I'm excited to join VAY as advisor and investor. VAY is a Swiss health-tech start-up focused on democratizing human motion analysis. In this article, I wanted to give a bigger context and talk about the reasons behind my decision to team up with VAY.
Vision behind VAY
VAY's mission is to democratize human motion analysis by leveraging readily available consumer devices and benefits from latest improvements in camera technologies in mobile phones, tablets, and other devices. The solution is based on cutting-edge computer vision and machine learning approaches to perform anatomically correct assessment for range of motion, angles of joints, velocities, and recognized repetitions of movement patterns.
Why it matters: The big picture
With advanced sensors or even a gait lab, researchers have been able to demonstrate that human motion analysis can be used to detect musculoskeletal imbalances and predict injury risk (e.g. [1, 2]), predict fall risk (e.g. [3, 4, 5]), and potentially detect early signs of cognitive and mental impairments (e.g. [6, 7, 8]). This opens up unforeseen possibilities to promote health and well-being. Here are just a few examples to illustrate the extent of the problem: Musculoskeletal disorders are the leading contributor to disability worldwide and every third person suffering from musculoskeletal condition. According to WHO, falls are the leading cause of accidents and unintentional deaths worldwide. Cognitive disorders are also on the rise where WHO estimates that the number of people with dementia will triple by 2050.
What would happen if you could perform human motion analysis with readily available consumer devices? This is where VAY could make a substantial contribution to mitigate some of the biggest health issues of our times. VAY is in good company. Several big tech companies have realized that they could disrupt the healthcare market. Apple even goes as far as claiming that their biggest contribution to society will be in the health area.
I believe, if you zoom out into the future, and you look back, and you ask the question, ‘What was Apple’s greatest contribution to mankind?’ it will be about health
But let’s focus back on VAY and the reasons behind my decision to team up with them.
Reason #1: Team
Let me first start with the main reason that convinced me that I wanted to become a part of VAY: the team. Hardened by over 1.5 years of bootstrapping and exploring various technology paths (including sportswear full of sensors), the team is exuding an incredible amount of energy and drive. Joel & Ben have managed to assemble a strong & interdisciplinary team that combines talents from human motion sciences & sports, computer vision, robotics, machine learning, full stack programming, and business.
Reason #2: Tech
The team is focused on leveraging latest research results & advances in machine learning as part of their unique technology. In general, the challenge is to build a system that is reasonably accurate, robust, and applicable to a full demographic coverage. Engineering such a learning-based system is a highly complex task and requires discipline and the right methodology. VAY has already demonstrated to first customers that they are able to ship on time and in the right quality and so I believe that they will be able to further capitalize on their strength.
Reason #3: Timing
Accelerated by COVID-19, the awareness on health is even higher than before. For some people, it becomes a new normal that Yoga & fitness classes are taught through video conferencing and there is an increasing demand for personalized fitness machines. VAY's technology can help to unblock and scale these cases as demonstrated with early customers. The technology can give easy feedback on posture correction and also quantify progress over time. But what is beyond this excites me even more. As the accuracy of the motion analysis increases, it could potentially assist healthcare professionals to predict injury risks early, provide screening of imbalances, monitor fall risk for elderly, or even aid rehabilitation and digital therapeutic measures. It may even help to run clinical trials in a more scalable and cost efficient way by turning consumer devices into a “mobile gait lab”.
As a start-up in the seed stage, there are of course still many things to figure out. While writing this article, VAY has secured a term-sheet for its seed round with an institutional lead investor, several committed business angels (including myself), as well as DART Labs and is aiming to close the round in the next month. Given the energy and potential of VAY, I cannot wait to see where VAY stands in a few years.
Witvrouw, 2003, Muscle flexibility as a Risk Factor for developing Muscle Injuries in Male Professional Soccer Players: A Prospective Study. (https://journals.sagepub.com/doi/full/10.1177/03635465030310011801)
Numata, 2017, Two-dimensional motion analysis of dynamic knee valgus identifies female high school athletes at risk of non-contact anterior cruciate ligament injury. (https://link.springer.com/article/10.1007/s00167-017-4681-9)
Verghese, 2009, Quantitative Gait Markers and Incident Fall Risk in Older Adults. (https://pubmed.ncbi.nlm.nih.gov/19349593/)
Mehdizadeh, 2020, Vision-Based Assessment of Gait Features Associated With Falls in People With Dementia (https://pubmed.ncbi.nlm.nih.gov/31428758/)
Hausdorff, 2001, Gait Variability and Fall Risk in Community-Living Older Adults: A 1-Year Prospective Study (https://pubmed.ncbi.nlm.nih.gov/11494184/)
Bahureksa, 2016, The Impact of Mild Cognitive Impairment on gait and Balance: a Systematic Review and Meta-Analysis of Studies using Instrumented Assessment. (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5107359/)
Muurling, 2020, Gait Disturbances are Associated with Increased Cognitive Impairment and Cerebrospinal Fluid Tau Levels in a Memory Clinic Cohort. (https://pubmed.ncbi.nlm.nih.gov/32597806/)
Shinkawa, 2019, Multimodal Behavioural Analysis Towards Detecting Mild Cognitive Impairment: Preliminary Resulst on Gait and Speech. (https://pubmed.ncbi.nlm.nih.gov/31437942/)