, ANSELMO ATHAYDE COSTA E SILVA1,JAMES BILZON3, and EDISON DUARTE1
1Department for Adapted Physical Education, University of Campinas, BRAZIL; 2Department for Movement Science,Federal University of Sao Paulo, BRAZIL; and 3Department for Health, University of Bath, UNITED KINGDOM
ABSTRACT
MAGNO E SILVA, M. P., C. WINCKLER, A. A. COSTA E SILVA, J. BILZON, and E. DUARTE. Sports Injuries in Paralympic Track
and Field Athletes with Visual Impairment.Med. Sci. Sports Exerc., Vol. 45, No. 5, pp. 908–913, 2013. Purpose: The aims of this study
were to determine the epidemiology, nature, and pattern of sports injuries in Brazilian Paralympic track and field athletes with visual
impairment and to assess differences between visual classes and sex. Methods: Forty visually impaired elite Paralympic athletes par-
ticipated in this study (28 males and 12 females). All athletes competed in International Paralympic competitions between 2004 and
2008. According to the visual classification, 14 athletes were T/F11, 15 were T/F12, and 11 were T/F13. A standardized report form was
used to collect injury data during five competitions. Results: Thirty-one athletes reported 77 sports injuries, with a prevalence of 78%, a
clinical incidence of 1.93 injuries per athlete, and an incidence rate of 0.39 injuries per athlete per competition. Overuse injuries
accounted for 82% and traumatic injuries 18% (P G 0.05). Small variations in the prevalence and clinical incidence of injury between
sexes and visual classes were observed, but these were not statistically different (P 9 0.05). The highest distribution of injury was in
the lower limbs (87%), followed by spine (12%) and upper limbs (1%). The body regions most affected were the thighs (33.8%),
lower legs (16.9%), and knees (9.1%). The most frequent diagnoses were spasms (26%), tendinopathies (23.4%), and strains (13%).
Conclusions: Elite visually impaired track and field Paralympic athletes present a pattern of overuse injuries predominantly affect-
ing the lower limbs, particularly the thighs, lower legs, and knees. These injuries are associated with tendinopathies, muscle spasms,
and strains. There were no apparent differences in injury characteristics between visual classes or sex. Key Words: ATHLETICS,DISABILITY SPORT, INJURY EPIDEMIOLOGY, PARALYMPICS
Athletics was one of only eight sports included in thefirst Paralympic Games, held in Rome, in 1960. Inthis first Paralympiad, only throwing and pentathlon
events were performed. In the modern Paralympic Games,track and field athletics is the sport with the largest numberof participating athletes, competing in eight track events(100, 200, 400, 800, 1500, 5000, and 10,000 m and mara-thon), six field events (long jump, high jump, triple jump,javelin, discus, and shot put), and one combined event(pentathlon). They compete in male and female categoriesand are classified in 1 of the 26 sport classes, according totheir disability type and motor function (motor, physical,visual, and intellectual). Athletes who participate in trackevents use the letter T before the class number to indicate theevent type, whereas those participating in field events use
the letter F (18). This short introduction serves to highlightthe complexity and variety of Paralympic athletic events,which is also reflected in the development and understand-ing of research in the discipline.
To compete, visually impaired athletes must be submittedto a visual classification, where an ophthalmologist evalu-ates acuity and visual field. Athletes can be categorized inone of three levels: B1 are considered blind athletes (fromno light perception in either eye, up to light perception butunable to recognize the shape of a hand at any distance ordirection), B2 are considered to have severely impaired vi-sion (from ability to recognize the shape of a hand, up to avisual acuity of 20/600 or a visual field of less than 5- in thebest eye with the best practical eye correction), and B3 areconsidered to have moderate to poor vision (visual acuityabove 20/600 to 20/200, or a visual field of less than 20-and more than 5- in the best eye with the best correction)(22). In track and field athletics, these classifications aregiven sport-specific nomenclature as follows: T/F11, T/F12,and T/F13, respectively. The Track and Field ParalympicRules determine that acoustic assistance and a guide arepermitted for the classes T/F11 and T/F12. Athletes T/F11should wear opaque glasses to match the capacity of lightperception between the competitors. The T/F13 athletesfollow the same rules as the regular athletics (18).
Address for correspondence: James Bilzon, Ph.D., Department for Health, Uni-versity of Bath, Bath BA2 7AY, United Kingdom; E-mail: [email protected] for publication June 2012.Accepted for publication November 2012.
0195-9131/13/4505-0908/0MEDICINE & SCIENCE IN SPORTS & EXERCISE!Copyright " 2013 by the American College of Sports Medicine
DOI: 10.1249/MSS.0b013e31827f06f3
908
EPIDEM
IOLO
GY
Copyright © 2013 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.
MAGNO E SILVA, M. P., C. WINCKLER, A. A. COSTA E SILVA, J. BILZON, and E. DUARTE. Sports Injuries in Paralympic Track and Field Athletes with Visual Impairment. Med. Sci. Sports Exerc., Vol. 45, No. 5, pp. 908–913, 2013.
Races
The blind athletes (Class T11) should be escorted by the athlete-guide.
The Low Vision athletes (Class T12)
can be escorted by the athlete-guide.
The guide and the Athletes T11 or T12 run side by side, connected by a rope
The guide will provide verbal and tactile information
Lieberman, Butcher & Moak, 2001
Athlete and Guide Connection
Athlete and Guide Connection
Athlete and Guide Connection
Tether Model
• Style
• Technique
• Experience
• Strategy
• Event
Infringiment of the Rule 7.10
Push
Pull
Propel
kind of Tether
+3-4 mts
How much the guide needs to be better than the athlete?
14
PALABRAS CLAVE: Discapacidad visual, Deporte paralímpico, Atletismo, Carreras de velocidad, Cinemática de la carrera
KEY WORDS: Visually impaired, Paralympic Sport, Athletics. Sprint race, Kinematic of the race
Rev.Ib.CC. Act. Fís. Dep. 2014; 3(3): 14-23
LA CARRERA DE VELOCIDAD EN PERSONAS CON
DISCAPACIDAD VISUAL THE SPRINT IN PERSONS WITH VISUALLY IMPAIRED
Miguel Ángel Torralba1, José María Padullés2, Marcelo Braz Vieira3 y Helena Olson4
1Miguel Ángel Torralba. Doctor en Ciencias de la Educación. Profesor titular de la Universidad de Barcelona. [email protected] 2José María Padullés. Doctor por la Universidad de Barcelona. Profesor titular del INEFC-Barcelona. [email protected] 3Marcelo Braz Vieira. Doctorando en Actividad Física, Educación Física y Deporte en la Universidad de Barcelona. [email protected] 4Helena Olson. Licenciada en Ciencias de la Actividad Física. Profesora asociada de la Universidad de Barcelona. [email protected] Código UNESCO: 240604 Biomecánica Clasificación Consejo de Europa: 3 Biomecánica FINANCIACIÓN Este estudio conto con la financiación de la Universidad de Barcelona y el Instituto Nacional de Educación Física de Cataluña (INEFC). Recibido el: 1/9/2014 Aceptado el: 16/12/2014
RESUMEN El presente estudio buscó identificar las diferencias que se observan en las carreras de velocidad realizadas por atletas con discapacidad visual. Para ello se recogieron los datos de 39 atletas ciegos de 24 países que participaron en los 100 metros de los Juegos Paralímpicos en Beijing 2008. Los datos extraídos permiten valorar el tiempo de carrera(s), velocidad media (m/s), número de pasos, frecuencia media (Hz), tiempo medio de paso(s) y amplitud media de paso (m), realizando un estudio comparativo con personas sin discapacidad. Se recogieron las grabaciones del Centro de audiovisuales del Comité Paralímpico en Beijing (DVD), siendo los datos tratados con el paquete estadístico SPSS (21.0). Entre los resultados, destacar la importancia que tienen la longitud de paso y la frecuencia, donde los atletas ciegos muestran un resultado inferior en el primer parámetro, resaltando como muy positivo la casi nula diferencia existente en la reacción de la salida de tacos.
ABSTRACT The present study aimed to identify differences observed in the sprints races performed by visually impaired athletes. Data were collected from 39 blind athletes from 24 countries participated in the 100 meters Paralympic Games in Beijing 2008. The extracted data allow to assess race time (s), average speed (m/s), number of steps, average frequency (Hz), mean of step time (s) and mean of the step amplitude (m), making a comparative study with non-disabled. Recordings of the audio-visual center of Beijing Paralympic Committee (DVD) were collected, and data was processed with SPSS (21.0). Among the results, highlight the importance of stride length and frequency, where the blind athletes show lower results in the first parameter, highlighting a very positive almost no difference in the reaction of output blocks.
La carrera de velocidad en personas con discapacidad visual
Miguel Ángel Torralba et al.
Rev. Ib. CC. Act. Fís. Dep.
18
atleta y el guía por dos calles, lo que convierte la carrera en 4 atletas por “serie”. En el análisis de las series fueron excluidos 2 hombres y 1 mujer ya que no pudimos analizar toda su carrera por no entrar, en algún momento, en el objetivo de la cámara, y en la final femenina, en dos calles no fue posible identificar el tiempo de reacción. Metodología de análisis Se realizó un análisis cinemático de la carrera de 100 m, de los atletas con discapacidad visual, categoría ciegos (T11), con el objeto de valorar las variables de tiempo de reacción (s), tiempo de carrera (s), velocidad media (m/s), número de pasos, frecuencia media (Hz), tiempo medio de paso (s) y amplitud media de paso (m), teniendo en cuenta la categoría y sexo de los participantes. Se extrajo la media de todas las variables y la desviación estándar (DE), así como la mínima
y máxima. Para ello se recogieron las grabaciones del Centro de audiovisuales del Comité Paralímpico en Beijing (DVD). Frame Rate (fr/s): 30. Tiempo frame 0,03333s. Todos los datos recogidos fueron tratados con el paquete estadístico SPSS versión 21.0. RESULTADOS Y DISCUSIÓN En primer lugar hemos recogido los datos de todos participantes en la fase clasificatoria, es decir de todos los atletas de la categoría T11 que han participado en los JJPP, debido a que es una muestra muy representativa del atletismo mundial, ya que participaron 23 países, en la competición más característica del deporte adaptado. En las tablas 2 y 3 se puede verificar los datos medios generales de las series clasificatorias masculinas y femeninas.
Tabla 2. Datos generales de la fase clasificatoria masculina
Marca (s)
Vel. Media (m/s)
T. reac.
(s)
T. carrera
(s)
Nº Pasos
Vel. Media real
(m/s)
Frec. Media (Hz)
T. Medio paso
(s)
Ampl. Media. paso (m)
N 23 23 23 23 23 23 23 23 23 Mínimo 11,19 8,07 0,14 10,96 47,5 8,16 4,08 0,21 1,80 Máximo 12,39 8,94 0,23 12,26 55,5 9,12 4,76 0,25 2,11 Media 11,77 8,50 0,19 11,58 51,2 8,65 4,43 0,23 1,95 DE 0,32 0,23 0,02 0,33 1,7 0,25 0,18 0,01 0,06
La carrera de velocidad en personas con discapacidad visual
Miguel Ángel Torralba et al.
Rev. Ib. CC. Act. Fís. Dep.
19
Tabla 3. Datos generales de la fase clasificatoria femenina
Marca
(s)
Vel. Media (m/s)
T. reac.
(s)
T. carrera
(s)
Nº Pasos
Vel. Media real
(m/s)
Frec. Media (Hz)
T. Medio paso
(s)
Ampl. Media. paso (m)
N 10 10 4 10 8 10 8 8 8 Mínimo 12,41 7,14 0,19 12,17 53,5 7,14 4,26 0,22 1,72 Máximo 14,00 8,06 0,45 14,00 58,3 8,22 4,45 0,24 1,87 Media 13,12 7,63 0,28 13,01 55,8 7,70 4,35 0,23 1,79 DE 0,45 0,26 0,11 0,54 1,5 0,32 0,08 0,00 0,05 En la tabla 4 se indican los datos referentes a las finales A y B de los JJPP de Beijing en la categoría T11 masculina. El resultado de la carrera indica la paridad entre los atletas participantes, donde la diferencia entre las marcas del más rápido al más lento es de 0,69s. Si comparamos la diferencia en las series, vemos que en la Final A (atletas 1 a 4) difieren 0,54s y en la Final B 0,16s. En la final de los Juegos Olímpicos en Beijing, la diferencia entre los ocho finalistas (en una serie única) fue de 0,34s(26) y, más recientemente, en el Campeonato del Mundo (CM) celebrado en Daegu(25) 0,57s. Los atletas finalistas recorren los 100m con 50 y 51 pasos y una frecuencia media de 4,54Hz. A diferencia de los atletas sin discapacidad que, en el CM(25), realizaron entre 41 y 49 pasos con una frecuencia media de 4,67Hz para completar los 100m. Esto motivó que la amplitud media del paso que realizan los atletas con discapacidad visual y sin discapacidad fuese de 1,95m por 2,15m respectivamente, por lo que creemos que el componente de percepción del espacio tiene una gran incidencia en la fase de vuelo del paso. Estos datos están de acuerdo con los encontrados con el
estudio de Ferro(29) en el que indica que la fase de vuelo es más corta en los atletas ciegos que en los atletas sin discapacidad que utilizó de control. La velocidad media en este estudio es tratada apenas como una variable indicativa, pues calcula la fracción del tiempo tardado para ultrapasar la línea de meta después del pistoletazo de salida. Así, la velocidad media del grupo paralímpico finalista de Beijing fue de 8,71m/s, mientras que los atletas finalistas de Daegu(25) lograron 9,84m/s. Otro dato que podemos analizar es el tiempo de reacción en salir de los tacos de salida. Los atletas con discapacidad visual presentan un promedio de reacción al disparo de 0,187s, logrando el más rápido en abandonar el bloque un tiempo de 0,145s y el más lento 0,246s. Por otro lado, los atletas participantes en la final del CM celebrado en Daegu(25) registraron una media de 0,166s, donde los más rápidos salieron en 0,154s y los menos rápidos 0,175s. Vistos los resultados de reacción podemos indicar que la discapacidad visual no tiene una incidencia negativa en la reacción a la salida de los 100 m.
Olympic 41-49 Steeps
RT 0,16
Olympic 47-51 Steeps
RT 0,17
Sprint RaceMaintenance Top Speed
18%
Starting
Block
5%
Acceleratio
n
64%
RT
1%
Lessened Degree of
desaceleration 12%
Tellez, 2008
Hand Position
Foot Position
11/11/12$
3$
Saída&Baixa&Tiro&
Joelho$e$quadril$totalmente$estendidos$
Balanço$rápido$da$perna$posterior$para$a$frente$
O$Empurar$da$perna$posterior$é$mais$potente$que$da$perna$anterior$
Os$Braços$se$elevam$e$começam$a$balancear$
O$Tronco$se$endurece$e$levanta$a$medida$que$os$pés$precionam$o$bloco$
Saída&Baixa&Aceleração&
Tronco$vai$se$endireitando$ao$longo$dos$20Z30$metros$
Frequência$e$amplitude$aumentam$a$cada$passada$
Perna$paralelo$ao$solo$durante$a$recuperação$
Inclinação$do$tronco$adiante$
Pé$dianteiro$se$apoio$sobre$o$metatarso$
Posicionamento& Saída&de&Bloco&
Sincronicidade& Sincronicidade&
Orientation
Reaction Time
1 2
Guide 0,209 0,283
Ahlete 0,146 0,222
Anthropometric
Anthropometric Differences
11/11/12$
3$
Saída&Baixa&Tiro&
Joelho$e$quadril$totalmente$estendidos$
Balanço$rápido$da$perna$posterior$para$a$frente$
O$Empurar$da$perna$posterior$é$mais$potente$que$da$perna$anterior$
Os$Braços$se$elevam$e$começam$a$balancear$
O$Tronco$se$endurece$e$levanta$a$medida$que$os$pés$precionam$o$bloco$
Saída&Baixa&Aceleração&
Tronco$vai$se$endireitando$ao$longo$dos$20Z30$metros$
Frequência$e$amplitude$aumentam$a$cada$passada$
Perna$paralelo$ao$solo$durante$a$recuperação$
Inclinação$do$tronco$adiante$
Pé$dianteiro$se$apoio$sobre$o$metatarso$
Posicionamento& Saída&de&Bloco&
Sincronicidade& Sincronicidade&
In review: POWER AND SPEED DIFFERENCES BETWEEN BRAZILIAN
PARALYMPIC SPRINTERS WITH VISUAL IMPAIRMENT AND GUIDES: A
PILOT STUDY
Figure 1. Comparisons of the velocities in 10 m between
AVI and guide athletes.
ES = 2.1 (Large), P < 0.05.
Figure 2. Comparisons of the velocities in 50 m between AVI and guide athletes.
ES = 1.7 (Large), P < 0.05.
Panel A individual comparisons. Panel B means of the groups and the
magnitude of the difference (%), between parentheses are presented the 95% confidence interval of difference
Isokinetics and Speed
192,2
98,9
251,3*
130,0*142,7
90,4
181,6*
118,0*119,191,2
148,5*112,6*
RExtensor RFlexor RExtensor RFlexor
ATHLETES GUIDES
PeakTorque60°/s 180°/s 300°/s
6,097,99 8,54
6,398,93* 9,69*
02468
1012
10m 30m 50m
Speed
Distance
SPEEDVI G
AthleteswithVisualImpairment
R.Extensor60°/s
R.Extensor180°/s
R.Extensor300°/s
0-10m 0,423 0,386 0,374
10-30m 0,786* 0,752* 0,721*
30-50m 0,792* 0,776* 0,731*
BARROS, R.A. ; Winckler, C. ; LOTURCO, I. . Analysis of Relationship between Strength and Speed in Athletes with Visual Impairment and Guides Participants of Athletics Brazil Paralympic Team. In:
VISTA 2013 'Equipment and Technology in Paralympic Sports', 2013, Bonn. VISTA2013 Scientific Conference Booklet. Bonn, 2013. v. 1. p. 81-83.
The stride length and arm swing of blind athletes and their guides change in the side connected
Torralba et al, 2007
SILVA, M. P. M. E. ; BARROS, R.A. ; Winckler, C. ; Miranda, A.J. . Evaluation of Muscle Imbalances and the Relationship with Sport Injuries in Athletes with Visual Impairment and their Guides. In: VISTA 2013 'Equipment and Technology in Paralympic Sports', 2013, Bonn. VISTA2013 Scientific Conference Booklet. Bonn, 2013. v. 1. p. 99-101.
ORIGINAL RESEARCHpublished: 06 November 2015
doi: 10.3389/fphys.2015.00323
Frontiers in Physiology | www.frontiersin.org 1 November 2015 | Volume 6 | Article 323
Edited by:
Thomas Janssen,
VU University Amsterdam,
Netherlands
Reviewed by:
Naoto Fujii,
University of Ottawa, Canada
Alvaro N. Gurovich,
Indiana State University, USA
*Correspondence:
Irineu Loturco
Specialty section:
This article was submitted to
Exercise Physiology,
a section of the journal
Frontiers in Physiology
Received: 28 August 2015
Accepted: 26 October 2015
Published: 06 November 2015
Citation:
Loturco I, Winckler C, Kobal R, Cal
Abad CC, Kitamura K, Veríssimo AW,
Pereira LA and Nakamura FY (2015)
Performance changes and relationship
between vertical jump measures and
actual sprint performance in elite
sprinters with visual impairment
throughout a Parapan American
games training season.
Front. Physiol. 6:323.
doi: 10.3389/fphys.2015.00323
Performance changes andrelationship between vertical jumpmeasures and actual sprintperformance in elite sprinters withvisual impairment throughout aParapan American games trainingseasonIrineu Loturco 1*, Ciro Winckler 2, Ronaldo Kobal 1, Cesar C. Cal Abad1, Katia Kitamura 1,Amaury W. Veríssimo2, Lucas A. Pereira 1 and Fábio Y. Nakamura 1, 3
1 Nucleus of High Performance in Sport, São Paulo, Brazil, 2 Brazilian Paralympic Committee, Brasília, Brazil, 3 Department of
Physical Education, State University of Londrina, Londrina, Brazil
The aims of this study were to estimate the magnitude of variability and progression in
actual competitive and field vertical jump test performances in elite Paralympic sprinters
with visual impairment in the year leading up to the 2015 Parapan American Games,
and to investigate the relationships between loaded and unloaded vertical jumping
test results and actual competitive sprinting performance. Fifteen Brazilian Paralympic
sprinters with visual impairment attended seven official competitions (four national, two
international and the Parapan American Games 2015) between April 2014 and August
2015, in the 100- and 200-m dash. In addition, they were tested in five different periods
using loaded (mean propulsive power [MPP] in jump squat [JS] exercise) and unloaded
(squat jump [SJ] height) vertical jumps within the 3 weeks immediately prior to the main
competitions. The smallest important effect on performances was calculated as half
of the within-athlete race-to-race (or test-to-test) variability and a multiple regression
analysis was performed to predict the 100- and 200-m dash performances using the
vertical jump test results. Competitive performance was enhanced during the Parapan
American Games in comparison to the previous competition averages, overcoming the
smallest worthwhile enhancement in both the 100- (0.9%) and 200-m dash (1.43%). In
addition, The SJ and JS explained 66% of the performance variance in the competitive
results. This study showed that vertical jump tests, in loaded and unloaded conditions,
could be good predictors of the athletes’ sprinting performance, and that during the
Parapan American Games the Brazilian team reached its peak competitive performance.
Keywords: Paralympics, track and field, muscle power, physical disability, blind athletes
9 Moss, B. M., Refsnes, P. E., Abildgaard, A., Nicolaysen, K., Jensen, J. (1997). Effects of maximal 413 effort strength training with different loads on dynamic strength, cross-sectional area, load-power 414 and load-velocity relationships. Eur J Appl Physiol Occup Physiol. 75, 193-9. 415 Nilsson, J., Thorstensson, A. (1989). Ground reaction forces at different speeds of human walking 416 and running. Acta Physiol Scand. 136, 217-27. 417 Pyne, D., Trewin, C., Hopkins, W. (2004). Progression and variability of competitive performance 418 of Olympic swimmers. J Sports Sci. 22, 613-20. 419 Sanchez-Medina, L., Perez, C. E., Gonzalez-Badillo, J. J. (2010). Importance of the propulsive 420 phase in strength assessment. Int J Sports Med. 31, 123-9. 421 Sleivert, G., Taingahue, M. (2004). The relationship between maximal jump-squat power and sprint 422 acceleration in athletes. Eur J Appl Physiol. 91, 46-52. 423 Stone, M. H., O'Bryant, H. S., McCoy, L., Coglianese, R., Lehmkuhl, M., Schilling, B. (2003). 424 Power and maximum strength relationships during performance of dynamic and static weighted 425 jumps. J Strength Cond Res. 17, 140-7. 426 Wisloff, U., Castagna, C., Helgerud, J., Jones, R., Hoff, J. (2004). Strong correlation of maximal 427 squat strength with sprint performance and vertical jump height in elite soccer players. Br J Sports 428 Med. 38, 285-8. 429 Young, W., Benton, D., Pryor, J. M. (2001). Resistance training for short sprints and maximum-430 speed sprints. Strength Cond J. 23, 7. 431 432 FIGURES AND TABLE LEGENDS 433 434 Figure 1. Variation in 100- (Panel A) and 200-m (Panel B) dash performances across seven official 435 competitions. The black line represent the mean individual performances, and the gray area 436 represent the smallest important effect on performances (i.e., calculated as half of the within-athlete 437 race-to-race variability). National corresponds to competitions organized by the local Paralympic 438 Committee; IPC corresponds to international competitions organized by the International 439 Paralympic Committee; ParaPan corresponds to the ParaPan American Games. 440 441 Figure 2. Variation in squat jump (SJ) (Panel A) and relative mean propulsive power in jump squat 442 exercise (MPP REL JS) (Panel B) test results across the five periods. The black line represents the 443 mean individual performances, and the gray area represents the smallest important effect on 444 performances (i.e., calculated as half of the within-athlete test-to-test variability). 445 446 Figure 3. Linear regression between 100-m (panels A and C) and 200-m (panels B and D) dash 447 performances and the squat jump (SJ) height and relative mean propulsive power (MPP REL) in 448 the jump squat (JS) exercise. 449 450 Table 1. Predictions of 100- and 200-m dash performances using multiple regression analysis. 451 452 453 TABLE 1 454 455 Table 1. Predictions of 100- and 200-m dash performances using multiple regression analysis. 456 457
R2 Equation 100-m 0.66* y = 15.558 - (0.063 x SJ) - (0.061 x JS) 200-m 0.66* y = 32.918 - (0.167 x SJ) - (0.098 x JS)
458 Note: SJ = squat jump; JS = jump squat; P < 0.01. 459
In review
Loturco et al. Performance of Paralympic sprinters
FIGURE 3 | Linear regression between 100 (A,C) and 200-m (B,D) dash performances and the squat jump (SJ) height and relative mean propulsive
power (MPP REL) in the jump squat (JS) exercise; *P < 0.01.
regression models have increased only (on average) ∼1.2% ofthe explained variance between dependent (actual sprint times)and independent variables (SJ and JS), we considered relevantto carry out this calculation, since slight differences betweenindividuals in 100- and 200-m dash events might significantlyaffect their competitive results. Observing the data reported here,from this point on, Paralympic coaches can better estimate theactual performance of their top-level athletes in official sprintcompetitions. Furthermore, by understanding the importanceof this specific “mechanical combination” (i.e., SJ and JS) insprinting performance, they will be able to develop more effectiveand specific training programs.
Concerning the within-subject variability, the smallestworthwhile enhancements in the 100- (0.9%) and 200-m dash(1.43%) were comparable to those reported in Olympic andParalympic swimmers (Pyne et al., 2004). However, these valueswere higher than the estimates provided by elite track athleteswithout disabilities (Hopkins, 2005). The greater variabilityin athletes with visual impairment’s performances may beassociated with their disabilities (Fulton et al., 2009) and thepossible influence of their respective guides on the individuals’sprinting mechanics (unpublished data). Importantly, thesmallest worthwhile enhancement provides the coach with anidea of the meaningfulness of a given change in an athlete’sperformance. In general, an enhancement needs to be higherthan the smallest worthwhile enhancement to affect the results
TABLE 2 | Predictions of 100- and 200-m dash performances using
multiple regression analysis.
R2 Equation
100-m 0.66* y = 15.558 – (0.063 × SJ) – (0.061 × JS)
200-m 0.66* y = 32.918 – (0.167 × SJ) – (0.098 × JS)
SJ, squat jump; JS, jump squat; *P < 0.01.
(i.e., medal prospects; Fulton et al., 2009). Curiously, in the100-m dash, the athletes presented worse sprinting times thantheir mean times during the period of observation, but duringthe Parapan American Games they achieved their “performancepeak.” Although in the 200-m the times were close to the meanperformance throughout the observation, during the ParapanAmerican Games, they reached a meaningful performancechange (in comparison to the previous analyzed competitions).To some extent, this explains the outstanding results obtained bythe Brazilian team during the 2015 Pan American Games (threegold, six silver, and two bronze medals in the 100- and 200-mraces).
The jumping test results were substantially more variable thanthe actual competitive performances in the 100- and 200-m dash(CV of SJ = 5.58% and JS = 7.97%), which implies the needfor larger improvements in jumping tests, in order to considerthese enhancements as meaningful. The general dynamics of
Frontiers in Physiology | www.frontiersin.org 6 November 2015 | Volume 6 | Article 323
Practical Impact
• Athletes with similar anthropometric
• Modification of the side of the race
• Training Rotine for the guide and for the athlete
Guide's Support
The influence of collective behaviour on pacing in
endurance competitions
Andrew Renfree1*, Everton Crivoi do Carmo2, Louise Martin1, Derek M. Peters1, 3
1Institute of Sport and Exercise Science, University of Worcester, United Kingdom,2Department of Physical Education, Senac University Centre, Brazil, 3Faculty of Healthand Sport Sciences, University of Agder, Norway
Submitted to Journal:
Frontiers in Physiology
Specialty Section:
Exercise Physiology
ISSN:
1664-042X
Article type:
Perspective Article
Received on:
19 Oct 2015
Accepted on:
23 Nov 2015
Provisional PDF published on:
23 Nov 2015
Frontiers website link:
www.frontiersin.org
Citation:
Renfree A, Crivoi_do_carmo E, Martin L and Peters DM(2015) The influence of collective behaviour onpacing in endurance competitions. Front. Physiol. 6:373. doi:10.3389/fphys.2015.00373
Copyright statement:
© 2015 Renfree, Crivoi_do_carmo, Martin and Peters. This is an open-access article distributedunder the terms of the Creative Commons Attribution License (CC BY). The use, distribution andreproduction in other forums is permitted, provided the original author(s) or licensor are creditedand that the original publication in this journal is cited, in accordance with accepted academicpractice. No use, distribution or reproduction is permitted which does not comply with these terms.
This Provisional PDF corresponds to the article as it appeared upon acceptance, after peer-review. Fully formatted PDFand full text (HTML) versions will be made available soon.
Frontiers in Physiology | www.frontiersin.org
Provisional
The influence of collective behaviour on pacing in endurance 1
competitions 2
Andrew Renfree1*, Everton Crivoi do Carmo2, Louise Martin1, Derek M Peters1&3 3
1 Institute of Sport & Exercise Science, University of Worcester, United Kingdom 4
2 Department of Physical education, Senac University Centre, Brazil 5
3 Faculty of Health & Sport Sciences, University of Agder, Kristiansand, Norway 6 7 Correspondence: Andrew Renfree, Institute of Sport & Exercise Science, University of 8 Worcester, Henwick Grove, Worcester, United Kingdom WR2 6AJ. 9 10 [email protected] 11 12 Keywords: decision-making, endurance performance, complex systems, sport 13 14
Abstract 15
A number of theoretical models have been proposed in recent years to explain pacing 16 strategies observed in individual competitive endurance events. These have typically related 17 to the internal regulatory processes that inform the making of decisions relating to muscular 18 work rate. Despite a substantial body of research which has investigated the influence of 19 collective group dynamics on individual behaviours in various animal species, this issue has 20 not been comprehensively studied in individual athletic events. This is somewhat surprising 21 given that athletes often directly compete in close proximity to one another, and that 22 collective behaviour has also been observed in other human environments including 23 pedestrian interactions and financial market trading. Whilst the reasons for adopting 24 collective behaviour are not fully understood, collective behaviour is thought to result from 25 individual agents following simple local rules that result in seemingly complex large systems 26 that act to confer some biological advantage to the collective as a whole. Although such 27 collective behaviours may generally be beneficial, competitive endurance events are 28 complicated by the fact that increasing levels of physiological disruption as activity 29 progresses may compromise the ability of some individuals to continue to interact with other 30 group members. This could result in early fatigue and relative underperformance due to 31 suboptimal utilisation of physiological resources by some athletes. Alternatively, engagement 32 with a collective behaviour may benefit all due to a reduction in the complexity of decisions 33 to be made and a subsequent reduction in cognitive loading and mental fatigue. This paper 34 seeks evidence for collective behaviour in previously published analyses of pacing behaviour 35 and proposes mechanisms through which it could potentially be either beneficial, or 36 detrimental to individual performance. It concludes with suggestions for future research to 37 enhance understanding of this phenomenon. 38
39
40
41
42
Provisional
The influence of collective behaviour on pacing in endurance 1
competitions 2
Andrew Renfree1*, Everton Crivoi do Carmo2, Louise Martin1, Derek M Peters1&3 3
1 Institute of Sport & Exercise Science, University of Worcester, United Kingdom 4
2 Department of Physical education, Senac University Centre, Brazil 5
3 Faculty of Health & Sport Sciences, University of Agder, Kristiansand, Norway 6 7 Correspondence: Andrew Renfree, Institute of Sport & Exercise Science, University of 8 Worcester, Henwick Grove, Worcester, United Kingdom WR2 6AJ. 9 10 [email protected] 11 12 Keywords: decision-making, endurance performance, complex systems, sport 13 14
Abstract 15
A number of theoretical models have been proposed in recent years to explain pacing 16 strategies observed in individual competitive endurance events. These have typically related 17 to the internal regulatory processes that inform the making of decisions relating to muscular 18 work rate. Despite a substantial body of research which has investigated the influence of 19 collective group dynamics on individual behaviours in various animal species, this issue has 20 not been comprehensively studied in individual athletic events. This is somewhat surprising 21 given that athletes often directly compete in close proximity to one another, and that 22 collective behaviour has also been observed in other human environments including 23 pedestrian interactions and financial market trading. Whilst the reasons for adopting 24 collective behaviour are not fully understood, collective behaviour is thought to result from 25 individual agents following simple local rules that result in seemingly complex large systems 26 that act to confer some biological advantage to the collective as a whole. Although such 27 collective behaviours may generally be beneficial, competitive endurance events are 28 complicated by the fact that increasing levels of physiological disruption as activity 29 progresses may compromise the ability of some individuals to continue to interact with other 30 group members. This could result in early fatigue and relative underperformance due to 31 suboptimal utilisation of physiological resources by some athletes. Alternatively, engagement 32 with a collective behaviour may benefit all due to a reduction in the complexity of decisions 33 to be made and a subsequent reduction in cognitive loading and mental fatigue. This paper 34 seeks evidence for collective behaviour in previously published analyses of pacing behaviour 35 and proposes mechanisms through which it could potentially be either beneficial, or 36 detrimental to individual performance. It concludes with suggestions for future research to 37 enhance understanding of this phenomenon. 38
39
40
41
42
Provisional
Tether for the long Distance
Running Economy
Association of the athlete and guide
performance
Running Economy
Evaluation on the Track
VI SD Guide SD p
HR max 169,78 10,80 169,69 13,10 0,60
VO2 max mL/kg/min
42,31 7,56 43,30 4,22 0,91
VO2 max L/min 2,85 0,64 3,33 0,37 0,02
Running Economy Running economy is typically defined as the energy demanded for a given velocity of submaximal running, and is determined by measuring the steady-state consumption of oxygen (VO2)
Saunders, et al 2004
The results show RE is higher than those found by long distance athletes using similar speed (Guglielmo, Coelho, & Sergio, 2005, Saunders et al., 2004) and those found using the higher speeds used in this study (Guglielmo , Greco, & Denadai, 2009; Nummela, Keränen, & Mikkelsson, 2007).
Impact in RE•A d j u s t m e n t s o f stride length
• Guide needs to p a s s v e r b a l information
•Increased demand of attention to race with the blind on treadmill
Guide's Demand
The higher O2 consumption of the guides indicates the need of more attention to training with these athletes as there is higher energy expenditure during the training and competition when performing guidance of the blind athlete.
What about Shorter Events?
Jump Events
RulesOrientation - Caller (11- 2/ 12 - 1)
Real Jump - 11 and 12
3.5m
Linha de Medição
1m.
Talco
Talco
Jump Area
Number of Steps
Men Female Men Female
F11/36/37/38/42/45/46
F11/36/37/38/42/45/46
F12/13/20/44/47 F12/13/20/44/47
Long Jump 10-16 8-16 12-20 10-16
Triple 6-16 4-12 8-16 6-14
High Jump 2-8 2-6 4-10 2-8
• Spacial Orientation
• Running
• Intermediary Jump
• Learning Process
• Motor Strategy
VOLUME 8 | Proc3 | 2013 | S671
Performance Analysis Workshop, 2 - 5 April 2013, Alicante, Spain
Biomechanical analysis of the final strides of the approach and the take-off by visually impaired class F12 and F13 long jumpers VASSILIOS PANOUTSAKOPOULOS1, APOSTOLOS THEODOROU1 , MARIANA C. KOTZAMANIDOU3, EMMANOUIL SKORDILIS2, IRAKLIS A. KOLLIAS1
1 Biomechanics Laboratory, Department of Physical Education & Sports Science, Aristotle University of Thessaloniki, Thessaloniki, Greece
2 Department of Physical Education & Sports Science, Kapodistrian University of Athens, Athens, Greece
3 Faculty of Health and Human Sciences, Akmi Metropolitan College Thessaloniki, Thessaloniki, Greece
ABSTRACT
Panoutsakopoulos V, Theodorou A, Kotzamanidou MC, Skordilis E, Kollias IA. Biomechanical analysis of the final strides of the approach and the take-off by visually impaired class F12 and F13 long jumpers. J. Hum. Sport Exerc. Vol. 8, No. Proc3, pp. S671-S680, 2013. Despite of the level of visual aquity, European Records in long jumping are greater in class F12 (visual acuity 2/60) than class F13 (visual acuity 6/60) both in males and females. The aim of the present study was to compare the biomechanical parameters of the final strides of the approach and the take-off in class F12 and F13 long jumpers. 19 class F12 (males: 13, females: 6) and 12 class F13 (males: 4, females: 8) long jumpers participating in the 2009 International Blind Sports Association European Championships were recorded using a stationary digital video camera (sampling frequency: 300 fps). Key biomechanical parameters were extracted with a typical 2D-DLT kinematical analysis. Differences between groups were investigated using Independent samples t-test. Results indicated that the official distance was 6.07 m ± 0.55 and 5.52 m ± 0.91 for F12 and F13 respectively (p<.05). Significant differences were also observed concerning the vertical take-off velocity (F12: 2.8 m/sec, F13: 2.4 m/sec), the support leg's knee flexion (F12: 18.2 deg, F13: 25.2 deg) and the knee joint flexion velocity (F12: 7.4 rad/sec, F13: 10.2 rad/sec) at the take-off board and the knee maximum flexion angle at the last stride (F12: 116.8 deg, F13: 125.4 deg). In conclusion, F12 performed better than F13 because of the more advantageus utilization of the factors defining the vertical component in the long-jump take-off. Additionally, the different last stride maximum knee flexion angle might imply differences concerning the mechanics of the placement of the take-off leg. It is possible that factors such as the size and surface properties of the 1.22 m x 1.00 m chalked take-off area used in F12 competition may contribute to the differences observed in the study. Key words: 2D-DLT ANALYSIS, STRIDE LENGTH, JOINT ANGULAR KINEMATICS, VISUAL ACUITY, TECHNIQUE
2 Corresponding author. Department of Physical Education and Sport Science. Kapodistrian University of Athens 41 Ethnikis E-mail: [email protected] Performance Analysis Workshop, 2 - 5 April 2013, Alicante, Spain JOURNAL OF HUMAN SPORT & EXERCISE ISSN 1988-5202 © Faculty of Education. University of Alicante doi:10.4100/jhse.2013.8.Proc3.13
Proceeding Panoutsakopoulos et al. / Visually impaired long jump JOURNAL OF HUMAN SPORT & EXERCISE
VOLUME8 | Proc3 | 2013 | S675
Table 1. Comparison of the biomechanical parameters of the approach between the examined class F12 and F13 long jumpers (see text for the abbreviations used)
parameter F12 F13 t p S3L (m) 1.95 ± 0.16 1.89 ± 0.15 1.015 .318 S2L (m) 2.12 ± 0.22 2.00 ± 0.17 1.688 .102 S1L (m) 1.88 ± 0.09 1.82 ± 0.21 0.892 .388 SF3L (Hz) 4.72 ± 0.34 4.81 ± 0.49 0.635 .531 SF2L (Hz) 4.18 ± 0.44 4.07 ± 0.41 0.727 .474 SF1L (Hz) 4.23 ± 0.30 4.17 ± 0.31 0.601 .553 Vx3L (m/sec) 8.45 ± 0.50 8.15 ± 0.62 1.268 .215 Vx2L (m/sec) 8.82 ± 0.60 8.37 ± 0.90 1.695 .101 Vx1L (m/sec) 8.41 ± 0.49 8.06 ± 0.70 1.677 .104 VxMAX (m/sec) 8.96 ± 0.61 8.49 ± 0.79 1.883 .070
At the examined part of the jump, F12 and F13 athletes were not significantly different (p > .05) concerning the alterations of HBCM at the instances examined (Figure 1). An average HBCM lowering of 0.05 m ± 0.02 was recorded during the flight phase of 2L. In general, the knee angular kinematics were not different between groups. However, a detailed look at the support phase of 1L revealed a significant difference (t1,29 = 2.577, p < .05) concerning θkMF (116.8 deg ± 9.0 and 125.4 deg ± 9.1 for F12 and F13, respectively) but not for θkTD or θkTO (Figure 2). VATD was not different between groups and it progressively increased during the last two landings of the foot and the final touchdown for the take-off.
Figure 1. Height alteration (ΔH) of the Body Center of Mass between touchdowns (td) and take-offs (to) for the penultimate stride (2L), last stride (1L) and contact on the take-off board (BO). The lines linking the data
points are not intended to represent the actual BCM trajectory
Panoutsakopoulos et al. / Visually impaired long jump JOURNAL OF HUMAN SPORT & EXERCISE
S676 | 2013 | Proc3 | VOLUME 8 © 2013 University of Alicante
Figure 2. Mean ensemble curves for the support leg’s knee angle (ϑk) during the support phase of the last
stride. Time is normalized for the comparison. The asterisk indicated statistical significant difference (p < .05) for the joint angle at its maximum flexion
Table 2 presents the parameters of the take-off phase. F12 had an almost three fold STΤB. With the exception of VyTO, θkFLEX, and ωkFLEX, no statistical significant differences were noted.
Table 2. Comparison of the biomechanical parameters of the take-off phase between the examined class
F12 and F13 long jumpers (see text for the abbreviations used). parameter F12 F13 t p STTB (m) 0.28 ± 0.19 0.10 ± 0.09 3.665 .001** STD (m) -0.60 ± 0.1 -0.62 ± 0.06 0.908 .371 UATD (m/sec) 2.68 ± 0.59 2.68 ± 0.95 0.011 .991 VxTD (m/sec) 8.20 ± 0.51 7.85 ± 0.71 1.604 .120 VxTO (m/sec) 6.90 ± 0.53 6.54 ± 0.68 1.649 .110 ΔVxBO (m/sec) -1.30 ± 0.46 -1.31 ± 0.44 0.031 .976 VyTD (m/sec) -0.05 ± 0.23 -0.20 ± 0.26 1.734 .094 VyTO (m/sec) 2.81 ± 0.42 2.41 ± 0.46 2.532 .017* ΔVyBO (m/sec) 2.86 ± 0.42 2.61 ± 0.46 1.568 .128 STO (m) 0.35 ± 0.06 0.35 ± 0.06 0.227 .822 AngPr (°) 21.7 ± 2.8 19.9 ± 3.4 1.584 .124 ϑkTD (deg) 158.5 ± 5.5 162.5 ± 7.5 1.733 .094 ϑkFLEX (deg) -18.2 ± 5.4 -25.2 ± 5.9 3.373 .002** ϑkTO (deg) 173.2 ± 3.6 170.8 ± 7.5 1.056 .308 ϕTH (deg) -2.4 ± 7.7 -2.4 ± 8.5 0.812 .423 ϕTRSTD (deg) 93.1 ± 5.6 93.5 ± 4.7 0.205 .839 ϕTRSTO (deg) 90.5 ± 7.3 92.7 ± 6.5 0.851 .402 ωkFLEX (rad/sec) -7.4 ± 1.6 -10.2 ± 3.6 2.984 .006** ωkEXT (rad/sec) 9.9 ± 1.7 9.7 ± 1.3 0.362 .720 WBR (J/kg) -6.2 ± 3 -5.8 ± 3.1 0.731 .688 WPR (J/kg) 2.3 ± 4.2 1.1 ± 3.2 0.547 .352
*: p < .05 / **: p < .01
Throwing Events
• Spacial Orientation
• Running
• Rotation
• Learning Process
• Motor Strategy
• Balance
Low Vision can create a inaccuracies
perceptions with impact in adjusted of speed
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