Siliconcoach is making a significant impact in the world of sport, education, clinical practice and sports retail. Our customers are amongst the most successful organisations in the world and include Nike, numerous national academies and institutes of sport, ICC cricket nations, and many of the world’s leading Rugby Unions.
Siliconcoach is also used by sports retailers and manufacturers such as Mizuno, Asics, and New Balance. Additionally, Siliconcoach developed the software for bicycle manufacturer Specialized’s renowned Body Geometry bike fitting system.
Our technology has been adopted within classrooms, giving teachers the ability to visually convey the principles of movement, biomechanics and functional anatomy. Siliconcoach has proven to be a dynamic learning tool that ultimately leads to a greater understanding for teacher and student; coach and athlete; clinician and patient.
Founded in 1997 by New Zealand biomechanist Joe Morrison, Siliconcoach has grown into one of the world’s most successful video analysis companies. A company based on our passion for sport and a firm belief that video analysis can assist in improving and assessing physical performance, rehabilitation, professional development and learning.
Siliconcoach is a committed team of programmers, biomechanists, physical educators and marketing executives who all share a desire to provide simple–to–use products that make a difference.
More about Siliconcoach
Joe Morrison, CEO
With six years of army training under his belt, and a Masters in Biomechanics, Joe Morrison set about revolutionizing the use of video analysis in sport in 1995. Utilizing his biomechanics knowledge, he learnt programming so he could build a video–capture software program that allowed coaches and athletes to break down, study and improve biomechanical technique – a swimming stroke, the running stride, a cricket shot, a golf swing – and from there Siliconcoach was born. Under Joe’s entrepreneurial leadership style, the company Siliconcoach has grown into one of the world’s most successful video analysis companies and now delivers solutions in sports, health, education and retail.
”We’ve done that by building a committed team of programmers, biomechanists, physical educators and health experts who all share a desire to provide simple–to–use products that make a difference.“
Contact: joe@Siliconcoach.com
Graeme Burborough, General Manager
Graeme Burborough has been with Siliconcoach since 2006, utilizing his management skills from 20 years in the finance sector. As well as managing the company, Graeme, who is a keen runner and mountain biker, also looks after the Retail Channel’s bike and shoe fitting product sales ”We’ve got an amazing team here working on some great technology. I’ve seen the company evolve over the years and the development of the new web–based product – The Zone – adds a whole new level of interaction with our retail customers based around provision of employee training programmes.“ When not in the office, Graeme spends time with his family in Central Otago, where he can easily pursue his varied sporting interests of mountain biking, snow skiing and jogging as well as indulging in an occasional sampling of the local produce.
Contact: graeme@Siliconcoach.com
Chris Latta, Lead Programmer
Chris started his career in the education, after completing a BSc at Otago University, and was instrumental in forming the Educational Technology Unit at the Otago Polytechnic. Chris then moved to London working as Technical Lead for a major advertising agency Ogilvy Interactive, where he worked on contracts for clients such as Ford, the TV licencing authority and Clearmoney. On returning to Dunedin in 2007 he worked as a senior developer for Siliconcoach and formed his own consulting company Cugini Technology. Since 2009, he has led the growing team of programmers at Siliconcoach.
Contact: chris@Siliconcoach.com
Steve Stanley, Education Channel and Specialised Team Leader
Steve graduated from Otago University with a Bachelor of Physical Education and a Masters degree in Physical Education in 1992. He has worked as a Research Officer and Lecturer at the Auckland University of Technology in the School of Physiotherapy, where he helped establish the Research Unit, undertook research projects and published in the area of clinical biomechanics. He is also a trained physiotherapist, and was a Senior Lecturer in the School of Physiotherapy in the late 1990s. Since 2006, Stan has been based in San Francisco, where he looks after Siliconcoach in the US market, which includes the Specialized Bicycles account. In his spare time he gets into the outdoors on bike, boat or feet.
Contact: stan@Siliconcoach.com
Ferg d'Ardis, Global Sales
Irishman Ferg d’Ardis is a dedicated Siliconcoach software user. He put TimeWarp to work perfecting his bodybuilding, which saw him go from an amateur to being ranked 3rd at the NZ Nationals within 12 months. So he’s the perfect person to lead Siliconcoach sales around the world. ”Sales of products that work as well as Siliconcoach is one of the things I enjoy most. The opportunity to meet and speak to a lot a new people, most of whom are from a sporting background, is a lot of fun.“ Despite his meteor–like rise in the world of bodybuilding, Ferg is not one to rest on his laurels – he is also a keen runner (undertaking his first mountain marathon last year), rugby player and has been known to partake in the odd game of golf.
Contact: ferg@Siliconcoach.com
Dan Thomas, Marketing Development
Dan is a keen outdoors man who spent his early 20s managing Dive HQ and retail store, Element in Queenstown and leading dive tours to the Doubtful Sounds and Stewart Island. As a keen mountain biker, he spent several years in the UK checking out the trails in the Highlands and around Ben Nevis while working for TIso Blues, specialising in ski and snowboard boot–fitting where he learnt all about how the little things make a big difference. Following on from his OE, Dan came back to Otago to study sport marketing and he is now putting his knowledge to use marketing Siliconcoach Video Analysis product in Sport, Education, Clinical and Retail.
Contact: dan@Siliconcoach.com
Andrew Wood (Woody), Programmer
Woody is a vital cog in the Siliconcoach development Machine and although he can turn his hand to anything, he generally works on software code that handles the video images and drawings that magically appear on your screen when you are using our software. Living in the sunniest part of New Zealand, Marlborough, makes it easy for Woody to get outdoors and engage in his main sporting interest – cycling. When not programming, he trains regularly and races long distance events like the 100km Grape ride that does a loop around the wine growing areas near the top of the South Island. He assures us that any stops for wine tasting are only during the training rides. Although you won’t usually be talking to Woody, you will see the work he does every time you use one of our products.
Jodie Lewis, Adminstrator
David Templeton, Programmer
Reference
R Bartlett. Journal of Sports Science and Medicine. Volume 5, 2006. Pages 474-479.
Source
http://www.jssm.org/
(NOTE: Due to copyright restraints, Siliconcoach cannot give away this resource. You can search for the article from the link above, however, a fee or subscription may be charged by the supplier.)
Abstract
This article reviews developments in the use of Artificial Intelligence (AI) in sports biomechanics over the last decade. It outlines possible uses of Expert Systems as diagnostic tools for evaluating faults in sports movements ("techniques") and presents some example knowledge rules for such an expert system. It then compares the analysis of sports techniques, in which Expert Systems have found little place to date, with gait analysis, in which they are routinely used. Consideration is then given to the use of Artificial Neural Networks (ANNs) in sports biomechanics, focusing on Kohonen self-organizing maps, which have been the most widely used in technique analysis, and multi-layer networks, which have been far more widely used in biomechanics in general. Examples of the use of ANNs in sports biomechanics are presented for javelin and discus throwing, shot putting and football kicking. I also present an example of the use of Evolutionary Computation in movement optimization in the soccer throw in, which predicted an optimal technique close to that in the coaching literature. After briefly over-viewing the use of AI in both sports science and biomechanics in general, the article concludes with some speculations about future uses of AI in sports biomechanics.
Use of Siliconcoach
Professor Bartlett talks about some of the possibilities in movement analysis and mentions that Siliconcoach's programmable "Wizards" are the closest thing he has seen to an Expert System.
Reference
J Cronin, M Nash, C Whatman. Physical Therapy in Sport. Volume 7, Issue 4, November 2006, Pages 191-194.
Source
http://www.sciencedirect.com/
(NOTE: Due to copyright restraints, Siliconcoach cannot give away this resource. You can search for the article from the link above, however, a fee or subscription may be charged by the supplier.)
Abstract
Objective: Compared to measuring static range of motion (ROM) the assessment of dynamic ROM has received very little research attention. The purpose of this study therefore was to determine the reliability of the siliconCOACH motion analysis system for assessing dynamic ROM of the knee joint.
Design: Test-retest reliability.
Setting: Laboratory.
Participants: Ten male subjects unable to fully extend their knee at 90° of hip flexion.
Main Outcome Measures: Static and dynamic ROM over four separate occasions using a video camera and siliconCOACH digitized footage
.
Results: The variation between days for both static and dynamic measurements was minimal (CV<2.1%). With regards to test-retest reliability, the ICC values, were high (ICC ≥ 0.89) for both assessment techniques and the static and dynamic ROM measurements did not differ significantly (p<0.05) on any given testing occasion.
Conclusions: The high ICC and low CVs indicate a high degree of stability between testing days for the procedures used in this study to assess dynamic ROM. Software programmes such as siliconCOACH seem ideal for determining the end range of a movement for both static and dynamic ROM and would seem to offer a functional and cost effective assessment strategy for those practitioners and clinicians interested in the effects of various interventions on ROM.
Use of Siliconcoach
These researchers were interested in the ability of Siliconcoach software to reliably measure static and dynamic range of motion. The concluded that Siliconcoach offers a reliable and functional (face validity) assessment strategy for those practitioners and clinicians interested in the effects of various interventions on dynamic range of motion
Reference
F Vercruyssen, R Suriano, D Bishop, C Hausswirth, J Brisswalter. British Journal of Sports Medicine. Volume 39, 2005, pages 267-272.
Source
http://bjsm.bmj.com
(NOTE: Due to copyright restraints, Siliconcoach cannot give away this resource. You can search for the article from the link above, however, a fee or subscription may be charged by the supplier.)
Abstract
Objectives: To investigate the effect of cadence selection during the final minutes of cycling on metabolic responses, stride pattern, and subsequent running time to fatigue.
Methods: Eight triathletes performed, in a laboratory setting, two incremental tests (running and cycling) to determine peak oxygen uptake (VO2PEAK) and the lactate threshold (LT), and three cycle-run combinations. During the cycle-run sessions, subjects completed a 30 minute cycling bout (90% of LT) at (a) the freely chosen cadence (FCC, 94 (5) rpm), (b) the FCC during the first 20 minutes and FCC-20% during the last 10 minutes (FCC-20%, 74 (3) rpm), or (c) the FCC during the first 20 minutes and FCC+20% during the last 10 minutes (FCC+20%, 109 (5) rpm). After each cycling bout, running time to fatigue (Tmax) was determined at 85% of maximal velocity.
Results: A significant increase in Tmax was found after FCC-20% (894 (199) seconds) compared with FCC and FCC+20% (651 (212) and 624 (214) seconds respectively). VO2, ventilation, heart rate, and blood lactate concentrations were significantly reduced after 30 minutes of cycling at FCC-20% compared with FCC+20%. A significant increase in VO2 was reported between the 3rd and 10th minute of all Tmax sessions, without any significant differences between sessions. Stride pattern and metabolic variables were not significantly different between Tmax sessions.
Conclusions: The increase in Tmax after FCC-20% may be associated with the lower metabolic load during the final minutes of cycling compared with the other sessions. However, the lack of significant differences in metabolic responses and stride pattern between the run sessions suggests that other mechanisms, such as changes in muscular activity, probably contribute to the effects of cadence variation on Tmax.
Use of Siliconcoach
These researchers used the timer and frame by frame capabilities of Siliconcoach software to determine the kinematic variables of running under the different conditions.
Reference
JL Cochrane, DG Lloyd, A Buttfield, H Seward. Journal of Science and Medicine in Sport. Volume 10, Issue 2, April 2007, Pages 96-104.
Source
http://www.sciencedirect.com/
(NOTE: Due to copyright restraints, Siliconcoach cannot give away this resource. You can search for the article from the link above, however, a fee or subscription may be charged by the supplier.)
Abstract
Anterior cruciate ligament (ACL) injuries are the most costly injuries in football at both professional and amateur levels (Orchard J, Seward H, McGivern J, Hood S. Intrinsic and extrinsic risk factors for anterior cruciate ligament injury in Australian footballers. Am J Sports Med 2001;29:196-200.). In this study video analysis of 34 ACL injuries in Australian football was performed to investigate the causes of these injuries. Factors that may have contributed to the cause of the injury were analysed, rated and reported. The factors analysed were: type of manoeuvre, direction the knee ˜gave way ™, running speed, knee angle, cutting angle and if the player was accelerating or decelerating. The majority of the injuries analysed occurred in non-contact situations (56%). Of these 37% occurred during sidestepping manoeuvres, 32% in landing, 16% land and step, 10% stopping/slowing and 5% crossover cut manoeuvres. Ninety-two percent of the non-contact injuries occurred at extended knee angles of 30° or less, which is also commonly known to place stress on the ACL and reduce the protective role of hamstrings. Over half (54%) of non-contact injuries occurred whilst decelerating. It would be expected that greater speed and angle cut too would increase the frequency of ACL injury. The results could not confirm this with most injuries occurring at running speeds of slow jogging to running and equal number of injuries occurred at cutting to angles of the ranges 15-45° and 45-75°. These results give greater understanding into potential causes or contributors of ACL injury and information to assist in the development of knee injury prevention programs.
Use of Siliconcoach
These researchers used the slow-motion, frame by frame and measurement features of the Siliconcoach software to analyse the mechanics of injuries in Australian rules football players.
Reference
B Elliott, M Khangure. Medicine and Science in Sports and Exercise. Volume 34, Number 11, 2002, Pages 1714-1718.
Source
http://www.acsm-msse.org
(NOTE: Due to copyright restraints, Siliconcoach cannot give away this resource. You can search for the article from the link above, however, a fee or subscription may be charged by the supplier.)
Abstract
Purpose: The purpose of this study was to identify the relationship between the incidence of lumber disk degeneration and bowling technique after 3 yr of educational intervention.
Methods: Two groups of cricketers from the Western Australian fast-bowling development squads acted as subjects in this longitudinal study. Group 1 comprised 24 fast bowlers, of mean age 13.4 yr at the commencement of the study. They attended at least three of the four yearly testing sessions between 1997 and 2000. A further 17 of mean age (in 1998) of 13.2 yr attended a minimum of two of three yearly testing sessions between 1998 and 2000, and comprised group 2. Players were filmed laterally and from above by two video cameras during each testing session. Specific technique variables that previously had been linked with an increased incidence of lumbar disk abnormalities were measured from the videos. Magnetic resonance imaging (MRI) scans of the lumbar disks of each player were also recorded at approximately the same time. A yearly half-day clinic and six small group coaching sessions spread over the season were held to assist the bowlers develop techniques that had been linked with a reduction in back injuries.
Results: Data showed that small group coaching significantly reduced the level of shoulder alignment counter-rotation in young fast bowlers. The incidence and progression of lumbar disk degeneration were also significantly reduced in parallel with this decreased shoulder counter-rotation.
Conclusion: Technique assessment and modifications through an educational process aimed at reducing mechanical features that have been linked to back injury decreased the incidence and/or progression of lumbar spine disk degeneration.
Use of Siliconcoach
These researchers used Siliconcoach software from two camera views to look at trunk and shoulder biomechanics in young cricket bowlers. They also looked at spinal X-rays to gauge spinal degeneration and attempted to find a link between abnormal trunk and shoulder motion when bowling and disk degeneration.
