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Coaching The Rowing Technique Physical Education Essay


Successful competitive rowing requires cardiovascular fitness, anaerobic power, and proper technique to move the boat as rapidly as possible over the course of a race. (Kleshnev 1999). Providing feedback to performers on the quality of their performance and ways they can improve it is a fundamental pedagogical mechanism. This project sought to answer the following questions (1) to what extent can Inertial sensors like SHIMMER be used in a sporting context. (2) Can the kinematic data provided be used as real-time feedback to rowers (3) Is the accelerometer data provided a viable form of visual feedback for rowers. 18 University of Limerick students, with less than 6 months rowing experience participated in a 2 week intervention, with 3 rowing sessions per week on a RowPerfect ergometer. Bland-Altman Analysis was used to assess the levels of agreement of each stroke to that of the "Ideal Stroke". These results were then averaged for each subject and a T-test was performed, p>.05 therefore no significant differences were found for either the experimental, control group or for any individual subjects. As a result the accelerometer data provided by the device, when used without additional on-screen graphical feedback, does not aid rowers in altering their rowing technique. Shimmer does however provide an excellent alternative to video analysis and could possibly be performed during competition or during field based training sessions. Future work should look into validating the data compared to different means of Laboratory and field rowing analysis.

The learning of any motor skill requires some form feedback, which, in together with practice, is one of the most important elements of motor learning (Newell, 1976).

Success in the sport of rowing requires a powerful biological system and an appropriately designed mechanical system that effectively uses a rower's power while minimising drag forces acting on the shell and the rower. (Baudouin2002)" performing at an elite level of rowing requires fitness and strength combined with high levels of skill and coordination" (Mackenzie 2008) Successful competitive rowing requires cardiovascular fitness, anaerobic power, and proper technique to move the boat as rapidly as possible over the course of a race. (Kleshnev 1999)

To determine an ideal rowing technique it is essential to firstly understand the movement patterns of the stroke cycle and the underlying forces. (Soper 2004) (Hart 2006) In summary, the rowing stroke is a continuous, fluid movement in which the handle is perpetually in motion.

The Stroke begins from the catch position, with shins vertical, torso angeled forward from the hip to create subtle forward spinal flexion, arms fully extended with fingers curved around the handle, abdominal muscles engaged and the navel pulling back away from the thighs, and the shoulders relaxed down with, slight scapular retraction

Begin the drive with the legs, giving a quick powerful push off the catch while maintaining the forward body angle for the first half of the drive. Continue pushing with the legs while opening the body angle with the strength and explosiveness of the legs and core body strength, resulting in suspension.

As the legs reach extension, finish the stroke with a powerful arm pull accelerating the handle as you pull it away from the flywheel and back to the upper abdomen. At the end of the drive your legs will be straight with a bit of plantar flexion at the ankle .

Return to the catch by extending the arms and allowing the handle to pull the body into forward flexion. Flex forward at the hips, aligning the chest over the thighs, and then slide the seat up toward the feet with slow control. Overall the recovery phase should take about twice as long as the drive phase. (Hart 2006)

An efficient rowing stroke ensures that the maximum amount of energy expended by the rower contributes to the speed of the boat. Good rowing technique is not only vital for performance, but also helps prevent injury by removing the stresses which may be placed on the body when poor rowing techniques are utilized. (King et al. 2009) This combination of actions, once optimized, must be repeated as accurately as possible for more than 200 strokes during the competition. "Competent rowing, then, requires good stroke-to-stroke consistency" (Smith 2002)

Efficient rowing will result in the highest boat speed for a given power output. Thus the crew members will view the boat as running well, independently of the class

of the boat. According to (Williams 1967), poor synchronization of movement patterns among a crew will adversely affect the coordination of movement of crew members and cause additional movement of the boat, including yawing, rolling and pitching. These adverse effects include a reduced power output and a waste of effort because of increased friction.

"Coordination and synchrony between rowers in a multiple rower shell affects overall system velocity" (Hill et al. 2002) .For a rowing crew to be successful, the movements of the rowers need to be well coordinated. Because rowers show individual force patterns, they need to adapt their movements when rowing as a crew.

(Mackenzie, 2008) Some would consider that these high forces and their repetitive nature create excessive motion in the spine as a result of the changes in the viscoelastic tissues (Cholewicki and McGill, 1996). Other factors that may be associated with injuries include muscle strength, endurance and fatigue (McGregor et al., 2004), and poor technique (Holt et al, 2003).

1.1 Aims of study

From this information it is clear that rowing could certainly benefit from some sort of tool in order to

Improve technique in individual rowers, thereby improving performance and preventing injury.

To improve synchronization within a crew of rowers.

Traditionally, the measurement of elite athlete performance is commonly done in a laboratory environment where detailed testing of physiology can take place. Laboratory testing however, places limits on an athlete's performance as the competition environment is sufficiently different to the training environment. Shimmer (Intel Corporation. 2006.) is a small wireless sensor platform that can record and transmit physiological and kinematic data in real time. As a result it can be used in a field environment and provides immediate feedback, allowing rowers to alter their technique if needed. This study seeks to investigate.

To what extent can inertial sensors like Shimmer be used in a sporting context

Can Shimmer provide real-time feedback to rowers on a rowing ergometer

Can this feedback be used to alter a rower's stroke pattern

The following Literature Review addresses the effects of feedback on rowing technique in addition to the use of inertial sensors in a sporting context. Shimmer technology and its previous uses will also be discussed as will other methods of instrumentation and technology.


Two main methods were undertaken to conduct the literature search for the compilation of this review. Literature relevant to the subject area was gathered from various academic disciplines including sports science, biomechanics, motor learning, and. Firstly, an extensive search of the University of Limerick library catalogue (books and journal articles) was performed. The key words of "Inertial Sensors", "Inertial Sensors and Rowing", "Rowing Coordination", "Feedback in Rowing", "Real-Time Feedback", "Shimmer Sensors", "Feedback and Coordination", and "Real-Time Feedback and Rowing" were used for electronic searches within the University of Limerick catalogues. Secondly, the reference lists of all located articles were searched.

2.1 Good Technique

The goal in rowing is to make the unit cover the required distance as fast as possible from the start to the finish. Physical performance is necessary to achieve this basic goal and the muscles of the human body produce the necessary energy. As every experienced rower and coach knows, rowing in a crew is much more efficient when the coordination between crew members is high. (Atkinson, 1896).

To determine an ideal rowing technique it is essential to understand the movement patterns of the stroke cycle and underlying forces. Kinematics represents the overall movement pattern of the sculling motion, which is the result of internal and external forces acting on a rower boat system. The overall movement shape is what the coach views and therefore manipulates to produce a more powerful and efficient stroke cycle.

2.2 Injuries

In rowing, the leg muscles play an important role in the force generation during the drive phase by stretching the legs against the foot stretcher. As considered by several authors, the hip and knee extensors are identified as the most important muscles for propulsion. Many lower body injuries in rowing can be attributed to poor technique As rowing is a non-weight-bearing activity rowers' knees in general do not sustain traumatic ligament or meniscal damage, but rowers may experience bouts of patellofemoral pain, which can develop in two ways. For example at the catch, a significant load is placed on the fully flexed knee, which may lead to patellofemoral complaints. Over compression at the catch can further strain the surrounding ligaments. Also at the finish of the stroke, there is a tendency for the knees to buckle slightly or pop up early. They should be held firmly in extension while the blade is being released in order to align the patella properly.

Iliotibial Band Friction Syndrome is another rowing injury associated with poor lower body coordination, as the iliotibial tract slides over the lateral condylar prominence of the knee, inflammation and pain can be caused from friction, leading to this common complaint. Full knee compression at the catch, coupled with varus knee alignment, may also contribute to lateral knee pain in rowers. (Rumball 2005)

2.3 Feedback

Providing feedback to performers on the quality of their performance and ways they can improve it is a fundamental pedagogical mechanism. The effective communication of correct technical information is the culmination of a good coach's assessment of their athlete and would help them to improve. Athletes often do not realise they are moving incorrectly which can lead to engraining faults into the technique and may cause injuries.

Technology that assists rowing coaching by providing automated reporting of an athlete's technical ability in real-time can provide timely, constant, and objective supplementary support in the absence of busy coaches.

The work of (Iskandar 2009) suggests a set of concepts when providing feedback to athletes in order for them to have a rounded learning experience: feedback should both refer to the overall competence of the performer and instruct them how to improve through allowing verification of their movements, evaluating their progress and determining the causes of errors. They also note that feedback motivates athletes to remain involved in the training tasks and the modality and user interface of the feedback are important. Many forms of feedback have been identified and some are successfully implemented but very little evaluation of how such feedback is received by athletes or affects their performances has been done. The work of (Saturday 2006) addresses the effects of feedback mode on rowing performance, claiming their tests were inconclusive, however if it is assumed all experiment participants were equally skilful the data supports the hypothesis that visual feedback is better than haptic feedback. Work in (Ruffaldi 2009) demonstrates vibrotactile feedback through the handle of a rowing simulator is not as good as visual feedback, which is not as good as both together, if results are averaged over six experiment participants. Although the method used a rowing simulator, the evaluation did not test the feedback on an athletic performance, merely on the very different task of tracing the shape of a square whilst sitting still. There was no control used to compare performances with using no feedback and the speed profile of the trajectory is ignored. The work does not address the relationship between handle trajectory and the quality of the entire technical performance either.

(Kleshnev 2004) states that traditional feedback usually works through the coach and the delay time could be from minutes or hours up to days or weeks. Immediate feedback presents information to an athlete and delay time is in a range of seconds.

(Smith 2002) Almost any valid feedback will improve the performance of a novice rower. However, the elite rower requires very accurate information for the detection of errors in a performance that is already proficient. This feedback can be intrinsic or extrinsic; the latter can consist of knowledge of results or knowledge of performance. Knowledge of results allows performers to examine their efforts in relation to an externally defined goal. However, such information feedback provides only goal-related information and ignores knowledge of performance, which is information about how the action was completed (Newell and Walter, 1981).

Furthermore, (Newell and Walter 1981) maintained that the provision of kinetic information feedback is preferable to mere knowledge of results and that feedback should occur as soon after performance as possible

The type of feedback provided by a coach can also have a big impact on performance, be it delayed or immediate, visual, auditory or hepatic. The work of (Saturday 2006) addresses the effects of feedback mode on rowing performance, claiming their tests were inconclusive, however if it is assumed all experiment participants were equally skilful the data supports the hypothesis that visual feedback is better than haptic feedback. According to (Kleshnev 2004) a useful method of feedback is to overlay biomechanical parameters and video footage. This helps to connect a visual image of the rower with internal biomechanical parameters. Computer animation methods can also be used for an easier understanding of the interaction of different parameters

(Soper 2004)Rowing instrumentation has improved noticeably in the last 10 years. Advances in micro technology have allowed on-water analysis of force application profiles from the feet and oar to be frequently reported in the literature. (Baird and Soroka1951) and (Cameron1967) used modified strain gauges and photographic analysis, respectively.

Spinks and Smith (1994) used a template and concurrent visual feedback of the force on the handle and angular position of the handle of a rowing ergometer to investigate whether such feedback could improve the consistency of the rowing performance.

The results of their study indicated that, at least for ergometer rowing:

(1) Concurrent visual feedback may be used to modify patterns of work output during maximal rowing and to enhance maximal rowing performance;

(2) There is biomechanical support for the even pace race strategy in competitive rowing; and

(3) Examination of the force± angle profile may allow coaches to identify those biomechanical factors which limit rowing performance

2.4 Rowing Ergometer

In training, as well as in testing concerning strength and endurance parameters of rowers, the use of rowing ergometers is common. The Concept2 ergometer is the most widely used. The rowing movement is simulated by pulling the ergometer handle. The force applied to the handle depends on the velocity of the flywheel, on the brake acceleration, and on the position of the handle. The Concept2 will only allow a symmetrical movement that resembles sculling. However, sweep-oar rowers are tested under such symmetrical conditions. Because ergometer rowing is symmetrical, investigators mainly focused on sculling had restricted recording of muscle activity to one side of the body. Under such experimental conditions, the detection of possible asymmetries in muscle activation between the two sides was not possible. While it is a good tool for the workout and the development of energetic resources, it is not appropriate for rowing technique and team training, since it does not allow the user to correctly reproduce the real gesture. Similarly in laboratory conditions the information about the effect of common displacements of the gravity centres of the boat and of the oarsman, about the character of the power characteristics etc., is lost.

Researchers have studied both rowing kinematics (Nelson and Widule, 1983) and kinetics (Macfarlane et al., 1997) on rowing ergometers .An ergometer-based biomechanical feedback system was developed to provide integrated kinematic and kinetic data in real time. While the athlete rows, a two dimensional stick figure of the rower is displayed above the power profile produced during the drive (power-producing) portion of the stroke.

Ergometers may be used for training during poor weather technique coaching, crew selection and performance tests. Additionally, ergometers allow for research in a controllable and technically simpler environment than the outdoors. The findings from research investigating the ability of an ergometer to simulate on water sculling or sweep rowing technique typically support the use of ergometers.

2.5 Inertial Sensors

"Wireless Sensor Networks (WSN) provide the potential to collect data at spatial and temporal scales that are often times not feasible with existing instrumentation" (Llosa 2009)

As described in (Rodríguez-Silva 2008), several different aspects must be taken into account to evaluate the quality of motion sensor systems:

• Update rate: the frequency at which the data is read by the sensors. A high update rate is better.

• Delay: The time between the motion and its detection by a sensor.

• Accuracy: The amount of error in the measurement.

• Resolution: It is directly related to the smallest motion that can be detected by the sensors.

• Drift: The measures can take absolute values of a coordinate system or represent changes from the last position.

• Range: Working set of values (between the minimum and maximum) for the sensor system.

• Size: Motion sensors must be lightweight devices, to facilitate wearing them.

• Robustness: Tracking dependence on environmental factors must be minimized.

• Degrees of freedom (DOFs): Number of independent variables the tracker uses to measure the motion.

• Wired/Wireless nature: It affects the freedom of movement.

The Deployment of low cost WSN has been proven to be an adequate mechanism for on the field data acquisition. With the rapid advances in sports technologies, athletes and sports coaches are constantly searching for improved performance assessment methods. While athletic performances continue to improve, accurate training prescription and feedback is vital to the consistency of the training outcomes and maintaining the level of performance. The primary aim of athletes is to improve their performance to achieve their objectives.

Current research in activity recognition from wearable sensors covers a huge range of topics with research groups focusing on topics such as, healthcare and elderly care and recognition of activities of daily living. Accelerometers are the most commonly used type of sensor for activity recognition with wearable sensors.

(Page 2003)Wearable inertial sensors have been used for motion classification and tracking in prior work - for example, in monitoring the activity of people at home, mainly for medical purposes (Tapia 2003)

A recent study by (Jasiewicz et al. 2007) found that similar orientation sensors were suitable for measuring cervical joint range of movement for neck pain assessments. A primary advantage of using these types of sensors is that they can be used relatively easily outside of a traditional laboratory setting, e.g. patients home, workplace or community.

(Kambiz Saber-Sheikh 2010) Inertial sensors are portable, relatively inexpensive and fairly easy to use, although measuring and analysing movement data in three dimensions is not a trivial exercise and requires knowledge of 3D kinematics. This study shows that it is feasible to use inertial sensors to study functional activities such as walking. It is possible that the sensors may be used to study motions of other body joints and other functional activities, and "future work should examine the feasibility of these applications."

2.6 Shimmer

Shimmer is a small wireless sensor capable of recording and transmitting physiological and kinematic data in real time. Shimmer incorporates wireless ECG, EMG, GSR, Accelerometer, Gyroscope, PIR Tilt and vibration sensors. Shimmer has a full range of kinematic modules for wearable inertial measurements and complex motion sensing applications. Inertial measurement units can be very useful to applications involving any level of biomechanics, motion tracking, orientation or activity classification. Shimmers kinematics modules have been applied to aspects of personal monitoring to classify and measure levels of activity, calorific expenditure, posture and gait analysis, motor fluctuation, monitor rehabilitation, assess exercise accuracy and compliance and for environmental vibration monitoring.

(Patel 2007) Investigated the use of Shimmer as a tool for monitoring patients with Parkinson's disease in their homes. Due to resource limitations, it was not possible to perform all computations in real time "Thus we must make several compromises between result delay and result quality"

(Lorincz 2009) also found the energy demands of the device to be a limiting factor. "We do not expect energy limitations to go away anytime soon, despite advances in device miniaturization and power"

(Patel 2008) "Two key points toward developing the tools necessary to achieve continuous monitoring of motor function are (1) development of a robust and deployable wearable wireless network of sensors and (2) the development of analysis techniques to derive clinically relevant information from miniature sensor data"

( Lorincz 2007) is a wearable, wireless health research platform with a 3-axis accelerometer and Bluetooth radio together with a micro SD slot for copious on-node data storage. These systems lack sufficient sensor degrees of freedom, sampling rate, and dynamic range for our applications and often employ limited sensing channels to mitigate costs


3.1 Shimmer development

Before any testing could be carried out, it was first necessary to do a great deal of pilot testing in order evaluate what the Shimmer devices were capable of. The first step in this process was to outline what was required in order for an optimal intervention.

3 shimmer devices working from one laptop using Lab view

Auditory Tone when accelerometer data leaves band-width set for back measures

Acceleration-Acceleration Graph with data from arm, plotted against the data from the leg

This would be Laid over an "ideal graph" obtained from the data of an experienced rower

This pattern would then reset at the end of each stroke, and start again.

It would also be necessary for LabView to record the accelerometer data in a Microsoft excel file when the data streaming was initiated.

The 1st step was to connect and calibrate the shimmer devices to the supplied laptop using a Bluetooth adaptor. This was achieved using the instructions supplied with the sensors, once this was achieved the devices were tested using the supplied software and found to be fully functional. In order to achieve the level of feedback that the study required it was necessary to use LabView. LabView is a platform and development environment for a visual programming language, making it possible to create an individualized display for the shimmer devices. The first page of LabView code (Appendix B) was downloaded from the shimmer website. This produced accelerometer and gyroscopic data in 3 planes for one shimmer, however the code also had a built in delay which needed to be removed .The delay was eliminated from changing some constant values embedded within the code. Although the original code provided a template to work from, it was necessary to alter it further in order to have 3 shimmer devices working from the one LabView VI. This edited LabView code (Appendix B) was then pilot tested, however this produced a delay which could not be removed making real time feedback impossible in addition to the graphs containing too much noise making them impossible to read.

When attempted with 2 shimmers in the LabView VI similar problems arose with a similar delay and graph issues. This meant that it was no longer possible to provide a graph which plotted the arm data against the leg data. As a result it was only possible to take data from the leg.

Due to these complications, it was necessary to have 2 shimmer devices operate from 2 separate laptops, using a different type of software known as shimmer connect. This software was ready built and streamed the required data in real time. However it was not possible to edit this program to achieve the requirements stated above.

3.2 Subjects

3.2.1 Subject Characteristics

18 subjects volunteered to participate in this study 12 males and 6 females. There were no dropouts over the course of the 2 week study. Participants (Mean [SD]; age 21.39[0.70] yrs., height 176.99 [7.69] cm, weight 72.02 [11.03] Kg) were recruited via word of mouth and email from the University of Limerick. Subjects were required to have less than 6 months rowing experience, no competitive wins and have been injury free for 3 months. Subjects were then divided into a control and experimental group using randomisation tables.

3.2.2 Ethical Procedures

All procedures were approved by the PESS Research Ethics Committee Prior to participation, testing procedures and any possible risks were outlined. Subjects then gave written informed consent and successfully completed a PESS pre-test questionnaire

3.3 Procedure

3.3.1 Rowing Ergometer

A RowPerfect (RowPerfect, CARE RowPerfect, The Netherlands) ergometer was used for this study.

3.3.2 Pre-Test

In order to obtain each subjects rowing technique prior to the intervention, each subject completed a pre-test on the RowPerfect without feedback while the Shimmers recorded each subject's data. Prior to this test, subjects completed a PESS pre-test questionnaire and had their height and weight recorded.

3.3.3 Instrumentation

Shimmer inertial sensors were used to capture and display the subject's kinematic data. The software used was Shimmer Connect.

3.3.4 Experimental Set-Up

Due to Limitations of the shimmer devices it was necessary to have 2 shimmers operate from 2 Laptops, one showing Data from the back and another showing the data from the tibia. In addition to this it was also necessary to show the stroke-rate data using the Row-Perfect, in order to ensure that all subjects stayed within a certain rate. Beside each Laptop was an "Ideal Stroke" obtained from an experienced rower using the same technique used on the subjects. This rower has 7 years rowing experience and has rowed at an international level. (Appendix ) Subjects were then asked to match the ideal stroke as best they could using the real time accelerometer data being streamed to the laptop screen.

3.3.5 Preparation of Subjects

Subjects were requested to wear shorts, a t-shirt and comfortable shoes. This made it easier to apply the Shimmer Devices to each subject, and didn't restrict their movement. Before the subjects began the warm up, they were seated in the Row Perfect and secured into the seat and foot stretcher.

The shimmer device was then attached to the shank using a Velcro strap, half way between the medial epicondyle of the right knee and the medial malleolus of the right ankle. If needed the shimmer was also secured using insulation tape.

Subjects were given 5 minutes prior to the start of the test to warm-up on the erg and to stretch. Each warm-up was subject - specific and similar to the process they would go through prior to training.

3.3.6 Data Collection

During the Warm up, 30 seconds of a sample was taken to ensure the shimmer was fully functional. The subjects were then instructed to row at between 20 and 25 strokes per minute. Using Shimmer Connect it was possible to record the data in an excel file as it was streaming.

3.4.0 Data Analysis

Once the Data was captured pre and post, test for each subject it was then necessary to analyse it. The 1st stage of this process was to divide this data into its individual strokes. In order to do this, each data point was examined. The 1st 5000 data points were ignored, as this allowed the subjects to warm up and develop a comfortable rowing pattern. Each stroke would begin on the lowest data point and continue until a peak was reached; the stroke would then finish at the lowest point. In order to ensure that the data corresponded with stroke pattern, each stroke was then represented on a scatter plot vs. time. A sequence 50 strokes was taken from each subject.

As each stroke was of varying lengths, this data was then plugged into a programme written in LabView (v8.2, National Instruments Corporation, USA) which used a cubic spline to normalise each stroke to 1001 data points. From this point it was now possible to compare each individual stroke to that of the "Ideal Stroke" obtained from the experienced rower. This was done using XLSTAT's (Fahmey 1999) Bland-Altman feature. A Bland-Altman plot is a method of data plotting used in analysing the agreement between two different sets of data. This software made it possible to calculate the mean level of agreement for each stroke, each subject and both the control and experimental group.

3.4.1 Statistical Analysis

Statistical analysis was performed using PASW Statistics 18.0 for windows (SPSS Inc., Chicago, IL.) A Shapiro-Wilk test, which was used due to the small sample size, confirmed that all variables were normally distributed. Paired t-tests were used to examine the changes in percentage difference pre and post-test in the control and experimental groups. Alpha levels set at a = 0.05 and a = 0.01 were implemented to determine significance

A paired sample t-test was conducted on all variables to evaluate the impact of immediate feedback from the shimmer wearable sensors. There were no significant differences in any of the variables however there were increases in levels of agreement in 7 of the 9 subjects in the control group, while there were increases 5 of the 9 subjects in the experimental group. Both groups increased their average levels of agreement. The control group had an average increase of 2.44% while the experimental group had an average increase of 2.87%.


4.1 Bland-Altman Analysis

Fig 4-1 Bland-Altman difference plot for subject 12 pre-test who showed the largest improvement in levels of agreement in the experimental group.

Fig 4-2 12's post-test Bland-Altman graph. While there does appear to be an improvement in the subjects stroke pattern, the P value was P>.05 and deemed not to be significant

Bland-Altman analysis was carried out on every stroke of each subject for the pre and post-test in order to calculate the levels of agreement between the subject's stroke pattern and the one they were asked to replicate. From this analysis it was possible to obtain the percentage difference between each subject's individual stroke and that of the experienced rower. From this information average values were obtained for each subject's pre-test and post-test.


Experimental Pre

Experimental Post

Subject 2



Subject 3



Subject 16



Subject 7



Subject 5



Subject 14



Subject 15



Subject 18



Subject 12






Fig 4-3 table summarising the results of the Experimental group


Control Pre

Control Post

Subject 13



Subject 9



Subject 1



subject 17



Subject 11



Subject 6



Subject 4



Subject 8



Subject 10






Fig 4-4 table summarising the results of the Control group

4.2 Levels of Agreement

The Results above show that while in some subjects an increased agreement level between the strokes over the course of the intervention was observed, these results, were not significant as P> .05. Both the control group and the experimental group did increase their average levels of agreement, however when examined on a subject by subject basis in figures 4-5 and 4-6 it is clear that there is no relationship between this increase and the use of shimmer technology as more subjects in the experimental group observed a decrease in levels of agreement when compared to that of the control group.

Fig 4-5 and Fig 4-6 the average results pre and post-test for both groups.


The results of this study seem to suggest that rowing on a RowPerfect ergometer 3 times a week for 2 weeks has no significant impact on an inexperienced rower's performance. The statistical analysis of both the control group and the experimental group returned P values of 0.320 and 0.386 respectively. Although some subjects, did improve over the course of the intervention, the P values obtained for the individual increases in levels of agreement were P>.05.

6.1 Feedback

As previously stated there was no significant improvement in the rowing stroke for the control or experimental group. This would suggest that Shimmer is not a reliable feedback tool. One possible reason for this is that the Kinematic data displayed may have been difficult to interpret when compared to more conventional forms of feedback. However, a study by (Anderson et al 2005) Used an accelerometer-based kinematic feedback system using "LabView software and a DAQCard-AI-16E-4 data acquisition card (National Instruments, Texas, USA), in conjunction with IC-based ADXL202 accelerometers (Analog Devices, Massachusetts, USA -Analog, 2002)". This system provided actual kinematic data during the stroke, similar to that of the shimmer devices of this study. The study concluded that both feedback interventions used were successful in improving kinematic consistency and performance consistency but did not result in a statistically significant improvement in performance indicators. The results of this study show no such improvements. However the more detailed LabView system seen in that particular study, provided a bandwidth in conjunction with the kinematic data, "The acceptable performance bandwidth this is based on 15 consecutive strokes extracted from data acquired during two minutes of steady state rowing at 20 strokes per minute immediately before the 2000 m trial, when in a non-fatigued state. Therefore, the acceptable performance bandwidth represents the individuals' variability in a non-fatigued state" this more detailed and accurate visual feedback was provided on screen in conjunction with the kinematic data, this would make it easier for subjects to see a poor stroke pattern and try to correct it. Had the Shimmer devices been more compatible with LabView it would have been possible to provide a more detailed and beneficial feedback system on screen similar to that used by (Anderson et al 2005). ). More recently 3D accelerometers have been used to aid more precise stroke phase determination and GPS has also been employed for more precise position determination. (James 2004)

Generally speaking, however, the nature and frequency of synchronization feedback are rather poor, and no experimental study has ever validated their usefulness in the teaching of team rowing (Filippeschi 2009). Specific technique training sessions are seldom performed separately, and are often the last part of fitness training sessions. It is currently assumed that if rowers classed as novice or intermediate, are able to develop force-time profiles similar to elite rowers, will improve their own performances. Had this study had a longer intervention there may have been a significant improvement in technique. However as technique varies on an individual basis, there are no optimal parameters that all rowers should exhibit.

Video analysis can be utilised, however, due to the on-water nature of this sport, footage is not viewed for some time following completion of the movement. Changes to technique most commonly occur as a coach is providing verbal cues to a rower. Trying to modify a pattern of movement once it has been learnt requires the learning of a new movement pattern.

(Soper 2002)Visual feedback in real time was provided to eight "rowers" whilst rowing on-water via a telemetry GTS. Although there were no significant differences in ensemble average lumbopelvic angles within or between testing sessions, there was a trend for small increases in lumbo-pelvic angle for six subjects when analysing individual data. This would suggest that even immediate visual feedback has little effect on a rower's technique. The results of this study are similar to that of (Soper 2002)

6.2 Potential uses

All rowers have to learn how to synchronize their movements with the others. Even professional rowers have to learn this synchronization skill when constituting a new team. For teaching how to synchronize with a teammate, two possibilities are available to coaches: the field situation or the simulator situation. The field situation is mostly based on verbal feedbacks provided by the coach, which is seldom precise enough and producing an adequate level of synchronization takes time. However, it is often used because rowers directly adjust their movement in the natural environment. The second way uses the rowing simulator. The disadvantage of simulators is that water and boat movements are neglected or unrealistic, and it sometimes requires an extra period of adaptation to adjust inter-rower synchronization.

Athlete's improvement depends on multiple metrics that coaches attempt to study and understand. Normally, most of the metrics are studied through simple observation or athletes sensations. This information, even extremely useful, is not accurate or completely objective. One of the main problems is to obtain objective diary information of the capacities and abilities of the athletes, without interfering with them. Using Shimmer Connect however, the Shimmer devices were able to provide Real-Time visual feedback. In addition to this feedback it also recorded the data, making it possible to analyse it at a later date. This makes the devices ideal for field testing. In theory the Shimmer devices could capture this data on an iPhone or a netbook, providing feedback to the rowers while obtaining data from on water rowing. "Post activity analysis and stroke diagnosis has been useful for Australian teams to compare inter-team differences thus helping to refine and develop race strategies. Statistical information derived from these phases of motion are useful benchmarks for coaches that have traditionally been difficult to obtain without purpose instrumented boats and/or video analysis"

As stated in the Literature Review while rowing ergometers are commonly used for performance testing, technique coaching, crew selection or for training during poor weather (Soper 2004) "ergometers do not allow good reproduction of trunk and upper limb body patterns compared with on-water rowing or sculling due the central pulley system most often used" As a result, the acceleration data obtained using the shimmers could be used to calculate force production for each stroke in on water rowing. This provides an excellent platform for analysing rower's technique during competition as opposed to using purely outcome measures." Performance characteristics are further increased during competition when compared to regular training. By better understanding athlete performance during the competition environment coaches can more effectively work with athletes to improve their performance" (James 2004)

In addition, the feedback received from the shimmer devices may also allow coaches to identify rowers who may be predisposed to injury, if this is identified in time it would allow athletes to be rested, encouraged to alter their technique, or advised to target specific muscle groups in an attempt to prevent such an injury.

5.3 Conclusion

This study concludes that the accelerometer data provided by the shimmer devices, when used alone, without an on screen indicator to tell the subject how accurately they are performing, is not a viable feedback tool. However, utilization of a sensor platform like Shimmer greatly simplifies the process of measuring an athletic event and turning it into something useful by providing, support for the sensor, basic signal conditioning, storage and application specific processing of the data. In the case of sporting applications this approach allows rapid customization and modification as the technical expertise, understanding and expectations of sport scientists was found to develop rapidly along with prototype systems developed for testing. Accelerometers when combined in such a system have enabled the recording of athlete activity and the storage and/or transmission of data.

5.3.1 Limitations

The experimental set-up meant that subjects had to divide their attention between 3 different visual stimuli. Had the Shimmer devices been more compatible with LabView, It would have been possible to provide a much more detailed feedback mechanism. Ideally this would have resulted in the subjects having to react to a visual stimulus and an auditory tone. However the delay in feedback from the Shimmers when using LabView made Real-Time feedback impossible.

Time constraints were also an issue due to the fact that the development phase of Shimmer with LabView took longer than expected. A longer intervention would have provided more information about the use of shimmer as a feedback tool. As previously stated technique varies on an individual basis and there are no optimal parameters that all rowers should exhibit. The fact that each subject was asked to copy the same rowing stroke did not take this into account.

6.3.2 Future research

Future research that could be carried out using Shimmer technology would be using the devices to measure consistency in a similar vein to (Anderson et al 2005). With each subject's stroke pattern being individualised. Also the use of Shimmer outside of a Laboratory setting appears to be the next logical step in analysis of the rowing stroke.

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