How to set up a target

The target that we had to set up was made last year by students in the mechanical engineering department, our task was to set up the target in practice for elite cricketers to throw against. With our first attempt it took us a significant amount of time (nearly an hour) to finalise setting up the target but with practice we believe we can shorten this down to 15 minutes each set up.

set up the outer frame stand using bolts, the washer and a spanner. To align the right corners together you need to match up the shaped stickers to its corresponding shape on the other corner frame stand. There were three shaped stickers: Stars, triangles and circles. The corner should look like this:

Fig 1. Corner with triangle shaped markers

Complete this for all four corners and then install the middle stand using bolts into both the top and bottom of the frame, once this is done the standing frame should be completed and should look something like this:

Fig 2. completed target frame

Now this is completed its time to set up the target, you'll need more than one person to help you lift and place the target into place. the target needs to aligned into the metal brackets that can be found on both sides of the standing frame. You have to make sure that the bracket is straight and perpendicular to the ground, to do this you have to use an Alan key to move the bracket up or down so that both sides are in line. Once you believe the brackets are in line and the target looks straight, use a leveling tool to confirm this. This is how the metal bracket looks and how to align it:

Fig 3. frame being leveled using brackets that are aligned using Alan key

Finally, once the target is aligned and leveled the target should be completed and this is how it should look:

Fig 4. Finished target

Neuro-protection by caffeine in a model of Parkinson's disease.

Today I just want to discuss Parkinson's disease and caffeine. Xu (2010) co-authored a paper in which caffeine was noted to hold a neuro-protective effect in a mouse model of Parkinson's disease.

They claim that this is perhaps down to dopaminergic neuron toxicity being attenuated and weakened by the administration of caffeine, at least in mice.

A couple of studies were run investigating the temporal onset of protection and what was found is quite interesting;

Study 1 - Pre-MPTP

The first study investigated giving caffeine (30mg) 10 minutes, 30 minutes, 1 hour and 2 hours before an MPTP (Methylphenyltetrahydropyridine - a known neuro toxin related to Parkinson's disease) injection and found that caffeine greatly attenuated toxicity induced striatal dopamine depletion. Caffeine was also trialled 6 hours before the treatment but did not attenuate toxicity.

Study 2 - Post-MPTP

The second study looked at a second group of mice who had not been given caffeine prior to MPTP injections but were given caffeine after MPTP injections. The results here also showed similar attenuation but only if given up to 2 hours after and did not weaken toxicity after this point.

These results show that caffeine does have a neuroprotective effect in the MPTP model of Parkinson's disease, at least in mice. It would be incredibly interesting to see this replicated on a human sample to investigate further.

Xu, K., Xu, Y., Chen, J., & Schwarzschild, M. (2010). NEUROPROTECTION BY CAFFEINE: TIME COURSE AND ROLE OF ITS METABOLITES IN THE MPTP MODEL OF PARKINSON’S. Neuroscience, (167), 475-481.

Research Project Into the Dynamics of Throwing

Just an update on dissertation progress:
After recently finishing a movement analysis essay on biomechanical equipment and the relatively high costs of each piece (some up to £10,000 a camera!) we have started to look at equipment we will ourselves use in our investigation into elite throwing using cricketers from the University of Leeds.
Our task last week was to assemble a target made for the perception and action lab last year and it's fair to say it's not the most expensive piece of equipment and that we were not the best at assembling it! However, the target that was actually made for us by students doing engineering last year and is perfect for the experiment we are going to conduct and I'm sure the practice of putting it together should cut the time down from an hour (1st attempt) to at most; 15minutes during the real experiment.
We are meeting Brendan today to sort out the use of the cameras (a very expensive piece of equipment) and will try to familiarise ourselves as best as possible with the equipment before the day of the data collection.
We will be completing a step by step guide of how to put together the target and use of the camera in an attempt to partly complete and have a framework of the method section of the dissertation write-up.
That's all for this week.
Vince.

Bimanual coordinated rhythmic movements

This study is my first proper taste of real experimental science. So the results of which could either be a source of immense frustration, relieve or equally delight. The first part of my study is relatively simple and involved 12 younger adult participants aged 18-27 (M=21) performing bimanual coordinated rhythmic movement training using one of two displays; Lissajous display or a coordination feedback display. With assessments at baseline and post training tests on both of these. In addition to this judgement tasks were performed at baseline and post training. The aim of this research is to directly compare the two feedback methods as they are both established but have not yet been compared.

After compiling and analysing my control group data for the current study a number points became clear. Results were either reassuring relationships or slightly surprising but none the less logical and somewhat exciting developments.

To start with the reassuring results. As this is my first study without peers or a supervisor present throughout all the data collection I was impressed to see my results conformed with almost everything written in this subject. To no great surprise 0 and 180 degrees mean relative phase were the most stable conditions during coordinated rhythmic movement performance. 90 degrees was the least stable with a significantly lower proportion of time on task compared to the two stable states. To make things even better, a relatively well established effect of training in younger adults was recorded. Training at 90 degrees in both feedback methods resulted in improved stability at 90 degrees in the trained condition with no generalisation to other phases.

This however is where the frustration began...
There was no transfer of learning from the trained feedback methods to the untrained method. Initially this was a little disappointing as this was not expected or more correctly not the desired outcome. It was originally hoped that the coordination feedback training group would show transfer to the Lissajous feedback but not vice versa. However on closer inspection the actual results provide strong evidence for perceptual learning and differing task dynamics. This is evident as people learnt to use the trained feedback method correctly. In such that people do not learn the desired movement pattern per se, but learn how to produce the desired feedback display. As a result people learn to perceive their movements in the form of a movement display not as an action. Since this is the case and no transfer occurred it suggests that the two feedback methods are informationally distinct from one another. With the learnt perceptual information encapsulated within the specific feedback displays. Therefore each group learnt fundamentally different task dynamics where subjects learnt to generate 90° mean relative phase using specific visual feedback.

With a bit of dedicated time and thought these results are not altogether surprising and tie up loose ends between the Lissajous and Coordination feedback displays; as direct comparisons are now possible between the two feedback methods.
Despite this, questions still arose from other areas of the results. Firstly in our study 0 degrees and 180 degrees are defined in terms of visual feedback not muscle activation. As a consequence 0 degrees produced a non-homologous muscle group activation whilst 180 degrees produced homologous muscle group activation. Which may account for a slightly higher than normal 180 degree performance. Secondly the judgement data did not change with training, but this may have been due to the design of the study. As judgements were performed at 1Hz which may be too fast to allow successful judgements of phase to occur.
In conclusion after dipping my toe into the water for the first time so to say the results were very positive and have produced favourable and exciting data from which my thesis and first paper can be written. So all in all I would say so far so good.

The Timed Up & Go Test: Its Reliability and Association With Lower-Limb Impairments and Locomotor Capacities in People With Chronic Stroke

The aim of the study was to examine test-retest reliability of the Timed Up & Go test, its ability to differentiate subjects with chronic stroke from healthy elderly subjects, and its associations with ankle plantarflexor spasticity, ankle muscle strength, gait performance, and distance walked in 6 minutes in subjects with chronic stroke. The individual measures used for the test was the Berg scale and the Barthel index.

For this study twenty one participants were used for the task (ten healthy elderly adults and eleven elderly adults with chronic stroke). The study also conducted four clinical and laboratory measures of the lower limb functions. They are spasticity of the plantarflexors, maximum isometric voluntary contraction of the ankle muscles, gait performance and a six minute walk test.

The timed up and go test required subjects were required to stand up from a chair with armrests, walk 3m, turn around, return to the chair, and sit down. The time taken to complete this task was measured in seconds with a stopwatch.

Results showed the spasticity in the ankle plantarflexors in the affected legs of subjects with stroke was significantly (P_.001) higher compared with their unaffected legs and with the mean scores of both legs in the healthy elderly subjects. For gait parameters, patients with stroke walked significantly (P_.001) slower (mean gait velocity, 48.7_22.1cm/s) than the healthy elderly subjects (mean gait velocity,125.6_23.8cm/s), with significantly (P_.001) reduced cadence (84.3_20.7 steps/min) compared with the healthy elderly subjects.

The study concluded that results show that there was a high degree of test-retest

reliability in the Timed Up & Go test scores in elderly subjects with chronic stroke. These scores were capable of detecting differences in functional mobility between healthy elderly subjects and subjects with stroke.

60-90 Minute Naps VS 200mg Caffeine - Motor Learning & Perceptual Learning

Whilst doing some research into the effects of caffeine on motor skill aquisition I came across one particular study which comes from the department of an old lecturer of mine and caught my attention more than the rest. A study that has come from the Department of Psychiatry & Veterans Affairs in San Diego, California by Mednick (2008) has showed that a 200mg supplement of caffeine significantly impaired motor learning compared to groups which were allowed to nap for 60-90 minutes, and more shockingly compared to a placebo group.

The study investigated three main areas of cognition; 1) verbal memory, 2) motor skill acquisition and 3) perceptual learning.

1) Verbal memory - two verbal memory tasks were administered to all groups of participants, shortly after the tasks there were interventions. 7 Hours later the participants were tested on the verbal memory tasks and the results showed that the "nap" group performed significantly higher in this when compared to the caffeine and placebo group.

2) Motor learning - On this task it was the placebo group who out performed all others - the results in this task were infact quite varied in that the caffeine group appear to have been incredibly impaired. See image below.

3) Perceptual learning - Napping & Caffeine produced high perceptual learning compared to the placebo group.

Interested in reading more? The full PDF can be found here: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2603066/pdf/nihms65981.pdf

A COMPARISON BETWEEN NOVICES AND EXPERTS OF THE VELOCITY-ACCURACY TRADE-OFF IN OVERARM THROWING

A study was conducted to investigate the speed-accuracy trade off in expert and novice throwers, and the movement strategies used to execute the task of throwing. It was hypothesised that the experts would maintain high accuracy throughout the range of velocities, and that the novices would show a trade in accuracy and velocity. It was also hypothesised that a change in co-ordination strategy would be expected in the form of movement patterns leading to a throw between the different groups.

The experts, in this case were male team handball players from a Norwegian second division team, and the novices had never been involved in any organised sport that required any form of throwing activity.

The data was gathered using 3D cameras, with markers placed on the body at the shoulder, hip, elbow, wrist and the ball was also tracked. Linear velocities of these points were calculated, along with time of release and total movement time. Throwing accuracy was measured by a video camera, and a ‘hit’ was recorded when the centre of the ball hit the centre of the target, otherwise, a ‘miss’ was noted.

There were several conditions, the first was where the participants were asked to throw the ball as fast as they could, in order to record maximum velocities. The second condition was also a throw at maximum velocity, but with accuracy as an afterthought. The third condition was where velocity and accuracy were equally important. In the forth condition, accuracy was the main priority with velocity as a secondary priority, and in the final condiditon the only priority was to hit the target with velocity made irrelevant.

In summary, the throwing performance of the experts was better than that of the novices in every condition, as expected, both in terms of speed and accuracy. Also, in the experts, the velocities of most of the body segments were higher than that of the novices. However, no significant differences in absolute and intersegmental timing of the movements of the body segments was found between the two groups. Also, in terms of speed-accuracy trade off both groups performed similarly. This means that when accuracy was required, acceleration and velocities were decreased, although accuracy was not actually improved.

It was thought that the novices would show more of a speed-accuracy trade off as they were thought not to have the ability to throw the ball accurately at high speeds. Therefore, it is suggested that it is the features of the required task rather than the skill level of the subject that explains the lack of a speed-accuracy trade off in handball overarm throwing.

There were no differences in timing of body segment movements between the groups. This suggests that novices and experts may use the same general coordination pattern. The analysis suggests that in a ballistic, whole body movement the accuracy was not affected by a faster execution that was likely to have been induced by more muscle activity.

Overall, it was found that the only essential difference between novice and expert throwers was the use of a wind up or counter movement, which lead on to a stronger and shorter acceleration period. By accelerating and moving faster an expert will reach the end of motion earlier. It is not proved however, that experts use the same movement range as novices. Recent data on throwing with dominant and non-dominant arms suggest that athletes use a longer movement range with the dominant arm.

Throwing velocity and accuracy in elite and sub-elite cricket players: A descriptive study

Throwing performance is a vital aspect of many sports. In cricket, the performance levels of an overarm throw often decide the outcome of the game. The release velocity and accuracy are modified by the player in question to create a speed-accuracy trade-off during the execution of an overarm throw.
110 Cricket players from 6 different populations were selected as participants for this study.
(1) Elite Senior Males
(2) Elite U19 Junior Males
(3) Elite U17 Junior Males
(4) Elite Senior Females
(5) Elite U19 Junior Females
(6) Sub-Elite Senior Males
Participants (Ps) were assessed on maximum throwing velocity, and throwing accuracy at maximum velocity and 3 sub-max velocities.
The tests were conducted in an indoor sports hall with a synthetic surface and max velocity throws were undertaken from a distance of 20.14m from the target. Regulation 4-piece leather cricket balls weighing 156g were thrown into a net. For the max velocity throw test; a net with no specific target was set up. A cordless speed radar gun was positioned behind the net whilst Ps were instructed to throw as hard as possible. All the throws were overarm and Ps were allowed one stride before throwing to minimise extraneous variables such as approach speed and angle.
For the throwing accuracy test, a specially designed cricket target was assembled and throws were made from behind a line at a distance of 20.14m. The target consisted of one cricket stump in the ground surrounded by five markers in order to attribute scores to how close to the stump, the throw hit.
Elite senior males had highest peak and mean throwing velocities whilst groups of males had significantly higher velocity throws than females. A speed-accuracy trade-off existed as all groups had improved accuracy scores at velocities between 75% and 85% of max throwing velocity.
To conclude, sex, playing experience, and training volume may all contribute to throwing performance in cricket players. Further research should be aimed at the mechanisms behind the differences seen in throwing profiles whilst also looking at the training techniques and differences between the genders.

Perceptual Learning Immediately Yields New Stable Motor Coordination

The purpose of this study is to determine whether perceptual training can significantly improve an unstable movement, which in this case is 90º.

12 participants (22-54 years old), half of which were assigned to an experimental group and the other to a controlled group. The experimental group participated in training sessions as well as assessment sessions, receiving feedback at the training sessions. The controlled group did three sessions of movement trials, with no feedback or training given. Experimental group took part in up to 14 training sessions (depending on how quickly plateau state of improvement occurred) and three assessment sessions. Each training set became increasingly harder; participants had a maximum of four repetitions to successfully complete each set otherwise they’d progress automatically. This was done to force learning, rather than having the participants carry out, as many trials as they wished to. Training did not involve any extensive practise regarding the movement task itself so learning is solely based on perception.

Judgement data was analysed first to determine whether the experimental group learnt as a result of the extensive training; which was followed by analysis of the movement data. A repeated measures ANOVA test was conducted to find out whether there were significant results regarding the two groups. The analysed judgement data proved to be significant, showing increments of improvement as training progressed, which resulted in an exhibition of perceptual learning. An analysis of the action data displayed improvements with each movement trial, indicating the ability to perform a 90º movement with more stability. The controlled group’s analysed data showed no significant results, which concludes that they were unable to perform 90º with improved movement stability as trials progressed. These results suggest that the experimental group were able to perform the novel movement as a result of perceptual learning, as the results of the training and movement trials correspond well. The controlled group however, was unable to improve, which leads this study to conclude that if extensive perceptual training were provided, the controlled group would have significantly improved their ability to perform 90º.

This study provides a strong notion towards the interrelation between perceptual learning and the ability to perform a coordinated rhythmic movement and encourages more research to be done in this field, in order to uncover other factors that might impede or improve learning as a whole.

A review of Individual Difference Measures

There have been lots of proposed individual measures concerning the elderly. Each measurement helps to test the differences in a group and a decision on the most appropriate ones to use needs to be made when assessing motor capabilities when the elderly perform the Timed ‘Up and Go’ Test. Particular differences may include the time it takes them, postural sway and jerk. Individual difference measures will help pinpoint the reasons for these differences.

When deciding upon a measure to use there are things that should be considered, particularly reliability and validity. The test might be easy to complete, however if it lacks reliability then it wouldn’t be worth doing because of the pitfalls that could result in the data obtained. Also validity is important to ensure that the measure isn’t a waste of experiment time.

In recent years frailty has been considered in research with the elderly as opposed to just age or disability being a risk factor in decreasing functional mobility. The Edmonton Frail Scale allows the assessment of many different domains such as cognition, social support and functional independence. This measure excludes only few participants (communication barriers and manual dexterity). The test is to be completed by the participant and has been described as brief, valid and reliable. Although it is easy to administer we must be aware of the possibility for incorrect answers given. Some participants may feel embarrasses when answering questions about continence for example. Nevertheless this method is a very popular one, and requires little or no specialist training to administer.

The Barthel Index is a simple index of independence and has been used in hospitals since 1955. The index includes everyday activities (feeding, bathing, and dressing) and these are scored on whether they require help or are independent. One advantage of this measure is its simplicity. It’s very easy to understand as there are strict instructions for each of the categories. It is also a useful test for assessing the progression of independence as it is carried out before and during treatment. However if we were to use this then we would need the carer or a nurse that works with the patients to give us all the necessary information on each patient.

A test that would be very easy to administer and would only need the participants to fill in a short answer sheet would be the Test Your Memory measurement. Having reviewed this method it seems a little bit patronising in places. It would be unethical to have any of the participants feel uncomfortable answering any questions. However this would be a good test for assessing cognitive function because there probably would be a difference in the results obtained from the participants.

Other measures would not be suited to our study. For example, the measurement of grip strength or the Geriatric Depression Scale. Although those suffering depression may not be suitable for the test, it is likely that they won’t need to be tested as it will already be knowledge whether they suffer depression or not.

Perception & Action Lab: Learning a coordinated rhythmic movement with task appropriate coordination feedback

Perception & Action Lab: Learning a coordinated rhythmic movement with task appropriate coordination feedback

The aim of this study is learning to produce a coordinated rhythmic movement (90˚ mean relative phase) using coordination feedback. People cannot produce 90˚ novel movements stably without training. They can only produce two stable movements without training, 0˚ and 180˚. So progression and learning has to occur, in this case coordination feedback is used. A key factor in this study is that feedback should not alter the perceptual information.

10 participants were split into two groups of five. Group 1 (‘Feedback’) received coordination feedback during training; Group 2 (‘No Feedback’) received no feedback. Each group completed the same number of trials.

Baseline and Post-training assessments were taken before the five training sessions. In the five training sessions participants performed ten 20 sec trials with a target mean relative phase of 90˚. When the participant was successfully moving at 90˚ ± error bandwidth colour change was used as feedback. The bandwidth faded in each session from 40˚ to 30˚, 20˚, 15˚ and 10˚. This will drive learning as the participant improves after each bandwidth. A colour change was used as the coordinated feedback because it is said that colour has no affect on movement stability. The No Feedback group also did 50 trials, but with no feedback.

A repeated measures ANOVA was used. The results found that participants who received coordination feedback successfully and significantly improved their ability to maintain 90˚ coordination. The No Feedback group showed no improvement at any mean relative phase. Coordination feedback does not alter or remove the visual information (relative direction). Unlike visual metronomes and Lissajous figures which do alter the perceptual information. The control group in this experiment received practice at 90˚, but no coordination feedback. Learning therefore didn’t occur.

People can not suddenly be able to produce 90˚ movements, they need to practice the movement long enough in order for perceptual learning to occur. This study successfully showed that coordination feedback enhances the learning of 90˚ movements without changing the perceptual information.

Reference

WILSON. A. D., W. SNAPP-CHILDS, R.COATS, G.P.BINGHAM. 2010 Learning a coordinated rhythmic movement with task appropriate coordination feedback. Exp brain research. 205, pp.513-520

The role of the Cerebellum in Learning Movement Coordination

The role of the Cerebellum in Learning

Movement Coordination

W. T. Thach

The aim of this study was to review previous research to see what roles the cerebellum has in learning a coordinated movement.

The cerebellum is said to learn new movements by different pathways going into the cerebellum e.g. purkinje cells. These cells were also said to be the ones producing action potentials when movement occurs.

These different pathways carry information about different situations i.e. learning a new movement. These pathways also contain a great amount of memory cells that contain the information about the new movement that has been learnt. There is also a second pathway that helps these purkinje cells learn and recognize new patterns in the information from the first pathways. In response to the new information that is inputted, new patterns of movements are then created.

Gilbert and Thach (1977) wanted to test to see if the cerebellum actually is involved when trying to learn a new co-ordination movement. To do this they tried to teach monkeys to perform different tasks using a manipulandum against constant torque loads. The main thing they were looking at were the wrist movements of the monkeys.

Within the first 12 to 100 trials the monkeys were able to adapt to the task and this was explained by Evarts (1973) as being because of the long loop functional stretch. This is when the muscle has to activated in order for movement to occur. In order for the muscle to be activated the cerebellum has to be stimulated.

One of the conclusions of the study was that once a skilled movement has been learned, it remains coded in cerebellar memory cells for a really long time.]

Coordination of the many body parts in order to attain smooth movements is usually agreed to be one of the particular roles of cerebellar control. This is often thought of as being due to a “fine-tuning” of the many movement pattern generators downstream from the cerebellum in the spinal cord, brainstem, and motor cortex (Holmes, 1939).

Individual difference measures.

Each participant used in a study differs completely from another; these differences need to be taken into account when carrying out research, to explain both links or anomolies between data collected from each individual. For our study into motor control and learning in older adults, we will need to discover a way to explore the individul differences, in order to explain what happens when the 'up and go' task takes takes different formats, and how people react to them.

Firstly, a reliable measure for individual differences needs to be established. There are hundreds of apporaches in research, and using previous studies I have selected a few that I think would be appropriate for the up and go task.

The mini mental state exam (MMSE) is a 30-point questionnaire that looks at arithmatic, memory and orientation all in the space of around 10 minutes. It is currently used as a screen for dementia or as an indicator of cognitive function, and was developed by Folstein (1975). Scores of above 25 indicate the particiapnt is of sound mind, whereas scors below 9 indicate severe cognitive impairment. This would help research as it would be made clear how cognitive functionality affects how a task is carried out.

Furthermore, Rolfson et al. (2006) developed a valid and reliable version of the Edmonson Frail scale, where frailty as a seperate varible from disability and ageing. A number of tests were carried out on each patient, all aged over 65. The 'up and go' task was included, to test function and mobility, and a clock task to test for cognitive impairment. The results from both of the tasks helped give an indication of both cognitive and physical function, and the results show that despite people being on a similar level of cognitive function, that didn't neccessarily mean they were similar in physical function. this highlights that every individuals needs and personal details differ, and that it is of utmost importance to take these differences into account when trying to correlate data.

Predicting the Probability for Falls in Community-Dwelling Older Adults

This study examined the sensitivity and specificity of the timed up and go test under single task versus dual task conditions for identifying elderly individuals who we prone to falling

Thirty community-dwelling older adults living in the greater Seattle area were enrolled in the study after giving informed consent. The participants were 15 older adults with no history of falls (mean age=78 years, SD = 6 range =65-85) and 15 older adults with a history of 2 or more falls in the previous six months (mean age=86.2 years, SD= 6, range 76-95)

The test was performed under 4 conditions (Timed Up and go, timed up and go with a subtraction task, timed up and go cognitive and timed up and go while carrying a full cup of water). Subjects were given verbal instructions to stand up from a chair walk 3m as quickly and as safely as possible cross a line marked on the floor, turn around, walk back and sit down.

Results showed the older adults with a history of falls were slower than the adults without a history of falling in all 4 conditions. Analysis showed that the difference in time is due to their balance status.

Results suggested that adults who take longer than 14 seconds have a higher risk of falling. The cut off value of 14 seconds is different from that of Podsiadlo and Richardson, who found that a cut off value of greater than 30 seconds was best for predicting functional dependence among older adults

How to Digitise a throwing video

To digitise a video first you need a copy of either the trial version or full version of MaxTRAQ. Once this is done, open up a video file of a recorded calibration, make sure that the video is formatted in .avi form.

Using the scaling tool found under the tools tab, set the dimensions to 1meter/100 centimeters and then left click on both ends of the ruler to plot out a 1 meter/100 centimeter scale. If sound is activated on your computer you should be notified that your clicking has been confirmed by an audible 'beep'. If this action is completed successfully MaxTRAQ will automatically map out a checkered line with your plotted scale.

When finished, save your file as a MaxTraq template file (.mqt) and save it under a suitable file name.

Open this template file that you just saved (you may need to change the file type by clicking on the drop down arrow next to the file name) and MaxTRAQ will automatically ask you to open up another video (.avi) file. This is so that the video will be analysed using the calibrations you had set up using the template. Try opening the .avi video of the throwing video from the sagital plane.

Once this file is open, look under the time frame and deselect the T1 button, this is to see the whole video. Play the video until the point of release and pause at this frame, once at the frame go back 10 more frames using the arrow keys and keep this as a standardised reference point for later.

On the right hand side is a button labeled 'Digitise', click this button and then click on 'Auto-track'. This is found on the bottom-right corner of the screen. From here, click on the ball (you may need to zoom in to be more accurate) and maxtraq should automatically move forward one frame for every click, once again an audible 'beep' should be heard for every click made. Do this for 20 frames so that you have digitised data for both 10 frames before the release point and 10 frames after the release point.

Once completed, save as an ASCII file (.mqa) under a sensible file name i.e 'subject01_10m_eyeheight_01.mqa'. This file can be opened into excel where your X and Y coordinate values would have been automatically plotted. Put this data into a graph to see a curve of your data.

To make the curve smoother and to get rid of 'noise', digitise your data two more times, (so that you have a total of 3 sets of data), plot out an average of the data you have collected and the curve should be smoother and with less 'noise'.