FP-00035

Section 1 - Basic information about you and your application:

Title of research project
Commercial pilot of a biomechanical Anterior Cruciate Ligament (ACL) Risk Assessment screening tool focused on female sports professionals who typically suffer much greater ACL injury rates than males.

Grant Type
The Ronald Furlong Fund

Research area
Diagnostic

Duration
12 months

Start date
January 1, 2024

Have you previously received funding from ORUK?
No.

Profession
Entrepreneur

Your current job title/position
Chief Executive

Are you an early-career researcher (ECR)? (definition of ECR)
no

Section 2 - Lay summary

Lay summary:

Joint Analytics aims to transform musculoskeletal health by making clinical-grade movement scans available to anyone. Using proven, cutting-edge technology of the highest accuracy, integrated with advanced AI, non-skilled staff can deliver scan results securely anywhere in the world.

Brazilian footballer Neymar is the latest high-profile athlete to sustain an ACL tear, but these are near-daily news items, particularly in female sport. ACL injuries are common, usually affecting young, active individuals and the commonest knee injury requiring surgery (1).

Currently a player and their team realise the risk of an ACL injury happening when it happens.

Being able to identify athletes at the highest risk of suffering an ACL injury early will enable preventative strategies to be implemented. These range from special warm up exercises to personalised strength and conditioning programmes.

Furthermore, regular movement scans with instantaneous results, enables tracking of ACL injury risk and triggering of warning notifications to both players and team medics. This aspect will be transformative for ACL injury risk prevention.

Much research on ACL injury screening has been done (3), but the biggest problem is not lack of research but understanding and translating the research findings into services that can be used to reduce injury risk.

As in the medical world, with conditions such as stroke and heart attacks, by identifying risk factors such as high blood pressure and then monitoring the effects of medication, Joint Analytics aim to reduce ACL injury problems by providing early automated identification of risk and then monitoring and reassessing.

Historically, such complex measures of movement can only be carried out in specialist laboratories not available to the general public. With Joint Analytics technology the service is mobile, so can be provided anywhere.  The collaboration between engineers, scientists and surgeons has developed an automated system that not only immediately processes data, but also displays results securely, instantaneously online, without requiring a medical degree to interpret them.

Joint Analytics would like investment from ORUK to help scale up the company to make the technology accessible nationally and internationally.

Joint Analytics is currently starting a pilot of this service with the 150 members of the Cambridge University Ospreys female athletics team, part funded by the Gwen Fish charity. They will each be scanned multiple times over a 3-4 month period and each time receive a Red-Amber-Green traffic light system to indicate risk of ACL injury. Results will be available immediately online to the team members and their team physio. This pilot will provide the foundation for commercial service launch.

Joint Analytics make money from this service from a £100 per-scan fee. This covers all the biomechanics heavy lifting data analytics as well was the web services needed to make everything simple to access.

Section 3 - Purpose of research

Purpose of research:

The project is a commercial pilot of an ACL Risk Assessment service delivered at customer premises and at-scale.

This project will confirm the commercial viability of this solution as part of a preventative strategy to reduce the occurrence of ACL injury. This will lead to further investment, needed to scale nationally and internationally.

We know the ACL screening test researched by Myers et al works. Despite being published almost 20 years ago it has never been translated into commercial product or made available to the benefit of the wider world.  This is a common theme for biomechanics research. This lack of translation is due in large part to the need for precision test equipment. Consumer equipment and Apps simply do not deliver the resolution required for viable tests.

Clinically valid biomechanics analysis, such as required for ACL testing, requires expensive, complex equipment only available in specialised laboratories, until now. Joint Analytics has created a mobile clinic capable of delivering this data in the community. With AI technology at its heart to automate the complex and time consuming data analytics processing, this enables high volumes of scans at low cost, with results available immediately.

However, smart research and advanced technology are not enough to benefit the people who need it most. Services must be commercially viable and easily available. Joint Analytics platform has been developed specifically to make this validated technology accessible to the wider world.

The ACL service is the tip of an iceberg demonstrating that even 20 year-old research can be translated into something profoundly useful and commercially viable. The eco-system created to deliver this will provide the translational “route to market” for many existing and future MSK biomechanics research findings.

Section 4 - Background to investigation

Background to investigation:

Joint Analytics will transform musculoskeletal health by bringing movement scans into mainstream use with proven, cutting-edge, technology. The service can be delivered by non-skilled staff and the results shared securely anywhere in the world. An example of how ACL risk results are presented is shown in the attachment.

• Brazilian footballer Neymar is the latest high-profile athlete to sustain an Anterior Cruciate Ligament (ACL) tear. ACL injuries result in a personal cost, teams and/or workplace with time lost from the sport, psychological effects, and consequences to long-term health and wellbeing. 2022/2023 Premier League ACL injuries resulted in total absence costs of £9,499,857 (1)
• Maheta Molango, chief executive of the Professional Footballers Association, said the “ number 1 topic” with players and managers is injury prevention (2).
• Within women’s football there is a so-called ACL epidemic. “The players are asking for research,” Alex Culvin, FIFPro’s head of strategy and research.
• FIFA’s Sarai Bareman announced the governing body had established a specific task force to focus on ACL injuries (3)

ACL injuries are common, usually affecting young, active individuals and are the most common knee injury requiring surgical intervention (4). Though good outcomes are achieved, only half of patients can return to their preinjury state (5).

A great deal of research has been done on ACL screening (6) which has identified clear markers for risk. However, this research has not translated into a usable tool for athletes and coaches.

As well as screening for ACL injury risk, injury prevention programmes can be biomechanically and objectively assessed. A recent review of eight meta-analysis articles (7), found a 67% reduction in the risk of non-contact ACL injuries in female athletes following systematic prevention programmes.

In work spanning over two decades Myer and Hewett have developed objective risk assessment tools that can identify athletes at risk of non-contact ACL injury, these have been shown to have high sensitivity and specificity. (8–13)

These tests have been optimised to focus on the biomechanical features of the “drop vertical jump” test and specifically focus on the features of the knee abductor moment (KAM) (11). Knee moments (the turning forces that act to twist and turn a joint) can be effectively identified using the combined precision measurement of 3d joint position and 3d force measurement.

Though it is recognised that there are many contributing factors to non-contact ACL injury including developmental and hormonal status (14–16)  there is strong evidence that evaluating knee mechanics alone combined with anthropometric factors such as limb length and body weight, identifies ACL injury risk (7) .

An ACL test comprises of a series of drop and vertical jump movements. These movements are similar to the movement a netball or basketball player would make jumping up to push the ball into the goal / basket.

To perform the test the player slides off a platform approximately 31 cm off the ground and lands, bending their knees to absorb the impact. They immediately push themselves upward trying to jump as high as they can. The risk factors are calculated between the times the player lands, initial contact, to the point at which they are at maximum shock absorption, which is when the player has crouched to their lowest point. The DVJ test is illustrated in the attachment.

The positions of the players’ knees are known by using a markered, motion capture system. The force acting across the knee is measured using a force plate which the player lands on. The ability of the player to control their landing, and the position of the knee, will change the size and direction of the force acting through the knee and therefore change their ACL injury risk factor. These tests have been shown to have excellent inter and intra trial repeatability (17)

In a study of over 200 17-18 year old players statistical methods were used to identify the key biomechanical predictors of ACL injury. A predictor threshold of 25.25kNm of knee abduction moment (KAM) during a drop vertical jump test showed excellent prediction when reviewing those players who subsequently suffered a ruptured ACL. (8)

The risk assessment was subsequently conducted in over 700 17-18 year olds. Using KAM moment threshold, players were classified in relation to risk of high forces across their knee. This work indicated a low presence of false positives results (18%) and a low presence of false negative results (23%)(9,13)

Importantly, work has been completed valuating the effect of training programs that used to reduce the chance of ACL injury in those classified at risk (10). This work has shown there is a very low risk of harm due to the training programmes themselves. This is an important finding which further promotes the wide-spread adoption of ACL injury risk assessment and prevention training.(11)

Although given the excellent and repeatable results presented in these series of journal articles, these techniques have, until now, failed to be widely deployed. Grassroot prevention programmes like Power Up to Play (18) are aiming to raise awareness and reduce ACL injury, but do not yet have an objective tool to screen or measure the effectiveness of the prevention programme. One reason for this lack of adoption may be the reliance of the tests on highly specialised staff and complex facilities.

This project will provide a route to impact for this seminal work by providing a highly scalable and accessible biomechanical measurement facility which enables the envisioned routine screening of athletes at risk of non-contact ACL injury.

As in the medical world with conditions such as stroke and heart attacks, by identifying risk factors such as high blood pressure and then monitoring the effects of medication, Joint Analytics technology aims to provide equivalent automated identification, monitoring, and reassessment for ACL injury.

Through Joint Analytics, the collaboration between engineers, scientists and surgeons has developed an automated system that immediately processes data, and displays the results securely online, almost instantaneously, without requiring a medical degree to interpret them.

Finally, attachments show the clinic layout and a list of references

Section 5 - Plan of investigation

Plan of investigation:

This proposal is for a commercial pilot of our non-contact ACL Risk Assessment service in the sports sector. The initial focus will be professional female football clubs where there is a high prevalence of ACL injury. The scope will then extend to the male counterparts in these same clubs.  Once established in the high performance sector the programme can be rolled out nationally and internationally to help prevent and reduce ACL injury risk in grassroots sports.

The objectives:

• to confirm there is a strong commercial demand and market for the service
• establish value of ACL risk tracking to individual athletes and clubs
• build the market for each club to buy their own dedicated clinic
• establish firm foundation for series A investment

The project will involve three work packages:

5.1                           Technology development

Joint Analytics’ engagements to date with the sports sector (and indeed healthcare and other sectors) have highlighted that the mobile clinic and capability to perform scans at customer premises and the wider community, is integral to the overall proposition.

This project will enhance the existing prototype mobile clinic to secure and fulfil contracts with selected, professional football clubs. This enhancement is necessary to improve the robustness and reliability for maximal throughput of scanning.

Clinically accurate motion capture equipment is specialist and expensive. It is developed by specialist companies for low volume, fixed installation research laboratory applications. Joint Analytics prototype has made significant modifications to the hardware to enable mobile deployment and fast data collection by low skilled staff. However, it remains a single prototype and carries a high business risk in case of failures.

A typical clinic day at a sports club involves the clinic operator arriving at the venue, unloading and setting up the equipment within 30mins. 20 scans can follow throughout the day and then the equipment is packed up and transported to the next venue. There is a higher probability of equipment failure in this environment and this workpackage will enhance the mobile clinic equipment to minimise risk.

This workpackage will deliver

• Smaller, lighter packaging solution for motion capture, video and force sensors
• More robust packaging solution suitable for daily deployment at multiple venues around the country
• Enhanced instrumented walkway meeting all health & safety requirements
• Improved force sensor capability optimised for sports
• Improve robustness of clinic setup to include industrial grade components as appropriate

5.2                           Customer acquisition.

There are currently 12 Women’s Super League football teams in England and contact with several of their medical teams has been established. These will be developed into contracts, and further club contacts added to the project, such as the men’s squads, which are larger and the cost of ACL injury at present is greater to the respective clubs. The target over the 12 months will be to have confirmed at least 6 professional football clubs as paying clients for the ACL risk service.

The baseline service for all clubs will be the same: our standardised ACL Risk Assessment Test to identify high (red) and moderate (amber) at risk individuals for personalised strength and conditioning. Each club will then decide how many players to scan and how frequently they want tracking. JAs recommendation will be the entire squad at least half yearly and all Red/Amber identified players monthly.

Acquisition of each club (meaning securing a contract to deliver ACL risk assessment scans) may involve an initial free promotional offer. We have budgeted for 20 free scans for each of the 6 clubs to demonstrate how everything works and help motivate them towards a paying service.

During the commercial pilot phase Joint Analytics will work very closely with team physios and medics to better understand what they like and want from the service. This will be invaluable to improve the product and optimise it for the subsequent national and international scaling phase of business.

5.3                           Project review and analysis

The clear objective of the project is to successfully deliver to the players and their teams valuable information to help them reduce ACL injury rates at their clubs. While doing this, and at the end of the project, we will review and report on key findings important for scaling up subsequent phases.

We will:

• Report on revenue generated by the sports teams involved in the commercial pilot
• Report on a profitability and service pricing review and analysis
• Report on market research questionnaires from individual players and team medics

Given the very short time available to submit this application the project plan needs further work to highlight not only detailed milestones and deliverables, but also to more fully explain the quality management procedures and risk mitigation strategies. This should be considered more of an outline plan which we will try to expand upon at the presentation.

Section 6 - Research environment and resources

Research environment and resources:

This project is foremost a commercial project and Joint Analytics (JA) has the necessary commercial expertise and partners to deliver the objectives of the project.

JA has an experienced team of software developers to ensure the efficient delivery of a scalable service to ensure the project goals are met. The team are experienced in product delivery especially in agile software development. The team are experienced in sectors requiring great sensitivity in the management of private and health related data with specific knowledge in international standards of data security.

Although this work is not within the scope of medical device regulation, future exploitation is likely to be. Therefore, the team’s strong expertise in the management of software as a medical device and related regulation is of significant benefit.

JA also accesses a breadth of professional expertise in the areas of clinical biomechanics (Thomas Stone), public and private surgical pathways (Niel Kang), physiotherapy including sports therapy (Kevin Hunt).

JA engages external partners with whom they have a long-standing working relationship to support the delivery of marketing and customer engagement. Ensuring that this vital commercial specialism is undertaken and delivered effectively.

The primary route to market is through the power up to play program and Associate Professor Stephen McDonnell is part of the project team specifically to ensure this partnership is effective.

Although this is a commercial pilot it is recognised that taking this work forward will need the engagement and support of academic partners to build an increasingly strong clinical evidence base to meet the threshold of evidence needed by most national health systems and insurance companies. Therefore, Joint Analytics also engages with a wider academic and clinical ecosystem, enabling it in the future to efficiently diversify the learning from this project into other sectors.

Joint Analytics has a strong record working with local universities and health organisations. Both internally and through its collaborative relationships, it has the skills, knowledge and expertise to deliver on wider research and development projects.

JA has worked with Cambridge University, Anglia Ruskin University and the University of East Anglia to deliver health related research projects. Although, this is a commercial proof of concept project JA’s academic links will enable it to ensure the proper dissemination of the results of this work. This will also ensure the foundation for continued funding and the realisation of wider research impact.

Section 7: Research impact

Who will benefit from this research?

Individuals who play sports with reduced non-contact ACL injury rates and subsequent reduction of arthritic sequelae.

Professional and amateur clubs with reduced non-contact ACL injury rates will benefit both from sporting performance and financial perspectives.

Healthcare, institutions such as the NHS will have less patients requiring diagnostic imaging and surgery for ACL reconstruction and future knee replacement for arthritic sequelae.

This project is a gateway to the commercial launch of a transformative platform developed specifically for MSK healthcare. The platform is designed to enable easy access to a constant stream of novel and much needed diagnostic of human function. The platform will evolve to provide tests for hip and knee OA, frozen shoulders, prosthetic limb calibration and optimisation, for example.   

How can your research be translated in real-life?

This is the key objective of this project and the purpose of the Joint Analytics platform. Biomechanics research has traditionally been laboratory based with no obvious route to be accessible in real-life situations.

Translation of research into real-life application project will demonstrate the commercial viability in the professional sports sector of having an easily accessible test for non-contact ACL injury risk, the test itself having been translated from validated research.

Beyond this initial ACL project, many more tests for MSK pathologies will be translated and added to the platform. Application within the healthcare sector is the primary longer term target of this capability and Joint Analytics has initiative parallel to this project to gain medical device regulation and support large-scale clinical trials.

How will your research be beneficial for ORUK and its purpose?

This technological development of screening for non-contact ACL injury risk and the effectiveness of prevention programmes aligns with the ORUK strategies of reducing the burden, on individuals and healthcare systems, of musculoskeletal injuries and pioneering different forms of imaging.

This project will provide objective evidence, that with time and data will become more refined through machine learning, all available for therapists, coaches and athletes without increasing the burden upon traditional healthcare providers. This also aligns with the ORUK vision of introducing and cultivating the appropriate use of AI within MSK healthcare.

The investment of funds to enable this commercial pilot to happen will make Joint Analytics suitable for Series A funding from the commercial sector within 12-18 months. Series A funding will be targeted at scaling the company nationally and internationally to create a significant Return on Investment for ORUK.

Section 8: Outreach and engagement

This work is inspired by Joint Analytics engagement with key stakeholders in the life sciences, health and biomechanics field. The identification of ACL injury as an important health condition is as a result of our outreach work.

Although we are evaluating a commercial service in this project, the delivery of this service and subsequent re-design will be predicated on the user-centred evaluation as part of this project. User centred design is a key/central concept in the development of Joint Analytics services.

We are working with the University sports teams to help optimise services for athletes at risk of ACL injury. This means that a significant part of our current work is directly driven by our customers who are helping design and run service development projects. It is intended that this empowers people who will ultimately use the services and enables them to play a key role in their development.

A key component of this project is to work interactively with the both the individual players and team medics and coaches in the various football clubs. This interactive working will lead to improvements in the product both in terms of how results are presented but also in what data is collected and analysed. This engagement will be aimed at improving the real-life usage of the service. We will ensure that the results of this work are communicated to key stakeholders through national presentations and publications in sporting journals and across social media channels.

Joint Analytics have completed a spectrum of clinician-initiated biomechanics projects, such as hip and knee osteoarthritis triaging, balance testing, lower limb prosthetics selection and shoulder diagnostic screening which can also be developed into fully fledged services to cater for a high volume and diverse range of conditions.

Section 9: Research budget

Requested funding from ORUK

University fees (if any)
£0

Salary
£75000

Consumables
£0

Publications
£0

Conference attendance
£0

Other items
£45000

Total 'requested fund'
£120000



Other items
Web services and other platform costs - £5,000 Clinic equipment materials annd components - £40,000 Promotional scans for customer acquisition - £30,000 (paid by Joint Analytics) With the level of funding outlined, the hardware development workpackage in this project necessitates that we develop and commercially operate in parallel using the same prototype equipment. This is very risky and inefficient. Ideally, a further £75k would be required to allow for the purchase of the relevant equipment to enable independent operations. We are unsure if this is beyond the scope of the application and so have omitted it.



Other secured funds

Internal funding
£30000

Partner (University)
£0

Partner (Commercial)
£0

Partner (Charity)
£0

Other sources
£0

Total 'other funds)
£30000

Section 10: Intellectual property and testing on animal

Is there an IP linked to this research?
No

Who owns and maintains this patent?


Does your research include procedures to be carried out on animals in the UK under the Animals (Scientific Procedures) Act?
No

If yes, have the following necessary approvals been given by:

The Home office(in relation to personal, project and establishment licences)?


Animal Welfare and Ethical Review Body?


Does your research involve the use of animals or animal tissue outside the UK?
No

Does the proposed research involve a protected species? (If yes, state which)



Does the proposed research involve genetically modified animals?


Include details of sample size calculations and statistical advice sought. Please use the ARRIVE guidelines when designing and describing your experiments.


There should be sufficient information to allow for a robust review of any applications involving animals. Further guidance is available from the National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs), including an online experimental design assistant to guide researchers through the design of animal experiments.

Please provide details of any moderate or severe procedures


Why is animal use necessary, are there any other possible approaches?


Why is the species/model to be used the most appropriate?