Research-based personalized exercise

Personalized exercise for every age.

EFEE — Exercise for Everyone, Every Age — is a personalized exercise approach built around Muscle Functional Capacity (MFC). Rather than starting with a standard exercise program, the method begins by assessing the functional capacity of individual muscle groups and identifying where a person's measurable capacities differ. The exercise program is then adapted to the individual instead of asking the individual to adapt to a predetermined routine.

The EFEE approach combines muscle-group measurements with functional and relevant health information to support individualized exercise prescription. This creates a measurement-to-intervention process in which exercise can be directed toward the person's specific functional profile and reassessed over time.

The underlying methodology has already been evaluated in published scientific research. A 12-week pilot study involving 169 participants aged 16–94 used individualized exercise programming based on measured muscle functional capacity and reported substantial within-participant improvements in MFC during the intervention.

We are now developing EFEE into a digital, AI-assisted platform for personalized exercise and longitudinal progress tracking, with particular relevance to healthy aging and older adults.

See the research What we're building

Older adults and children using pneumatic resistance exercise equipment in a bright supervised training environment.

The EFEE Method

Start with the person, not the program.

Conventional exercise programs commonly begin with standardized recommendations about frequency, duration, intensity, repetitions, and general measures of strength or fitness.

EFEE begins from a different question: what is the functional capacity of each measured muscle group relative to a defined reference, and how should the exercise program respond to that profile?

Within the MFC framework, individual muscle groups are measured, expressed relative to reference capacity, and integrated with clinical and functional information through a structured, software-based method to support individualized exercise prescription and repeated reassessment.

169 participants in the published pilot study

16–94 age range represented in the study

12 weeks personalized intervention period

MFC Muscle Functional Capacity

Scientific foundation

Built on published research.

EFEE's scientific foundation is not just a concept. The personalized exercise methodology has been evaluated in a peer-reviewed pilot study, and the broader Muscle Functional Capacity framework has subsequently been developed as a conceptual approach for individualized measurement, follow-up, and future validation.

2025

The Effect of a Personalized Exercise Program on Muscle Functional Capacity and Quality of Daily Life: A Randomized Pilot Study

International Journal of Environmental Research and Public Health, 22(9), 1344

The 12-week pilot involved 169 participants aged 16–94 and reported improvement in the study-specific MFC index during the personalized intervention. The findings support feasibility and further research, but do not by themselves establish comparative effectiveness or predictive validity.

View publication ↗

2026

From Exercise Prescription to Human Functional Capacity Management: A Narrative Review and Conceptual Perspective

Open Journal of Orthopedics and Rheumatology

This work places MFC within a broader framework of muscle-group measurement, individualized prescription, repeated assessment, and longitudinal monitoring, while clearly identifying the validation work still required before predictive or screening use.

View publication ↗

What we're building

From a research-backed method to an AI-assisted digital platform.

We are working to translate EFEE into a digital platform that combines structured functional assessment, progress data, and user feedback to support individualized exercise over time.

AI is being explored as a reasoning and interaction layer: helping interpret structured assessments, explain recommendations in clear language, organize longitudinal information, and support adaptive personalization.

Core physiological calculations and safety rules are intended to remain structured and deterministic rather than being delegated to an unconstrained AI model. The goal is to make a measurement-driven methodology more accessible, explainable, and scalable without overstating the current evidence.

Contact

Interested in EFEE?

We are currently developing EFEE into a digital, AI-assisted platform based on the Muscle Functional Capacity approach and our published research.

If you are interested in the method, research collaboration, future pilot studies, or early access to the platform, we'd be happy to hear from you.