We are always looking for the next revolutionary advancement to optimise our health.
Since the early development of exercise products like the stationary bike, technological improvements have provided individuals with a vast array of fitness metrics and health results. Artificial intelligence (AI) had not yet provided the mainstream fitness industry with the proper access to the equipment needed to reach our health goals in a scientifically accurate manner in a shorter time span.
Before CAR.O.L and the sufficient amount of science behind her creation, it was almost unheard of to rely on AI to accurately personalise our exercise routines based on our body’s current state of health, its riding behaviour, and its overall fitness needs. Unlike a traditional cycle ergometer, CAR.O.L learns about your baseline health to optimize workout resistance and customize cues that will help users achieve their individual exercise goals (Matteo, 2020).
Separate from her scientific features and her ability to perform unlike any other stationary bike on the market, CAR.O.L replaces the need for an exercise physiologist to design, implement, and supervise your workouts.
The science behind interval training was originally introduced in the 1930s by German physician and coach Woldemar Gerschleron Olympic athletes. But its research principles would not be applied to a stationary bike until the 1970s through theWingate Anaerobic test. It [was] commonly performed on a cycle ergometer and primarily used to measure an individual’s anaerobic capacity and anaerobic power outputs (Walker, 2016). Scientists used stationary bikes because ‘physiological responses to exercise on a cycle ergometer differ from those obtained on a treadmill’ (Ito, 2019) or other relevant exercise machinery.
However, typical modern indoor exercise bikes do not offer the level of resistance the rider needs in order to reach maximum intensity. This [type of] exercise cannot be done on a regular bike because of the supra-maximal resistance required that also needs to be tailored to each individual’s goals, needs, and physiology (Ito, 2019).
This is why CAR.O.L is revolutionary.
Her design replaces the need for all the aspects that make access hard, such as replacing the need for a specialist using AI. She is also far more affordable than a traditional cycle ergometer.
At first glance, sure, $2,995 may seem expensive for a generic stationary bike, but CAR.O.L is anything but a generic exercise bike. Her actual value lies on nearly the same level as – if not more than – a cycle lab ergometer, except her slim design resembles the exercise equipment you’d find at your local gym.
Performance analysis lab bikes like the LC7TT (their most advanced cycle ergometer to date) are specifically “designed for medical and therapeutic purposes.”
Needless to say, these bulky lab bike aren’t your average local bike shop staple for obvious reasons. It carries many similar AI components to CAR.O.L, yet lacks fundamental elements to make it suitable for an average home user. These lab bikes are solely used for exercise science research purposes only and because of their complex design, they are expensive. For instance, the LC7TT carries a whopping price tag of £12,900 (~ $17,330 USD).
[CAR.O.L] utilises self-learning algorithms called Cardiovascular Optimisation Logic to adapt the resistance level according to participant’s weight, power output and fatigue index in every session as they get progressively fitter and stronger (Cuddy et. al, 2019). This happens during your first six introductory rides, which are called ‘calibration rides.’ The calibration process for lab bikes like LC7TT require people with the knowledge, familiarity and practice to manually calibrate the ergometer through a computer. According to Dr. Niels Vollaard, professor of Health and Exercise Science at Stirling University, lab bikes “must be controlled by a computer…specialized software and expensive hardware are [also] needed” (2019).
CAR.O.L is the only system that accurately replicates my research outside of the labs (Vollaard, 2019). CAR.O.L has proven itself to be a product that will forever change the way we have been conditioned to think in terms of reaching our desired health and fitness goals. But the regular additions, modifications and developments being made on the bike further demonstrates its unique multi-capability, while upholding its core purpose and significance for the user.
Referenced Sources in this Post:
Kummer M. (2019) ‘CAR.O.L Bike Review’. Michael Kummer Blog. Assessed: 08 Aug. Available at: https://michaelkummer.com/health/fitness/carol-hiit-bike-review/
Matteo, A. (2020) ‘A.I. Home Fitness Machines Push You Past Your Limits’. The Wall Street Journal. Assessed: 12 May. Available at: https://www.wsj.com/articles/a-i-home-fitness-machines-push-you-past-your-limits-11589309016
Cuddy, T. et. al (2019) ‘Reduced Exertion High-Intensity Interval Training is More Effective at Improving Cardiorespiratory Fitness and Cardiometabolic Health than Traditional Moderate-Intensity Continuous Training’. International Journal of Environmental Research and Public Health. Assessed: 07 February.
Walker, O. (2016) ‘Wingate Anaerobic Test’. Science for Sport. Assessed: 27 January. Available at: https://www.scienceforsport.com/wingate-anaerobic-test.html
Ito, S. (2019) ‘High-intensity interval training for health benefits and care of cardiac diseases - The key to an efficient exercise protocol’. Division of Cardiology at Sankuro Hospital. Assessed: 26 July.